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2310.10395
Elizabeth Munch
Elizabeth Munch
An Invitation to the Euler Characteristic Transform
null
null
null
null
cs.CG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The Euler characteristic transform (ECT) is a simple to define yet powerful representation of shape. The idea is to encode an embedded shape using sub-level sets of a a function defined based on a given direction, and then returning the Euler characteristics of these sublevel sets. Because the ECT has been shown to b...
[ { "created": "Mon, 16 Oct 2023 13:38:48 GMT", "version": "v1" } ]
2023-10-17
[ [ "Munch", "Elizabeth", "" ] ]
The Euler characteristic transform (ECT) is a simple to define yet powerful representation of shape. The idea is to encode an embedded shape using sub-level sets of a a function defined based on a given direction, and then returning the Euler characteristics of these sublevel sets. Because the ECT has been shown to be ...
2012.13990
Mitsuo Yoshida
Kenshin Sekimoto, Yoshifumi Seki, Mitsuo Yoshida, Kyoji Umemura
The metrics of keywords to understand the difference between Retweet and Like in each category
The 2020 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT '20)
null
10.1109/WIIAT50758.2020.00084
null
cs.IR cs.DL cs.SI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The purpose of this study is to clarify what kind of news is easily retweeted and what kind of news is easily Liked. We believe these actions, retweeting and Liking, have different meanings for users. Understanding this difference is important for understanding people's interest in Twitter. To analyze the difference ...
[ { "created": "Sun, 27 Dec 2020 18:32:19 GMT", "version": "v1" } ]
2021-12-16
[ [ "Sekimoto", "Kenshin", "" ], [ "Seki", "Yoshifumi", "" ], [ "Yoshida", "Mitsuo", "" ], [ "Umemura", "Kyoji", "" ] ]
The purpose of this study is to clarify what kind of news is easily retweeted and what kind of news is easily Liked. We believe these actions, retweeting and Liking, have different meanings for users. Understanding this difference is important for understanding people's interest in Twitter. To analyze the difference be...
2203.08189
Elizabeth Coda
Elizabeth Coda, Nico Courts, Colby Wight, Loc Truong, WoongJo Choi, Charles Godfrey, Tegan Emerson, Keerti Kappagantula, Henry Kvinge
Fiber Bundle Morphisms as a Framework for Modeling Many-to-Many Maps
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
While it is not generally reflected in the `nice' datasets used for benchmarking machine learning algorithms, the real-world is full of processes that would be best described as many-to-many. That is, a single input can potentially yield many different outputs (whether due to noise, imperfect measurement, or intrinsi...
[ { "created": "Tue, 15 Mar 2022 18:38:56 GMT", "version": "v1" }, { "created": "Fri, 29 Apr 2022 15:40:25 GMT", "version": "v2" } ]
2022-05-02
[ [ "Coda", "Elizabeth", "" ], [ "Courts", "Nico", "" ], [ "Wight", "Colby", "" ], [ "Truong", "Loc", "" ], [ "Choi", "WoongJo", "" ], [ "Godfrey", "Charles", "" ], [ "Emerson", "Tegan", "" ], [ "Kappag...
While it is not generally reflected in the `nice' datasets used for benchmarking machine learning algorithms, the real-world is full of processes that would be best described as many-to-many. That is, a single input can potentially yield many different outputs (whether due to noise, imperfect measurement, or intrinsic ...
2102.03482
Bo Han
Jianing Zhu, Jingfeng Zhang, Bo Han, Tongliang Liu, Gang Niu, Hongxia Yang, Mohan Kankanhalli and Masashi Sugiyama
Understanding the Interaction of Adversarial Training with Noisy Labels
null
null
null
null
cs.LG
http://creativecommons.org/licenses/by-nc-nd/4.0/
Noisy labels (NL) and adversarial examples both undermine trained models, but interestingly they have hitherto been studied independently. A recent adversarial training (AT) study showed that the number of projected gradient descent (PGD) steps to successfully attack a point (i.e., find an adversarial example in its ...
[ { "created": "Sat, 6 Feb 2021 02:45:03 GMT", "version": "v1" }, { "created": "Tue, 9 Feb 2021 06:12:49 GMT", "version": "v2" } ]
2021-02-10
[ [ "Zhu", "Jianing", "" ], [ "Zhang", "Jingfeng", "" ], [ "Han", "Bo", "" ], [ "Liu", "Tongliang", "" ], [ "Niu", "Gang", "" ], [ "Yang", "Hongxia", "" ], [ "Kankanhalli", "Mohan", "" ], [ "Sugiyama", ...
Noisy labels (NL) and adversarial examples both undermine trained models, but interestingly they have hitherto been studied independently. A recent adversarial training (AT) study showed that the number of projected gradient descent (PGD) steps to successfully attack a point (i.e., find an adversarial example in its pr...
2406.13018
William Liem
William Liem, Andrew Berry, Kathryn Macapagal
Reclaiming Power over AI: Equipping Queer Teens as AI Designers for HIV Prevention
In CHI 2024: Designing (with) AI for Wellbeing
null
null
null
cs.HC
http://creativecommons.org/licenses/by/4.0/
In this position paper, we explore the potential of generative AI (GenAI) tools in supporting HIV prevention initiatives among LGBTQ+ adolescents. GenAI offers opportunities to bridge information gaps and enhance healthcare access, yet it also risks exacerbating existing inequities through biased AI outputs reflectin...
[ { "created": "Tue, 18 Jun 2024 19:25:22 GMT", "version": "v1" } ]
2024-06-21
[ [ "Liem", "William", "" ], [ "Berry", "Andrew", "" ], [ "Macapagal", "Kathryn", "" ] ]
In this position paper, we explore the potential of generative AI (GenAI) tools in supporting HIV prevention initiatives among LGBTQ+ adolescents. GenAI offers opportunities to bridge information gaps and enhance healthcare access, yet it also risks exacerbating existing inequities through biased AI outputs reflecting ...
2307.00729
Qilong Yuan
Sheng Zhao, Qilong Yuan, Yibo Duan and Zhuoyue Chen
An End-to-End Multi-Module Audio Deepfake Generation System for ADD Challenge 2023
null
null
null
null
cs.SD cs.CL eess.AS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The task of synthetic speech generation is to generate language content from a given text, then simulating fake human voice.The key factors that determine the effect of synthetic speech generation mainly include speed of generation, accuracy of word segmentation, naturalness of synthesized speech, etc. This paper bui...
[ { "created": "Mon, 3 Jul 2023 03:21:23 GMT", "version": "v1" } ]
2023-07-04
[ [ "Zhao", "Sheng", "" ], [ "Yuan", "Qilong", "" ], [ "Duan", "Yibo", "" ], [ "Chen", "Zhuoyue", "" ] ]
The task of synthetic speech generation is to generate language content from a given text, then simulating fake human voice.The key factors that determine the effect of synthetic speech generation mainly include speed of generation, accuracy of word segmentation, naturalness of synthesized speech, etc. This paper build...
1601.04621
Benjamin Chamberlain
Benjamin Paul Chamberlain, Clive Humby, Marc Peter Deisenroth
Probabilistic Inference of Twitter Users' Age based on What They Follow
9 pages, 9 figures
null
null
null
cs.SI stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Twitter provides an open and rich source of data for studying human behaviour at scale and is widely used in social and network sciences. However, a major criticism of Twitter data is that demographic information is largely absent. Enhancing Twitter data with user ages would advance our ability to study social networ...
[ { "created": "Mon, 18 Jan 2016 17:40:56 GMT", "version": "v1" }, { "created": "Fri, 24 Feb 2017 15:02:37 GMT", "version": "v2" } ]
2017-02-27
[ [ "Chamberlain", "Benjamin Paul", "" ], [ "Humby", "Clive", "" ], [ "Deisenroth", "Marc Peter", "" ] ]
Twitter provides an open and rich source of data for studying human behaviour at scale and is widely used in social and network sciences. However, a major criticism of Twitter data is that demographic information is largely absent. Enhancing Twitter data with user ages would advance our ability to study social network ...
2207.08860
Mathew Schwartz
Xun Zhang, Mathew Schwartz, Muhammad Usman, Petros Faloutsos, Mubbasir Kapadia
Optimizing Indoor Navigation Policies For Spatial Distancing
9 pages, 8 figures, conference-- simulation in architecture and urban design, in-cooperation with ACM SIGSIM
null
null
null
cs.MA cs.AI cs.GR cs.RO
http://creativecommons.org/licenses/by-nc-sa/4.0/
In this paper, we focus on the modification of policies that can lead to movement patterns and directional guidance of occupants, which are represented as agents in a 3D simulation engine. We demonstrate an optimization method that improves a spatial distancing metric by modifying the navigation graph by introducing ...
[ { "created": "Sat, 4 Jun 2022 21:57:22 GMT", "version": "v1" } ]
2022-07-20
[ [ "Zhang", "Xun", "" ], [ "Schwartz", "Mathew", "" ], [ "Usman", "Muhammad", "" ], [ "Faloutsos", "Petros", "" ], [ "Kapadia", "Mubbasir", "" ] ]
In this paper, we focus on the modification of policies that can lead to movement patterns and directional guidance of occupants, which are represented as agents in a 3D simulation engine. We demonstrate an optimization method that improves a spatial distancing metric by modifying the navigation graph by introducing a ...
1610.09610
Ashish Sureka
Vidushi Chaudhary, Vishnu Agrawal and Ashish Sureka
An Experimental Study on the Learning Outcome of Teaching Elementary Level Children using Lego Mindstorms EV3 Robotics Education Kit
Extended version of the accepted and to be published paper in T4E 2016 The 8th IEEE International Conference on Technology for Education
null
null
null
cs.CY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Skills like computational thinking, problem solving, handling complexity, team-work and project management are essential for future careers and needs to be taught to students at the elementary level itself. Computer programming knowledge and skills, experiencing technology and conducting science and engineering exper...
[ { "created": "Sun, 30 Oct 2016 07:03:02 GMT", "version": "v1" } ]
2016-11-01
[ [ "Chaudhary", "Vidushi", "" ], [ "Agrawal", "Vishnu", "" ], [ "Sureka", "Ashish", "" ] ]
Skills like computational thinking, problem solving, handling complexity, team-work and project management are essential for future careers and needs to be taught to students at the elementary level itself. Computer programming knowledge and skills, experiencing technology and conducting science and engineering experim...
1611.08951
Rodrigo de Lamare
C. T. Healy and R. C. de Lamare
Distributed Estimation for Adaptive Networks Based on Serial-Inspired Diffusion
8 figures
null
null
null
cs.MA
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Distributed estimation and processing in networks modeled by graphs have received a great deal of interest recently, due to the benefits of decentralised processing in terms of performance and robustness to communications link failure between nodes of the network. Diffusion-based algorithms have been demonstrated to ...
[ { "created": "Mon, 28 Nov 2016 01:10:54 GMT", "version": "v1" } ]
2016-11-29
[ [ "Healy", "C. T.", "" ], [ "de Lamare", "R. C.", "" ] ]
Distributed estimation and processing in networks modeled by graphs have received a great deal of interest recently, due to the benefits of decentralised processing in terms of performance and robustness to communications link failure between nodes of the network. Diffusion-based algorithms have been demonstrated to be...
2305.00316
Liangzu Peng
Liangzu Peng, Paris V. Giampouras, Ren\'e Vidal
The Ideal Continual Learner: An Agent That Never Forgets
Accepted to ICML 2023
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The goal of continual learning is to find a model that solves multiple learning tasks which are presented sequentially to the learner. A key challenge in this setting is that the learner may forget how to solve a previous task when learning a new task, a phenomenon known as catastrophic forgetting. To address this ch...
[ { "created": "Sat, 29 Apr 2023 18:06:14 GMT", "version": "v1" }, { "created": "Thu, 8 Jun 2023 03:39:48 GMT", "version": "v2" } ]
2023-06-09
[ [ "Peng", "Liangzu", "" ], [ "Giampouras", "Paris V.", "" ], [ "Vidal", "René", "" ] ]
The goal of continual learning is to find a model that solves multiple learning tasks which are presented sequentially to the learner. A key challenge in this setting is that the learner may forget how to solve a previous task when learning a new task, a phenomenon known as catastrophic forgetting. To address this chal...
2101.09536
James Smith
James Smith, Jonathan Balloch, Yen-Chang Hsu, Zsolt Kira
Memory-Efficient Semi-Supervised Continual Learning: The World is its Own Replay Buffer
Accepted by the 2021 International Joint Conference on Neural Networks (IJCNN 2021)
null
null
null
cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Rehearsal is a critical component for class-incremental continual learning, yet it requires a substantial memory budget. Our work investigates whether we can significantly reduce this memory budget by leveraging unlabeled data from an agent's environment in a realistic and challenging continual learning paradigm. Spe...
[ { "created": "Sat, 23 Jan 2021 17:23:08 GMT", "version": "v1" }, { "created": "Thu, 6 May 2021 17:55:20 GMT", "version": "v2" } ]
2021-05-07
[ [ "Smith", "James", "" ], [ "Balloch", "Jonathan", "" ], [ "Hsu", "Yen-Chang", "" ], [ "Kira", "Zsolt", "" ] ]
Rehearsal is a critical component for class-incremental continual learning, yet it requires a substantial memory budget. Our work investigates whether we can significantly reduce this memory budget by leveraging unlabeled data from an agent's environment in a realistic and challenging continual learning paradigm. Speci...
2206.01934
Phan Hoang
Hoang Phan, Ngoc Tran, Trung Le, Toan Tran, Nhat Ho, Dinh Phung
Stochastic Multiple Target Sampling Gradient Descent
Accepted to Advances in Neural Information Processing Systems (NeurIPS) 2022. 27 pages, 10 figures, 5 tables
null
null
null
cs.LG cs.AI stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Sampling from an unnormalized target distribution is an essential problem with many applications in probabilistic inference. Stein Variational Gradient Descent (SVGD) has been shown to be a powerful method that iteratively updates a set of particles to approximate the distribution of interest. Furthermore, when analy...
[ { "created": "Sat, 4 Jun 2022 07:54:35 GMT", "version": "v1" }, { "created": "Sun, 12 Jun 2022 17:19:29 GMT", "version": "v2" }, { "created": "Fri, 23 Sep 2022 03:00:25 GMT", "version": "v3" }, { "created": "Fri, 10 Feb 2023 16:43:01 GMT", "version": "v4" } ]
2023-02-13
[ [ "Phan", "Hoang", "" ], [ "Tran", "Ngoc", "" ], [ "Le", "Trung", "" ], [ "Tran", "Toan", "" ], [ "Ho", "Nhat", "" ], [ "Phung", "Dinh", "" ] ]
Sampling from an unnormalized target distribution is an essential problem with many applications in probabilistic inference. Stein Variational Gradient Descent (SVGD) has been shown to be a powerful method that iteratively updates a set of particles to approximate the distribution of interest. Furthermore, when analysi...
1703.10187
Mohamed El Massad
Mohamed El Massad, Jun Zhang, Siddharth Garg and Mahesh V. Tripunitara
Logic Locking for Secure Outsourced Chip Fabrication: A New Attack and Provably Secure Defense Mechanism
null
null
null
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Chip designers outsource chip fabrication to external foundries, but at the risk of IP theft. Logic locking, a promising solution to mitigate this threat, adds extra logic gates (key gates) and inputs (key bits) to the chip so that it functions correctly only when the correct key, known only to the designer but not t...
[ { "created": "Wed, 29 Mar 2017 18:17:55 GMT", "version": "v1" } ]
2017-03-31
[ [ "Massad", "Mohamed El", "" ], [ "Zhang", "Jun", "" ], [ "Garg", "Siddharth", "" ], [ "Tripunitara", "Mahesh V.", "" ] ]
Chip designers outsource chip fabrication to external foundries, but at the risk of IP theft. Logic locking, a promising solution to mitigate this threat, adds extra logic gates (key gates) and inputs (key bits) to the chip so that it functions correctly only when the correct key, known only to the designer but not the...
1301.1394
Michael Fink
Vladimir Lifschitz and Fangkai Yang
Lloyd-Topor Completion and General Stable Models
Proceedings of Answer Set Programming and Other Computing Paradigms (ASPOCP 2012), 5th International Workshop, September 4, 2012, Budapest, Hungary
null
null
null
cs.LO cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We investigate the relationship between the generalization of program completion defined in 1984 by Lloyd and Topor and the generalization of the stable model semantics introduced recently by Ferraris et al. The main theorem can be used to characterize, in some cases, the general stable models of a logic program by a...
[ { "created": "Tue, 8 Jan 2013 02:29:55 GMT", "version": "v1" } ]
2013-01-09
[ [ "Lifschitz", "Vladimir", "" ], [ "Yang", "Fangkai", "" ] ]
We investigate the relationship between the generalization of program completion defined in 1984 by Lloyd and Topor and the generalization of the stable model semantics introduced recently by Ferraris et al. The main theorem can be used to characterize, in some cases, the general stable models of a logic program by a f...
2311.01115
Lara Ost
Sebastiano Cultrera di Montesano, Herbert Edelsbrunner, Monika Henzinger, Lara Ost
Dynamically Maintaining the Persistent Homology of Time Series
Corrected the statement and proof of Theorem 5.2; added a missing edge-case to the anti-cancellation algorithm
null
null
null
cs.DS cs.CG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present a dynamic data structure for maintaining the persistent homology of a time series of real numbers. The data structure supports local operations, including the insertion and deletion of an item and the cutting and concatenating of lists, each in time $O(\log n + k)$, in which $n$ counts the critical items a...
[ { "created": "Thu, 2 Nov 2023 09:41:49 GMT", "version": "v1" }, { "created": "Tue, 2 Jul 2024 12:26:47 GMT", "version": "v2" } ]
2024-07-03
[ [ "di Montesano", "Sebastiano Cultrera", "" ], [ "Edelsbrunner", "Herbert", "" ], [ "Henzinger", "Monika", "" ], [ "Ost", "Lara", "" ] ]
We present a dynamic data structure for maintaining the persistent homology of a time series of real numbers. The data structure supports local operations, including the insertion and deletion of an item and the cutting and concatenating of lists, each in time $O(\log n + k)$, in which $n$ counts the critical items and...
2401.12596
Hengjia Li
Hengjia Li, Yang Liu, Yuqi Lin, Zhanwei Zhang, Yibo Zhao, weihang Pan, Tu Zheng, Zheng Yang, Yuchun Jiang, Boxi Wu, Deng Cai
UniHDA: A Unified and Versatile Framework for Multi-Modal Hybrid Domain Adaptation
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recently, generative domain adaptation has achieved remarkable progress, enabling us to adapt a pre-trained generator to a new target domain. However, existing methods simply adapt the generator to a single target domain and are limited to a single modality, either text-driven or image-driven. Moreover, they cannot m...
[ { "created": "Tue, 23 Jan 2024 09:49:24 GMT", "version": "v1" }, { "created": "Fri, 15 Mar 2024 07:44:00 GMT", "version": "v2" } ]
2024-03-18
[ [ "Li", "Hengjia", "" ], [ "Liu", "Yang", "" ], [ "Lin", "Yuqi", "" ], [ "Zhang", "Zhanwei", "" ], [ "Zhao", "Yibo", "" ], [ "Pan", "weihang", "" ], [ "Zheng", "Tu", "" ], [ "Yang", "Zheng", "...
Recently, generative domain adaptation has achieved remarkable progress, enabling us to adapt a pre-trained generator to a new target domain. However, existing methods simply adapt the generator to a single target domain and are limited to a single modality, either text-driven or image-driven. Moreover, they cannot mai...
1702.03389
Bing Zeng
Bing Zeng, Liang Gao, Xinyu Li
Whale swarm algorithm for function optimization
8 pages, 5 figures
LNCS. volume 10361. ICIC 2017: pp 624-639
10.1007/978-3-319-63309-1_55
null
cs.NE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Increasing nature-inspired metaheuristic algorithms are applied to solving the real-world optimization problems, as they have some advantages over the classical methods of numerical optimization. This paper has proposed a new nature-inspired metaheuristic called Whale Swarm Algorithm for function optimization, which ...
[ { "created": "Sat, 11 Feb 2017 06:39:38 GMT", "version": "v1" }, { "created": "Thu, 30 Mar 2017 12:53:54 GMT", "version": "v2" } ]
2017-08-10
[ [ "Zeng", "Bing", "" ], [ "Gao", "Liang", "" ], [ "Li", "Xinyu", "" ] ]
Increasing nature-inspired metaheuristic algorithms are applied to solving the real-world optimization problems, as they have some advantages over the classical methods of numerical optimization. This paper has proposed a new nature-inspired metaheuristic called Whale Swarm Algorithm for function optimization, which is...
1705.00744
Ragav Venkatesan
Ragav Venkatesan, Hemanth Venkateswara, Sethuraman Panchanathan, Baoxin Li
A Strategy for an Uncompromising Incremental Learner
Under review at IEEE Transactions of Neural Networks and Learning Systems
null
null
null
cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Multi-class supervised learning systems require the knowledge of the entire range of labels they predict. Often when learnt incrementally, they suffer from catastrophic forgetting. To avoid this, generous leeways have to be made to the philosophy of incremental learning that either forces a part of the machine to not...
[ { "created": "Tue, 2 May 2017 00:17:54 GMT", "version": "v1" }, { "created": "Mon, 17 Jul 2017 07:30:18 GMT", "version": "v2" } ]
2017-07-18
[ [ "Venkatesan", "Ragav", "" ], [ "Venkateswara", "Hemanth", "" ], [ "Panchanathan", "Sethuraman", "" ], [ "Li", "Baoxin", "" ] ]
Multi-class supervised learning systems require the knowledge of the entire range of labels they predict. Often when learnt incrementally, they suffer from catastrophic forgetting. To avoid this, generous leeways have to be made to the philosophy of incremental learning that either forces a part of the machine to not l...
2003.09554
Evangelia Gergatsouli
Evangelia Gergatsouli, Brendan Lucier, Christos Tzamos
Black-box Methods for Restoring Monotonicity
null
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In many practical applications, heuristic or approximation algorithms are used to efficiently solve the task at hand. However their solutions frequently do not satisfy natural monotonicity properties of optimal solutions. In this work we develop algorithms that are able to restore monotonicity in the parameters of in...
[ { "created": "Sat, 21 Mar 2020 02:19:56 GMT", "version": "v1" } ]
2020-03-24
[ [ "Gergatsouli", "Evangelia", "" ], [ "Lucier", "Brendan", "" ], [ "Tzamos", "Christos", "" ] ]
In many practical applications, heuristic or approximation algorithms are used to efficiently solve the task at hand. However their solutions frequently do not satisfy natural monotonicity properties of optimal solutions. In this work we develop algorithms that are able to restore monotonicity in the parameters of inte...
2112.13927
Yayun Du
Yayun Du, Andrew Miller, M. Khalid Jawed
Mechanics-based Analysis on Flagellated Robots
16 pages, 7 figures
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We explore the locomotion of soft robots in granular medium (GM) resulting from the elastic deformation of slender rods. A low-cost, rapidly fabricable robot inspired by the physiological structure of bacteria is presented. It consists of a rigid head, with a motor and batteries embedded, and multiple elastic rods (o...
[ { "created": "Mon, 27 Dec 2021 22:40:51 GMT", "version": "v1" } ]
2021-12-30
[ [ "Du", "Yayun", "" ], [ "Miller", "Andrew", "" ], [ "Jawed", "M. Khalid", "" ] ]
We explore the locomotion of soft robots in granular medium (GM) resulting from the elastic deformation of slender rods. A low-cost, rapidly fabricable robot inspired by the physiological structure of bacteria is presented. It consists of a rigid head, with a motor and batteries embedded, and multiple elastic rods (our...
2012.11150
Sungwon Han
Sungwon Park, Sungwon Han, Sundong Kim, Danu Kim, Sungkyu Park, Seunghoon Hong and Meeyoung Cha
Improving Unsupervised Image Clustering With Robust Learning
Accepted at CVPR2021
null
null
null
cs.CV cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Unsupervised image clustering methods often introduce alternative objectives to indirectly train the model and are subject to faulty predictions and overconfident results. To overcome these challenges, the current research proposes an innovative model RUC that is inspired by robust learning. RUC's novelty is at utili...
[ { "created": "Mon, 21 Dec 2020 07:02:11 GMT", "version": "v1" }, { "created": "Mon, 29 Mar 2021 15:36:14 GMT", "version": "v2" } ]
2021-03-30
[ [ "Park", "Sungwon", "" ], [ "Han", "Sungwon", "" ], [ "Kim", "Sundong", "" ], [ "Kim", "Danu", "" ], [ "Park", "Sungkyu", "" ], [ "Hong", "Seunghoon", "" ], [ "Cha", "Meeyoung", "" ] ]
Unsupervised image clustering methods often introduce alternative objectives to indirectly train the model and are subject to faulty predictions and overconfident results. To overcome these challenges, the current research proposes an innovative model RUC that is inspired by robust learning. RUC's novelty is at utilizi...
2110.11525
Jeremy Speth
Jeremy Speth, Nathan Vance, Patrick Flynn, Kevin W. Bowyer, Adam Czajka
Digital and Physical-World Attacks on Remote Pulse Detection
null
null
null
null
cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Remote photoplethysmography (rPPG) is a technique for estimating blood volume changes from reflected light without the need for a contact sensor. We present the first examples of presentation attacks in the digital and physical domains on rPPG from face video. Digital attacks are easily performed by adding impercepti...
[ { "created": "Thu, 21 Oct 2021 23:41:27 GMT", "version": "v1" } ]
2021-10-25
[ [ "Speth", "Jeremy", "" ], [ "Vance", "Nathan", "" ], [ "Flynn", "Patrick", "" ], [ "Bowyer", "Kevin W.", "" ], [ "Czajka", "Adam", "" ] ]
Remote photoplethysmography (rPPG) is a technique for estimating blood volume changes from reflected light without the need for a contact sensor. We present the first examples of presentation attacks in the digital and physical domains on rPPG from face video. Digital attacks are easily performed by adding imperceptibl...
2207.10257
Jeong-Gi Kwak
Jeong-gi Kwak, Yuanming Li, Dongsik Yoon, Donghyeon Kim, David Han, Hanseok Ko
Injecting 3D Perception of Controllable NeRF-GAN into StyleGAN for Editable Portrait Image Synthesis
ECCV 2022, project page: https://jgkwak95.github.io/surfgan/
null
null
null
cs.CV cs.GR
http://creativecommons.org/licenses/by/4.0/
Over the years, 2D GANs have achieved great successes in photorealistic portrait generation. However, they lack 3D understanding in the generation process, thus they suffer from multi-view inconsistency problem. To alleviate the issue, many 3D-aware GANs have been proposed and shown notable results, but 3D GANs strug...
[ { "created": "Thu, 21 Jul 2022 01:41:54 GMT", "version": "v1" }, { "created": "Tue, 26 Jul 2022 07:27:35 GMT", "version": "v2" } ]
2022-07-27
[ [ "Kwak", "Jeong-gi", "" ], [ "Li", "Yuanming", "" ], [ "Yoon", "Dongsik", "" ], [ "Kim", "Donghyeon", "" ], [ "Han", "David", "" ], [ "Ko", "Hanseok", "" ] ]
Over the years, 2D GANs have achieved great successes in photorealistic portrait generation. However, they lack 3D understanding in the generation process, thus they suffer from multi-view inconsistency problem. To alleviate the issue, many 3D-aware GANs have been proposed and shown notable results, but 3D GANs struggl...
1712.07206
Edoardo Di Napoli
Davor Davidovi\'c, Diego Fabregat-Traver, Markus H\"ohnerbach, and Edoardo di Napoli
Accelerating the computation of FLAPW methods on heterogeneous architectures
22 pages, submitted to special issue of CCPE
null
10.1002/cpe.4905
null
cs.DC cs.CE cs.MS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Legacy codes in computational science and engineering have been very successful in providing essential functionality to researchers. However, they are not capable of exploiting the massive parallelism provided by emerging heterogeneous architectures. The lack of portable performance and scalability puts them at high ...
[ { "created": "Tue, 19 Dec 2017 20:58:08 GMT", "version": "v1" } ]
2022-03-18
[ [ "Davidović", "Davor", "" ], [ "Fabregat-Traver", "Diego", "" ], [ "Höhnerbach", "Markus", "" ], [ "di Napoli", "Edoardo", "" ] ]
Legacy codes in computational science and engineering have been very successful in providing essential functionality to researchers. However, they are not capable of exploiting the massive parallelism provided by emerging heterogeneous architectures. The lack of portable performance and scalability puts them at high ri...
2207.14124
Peter Xenopoulos
Peter Xenopoulos, Claudio Silva
Graph Neural Networks to Predict Sports Outcomes
Accepted as a short paper (6 pages) to 2021 IEEE International Conference on Big Data
null
10.1109/BigData52589.2021.9671833
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Predicting outcomes in sports is important for teams, leagues, bettors, media, and fans. Given the growing amount of player tracking data, sports analytics models are increasingly utilizing spatially-derived features built upon player tracking data. However, player-specific information, such as location, cannot readi...
[ { "created": "Thu, 28 Jul 2022 14:45:02 GMT", "version": "v1" } ]
2022-07-29
[ [ "Xenopoulos", "Peter", "" ], [ "Silva", "Claudio", "" ] ]
Predicting outcomes in sports is important for teams, leagues, bettors, media, and fans. Given the growing amount of player tracking data, sports analytics models are increasingly utilizing spatially-derived features built upon player tracking data. However, player-specific information, such as location, cannot readily...
1612.07928
Martianus Frederic Ezerman
Zuling Chang, Martianus Frederic Ezerman, San Ling and Huaxiong Wang
The Cycle Structure of LFSR with Arbitrary Characteristic Polynomial over Finite Fields
An extended abstract containing preliminary results was presented at SETA 2016
Cryptogr. Commun. vol 10 no. 6 pp. 1183-1202, 2018
10.1007/s12095-017-0273-2
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We determine the cycle structure of linear feedback shift register with arbitrary monic characteristic polynomial over any finite field. For each cycle, a method to find a state and a new way to represent the state are proposed.
[ { "created": "Fri, 23 Dec 2016 10:43:52 GMT", "version": "v1" } ]
2019-06-13
[ [ "Chang", "Zuling", "" ], [ "Ezerman", "Martianus Frederic", "" ], [ "Ling", "San", "" ], [ "Wang", "Huaxiong", "" ] ]
We determine the cycle structure of linear feedback shift register with arbitrary monic characteristic polynomial over any finite field. For each cycle, a method to find a state and a new way to represent the state are proposed.
2204.02973
Yanyong Huang
Yanyong Huang, Kejun Guo, Xiuwen Yi, Zhong Li, Tianrui Li
Incremental Unsupervised Feature Selection for Dynamic Incomplete Multi-view Data
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Multi-view unsupervised feature selection has been proven to be efficient in reducing the dimensionality of multi-view unlabeled data with high dimensions. The previous methods assume all of the views are complete. However, in real applications, the multi-view data are often incomplete, i.e., some views of instances ...
[ { "created": "Tue, 5 Apr 2022 16:29:39 GMT", "version": "v1" }, { "created": "Fri, 30 Dec 2022 09:59:37 GMT", "version": "v2" } ]
2023-01-02
[ [ "Huang", "Yanyong", "" ], [ "Guo", "Kejun", "" ], [ "Yi", "Xiuwen", "" ], [ "Li", "Zhong", "" ], [ "Li", "Tianrui", "" ] ]
Multi-view unsupervised feature selection has been proven to be efficient in reducing the dimensionality of multi-view unlabeled data with high dimensions. The previous methods assume all of the views are complete. However, in real applications, the multi-view data are often incomplete, i.e., some views of instances ar...
1204.3799
David Laniado
Pablo Arag\'on, Andreas Kaltenbrunner, David Laniado and Yana Volkovich
Biographical Social Networks on Wikipedia - A cross-cultural study of links that made history
4 pages, 3 figures
Proceedings of WikiSym, 2012
null
null
cs.SI cs.CY physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
It is arguable whether history is made by great men and women or vice versa, but undoubtably social connections shape history. Analysing Wikipedia, a global collective memory place, we aim to understand how social links are recorded across cultures. Starting with the set of biographies in the English Wikipedia we foc...
[ { "created": "Tue, 17 Apr 2012 14:14:08 GMT", "version": "v1" }, { "created": "Wed, 4 Jul 2012 14:11:12 GMT", "version": "v2" } ]
2012-07-05
[ [ "Aragón", "Pablo", "" ], [ "Kaltenbrunner", "Andreas", "" ], [ "Laniado", "David", "" ], [ "Volkovich", "Yana", "" ] ]
It is arguable whether history is made by great men and women or vice versa, but undoubtably social connections shape history. Analysing Wikipedia, a global collective memory place, we aim to understand how social links are recorded across cultures. Starting with the set of biographies in the English Wikipedia we focus...
2104.10247
Ian Porada
Ian Porada, Kaheer Suleman, Adam Trischler, and Jackie Chi Kit Cheung
Modeling Event Plausibility with Consistent Conceptual Abstraction
NAACL-HLT 2021
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
Understanding natural language requires common sense, one aspect of which is the ability to discern the plausibility of events. While distributional models -- most recently pre-trained, Transformer language models -- have demonstrated improvements in modeling event plausibility, their performance still falls short of...
[ { "created": "Tue, 20 Apr 2021 21:08:32 GMT", "version": "v1" } ]
2021-04-22
[ [ "Porada", "Ian", "" ], [ "Suleman", "Kaheer", "" ], [ "Trischler", "Adam", "" ], [ "Cheung", "Jackie Chi Kit", "" ] ]
Understanding natural language requires common sense, one aspect of which is the ability to discern the plausibility of events. While distributional models -- most recently pre-trained, Transformer language models -- have demonstrated improvements in modeling event plausibility, their performance still falls short of h...
1904.09936
Meera Hahn
Meera Hahn, Asim Kadav, James M. Rehg and Hans Peter Graf
Tripping through time: Efficient Localization of Activities in Videos
Presented at BMVC, 2020
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Localizing moments in untrimmed videos via language queries is a new and interesting task that requires the ability to accurately ground language into video. Previous works have approached this task by processing the entire video, often more than once, to localize relevant activities. In the real world applications o...
[ { "created": "Mon, 22 Apr 2019 15:53:13 GMT", "version": "v1" }, { "created": "Tue, 23 Apr 2019 18:41:21 GMT", "version": "v2" }, { "created": "Thu, 25 Apr 2019 17:06:49 GMT", "version": "v3" }, { "created": "Thu, 12 Sep 2019 17:49:05 GMT", "version": "v4" }, { "c...
2020-08-19
[ [ "Hahn", "Meera", "" ], [ "Kadav", "Asim", "" ], [ "Rehg", "James M.", "" ], [ "Graf", "Hans Peter", "" ] ]
Localizing moments in untrimmed videos via language queries is a new and interesting task that requires the ability to accurately ground language into video. Previous works have approached this task by processing the entire video, often more than once, to localize relevant activities. In the real world applications of ...
2102.04361
Daniel Stan
Daniel Stan and Anthony Widjaja Lin
Regular Model Checking Approach to Knowledge Reasoning over Parameterized Systems (technical report)
Extended version, version of record accepted at the 20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS-21)
null
null
null
cs.FL cs.LO cs.MA
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present a general framework for modelling and verifying epistemic properties over parameterized multi-agent systems that communicate by truthful public announcements. In our framework, the number of agents or the amount of certain resources are parameterized (i.e. not known a priori), and the corresponding verific...
[ { "created": "Mon, 8 Feb 2021 17:10:24 GMT", "version": "v1" }, { "created": "Wed, 17 Feb 2021 21:50:29 GMT", "version": "v2" }, { "created": "Mon, 8 Mar 2021 19:20:12 GMT", "version": "v3" } ]
2021-03-10
[ [ "Stan", "Daniel", "" ], [ "Lin", "Anthony Widjaja", "" ] ]
We present a general framework for modelling and verifying epistemic properties over parameterized multi-agent systems that communicate by truthful public announcements. In our framework, the number of agents or the amount of certain resources are parameterized (i.e. not known a priori), and the corresponding verificat...
2306.06264
Pouya Pezeshkpour
Pouya Pezeshkpour
Measuring and Modifying Factual Knowledge in Large Language Models
null
null
null
null
cs.CL cs.LG
http://creativecommons.org/licenses/by/4.0/
Large Language Models (LLMs) store an extensive amount of factual knowledge obtained from vast collections of text. To effectively utilize these models for downstream tasks, it is crucial to have reliable methods for measuring their knowledge. However, existing approaches for knowledge measurement have certain limita...
[ { "created": "Fri, 9 Jun 2023 21:25:48 GMT", "version": "v1" } ]
2023-06-13
[ [ "Pezeshkpour", "Pouya", "" ] ]
Large Language Models (LLMs) store an extensive amount of factual knowledge obtained from vast collections of text. To effectively utilize these models for downstream tasks, it is crucial to have reliable methods for measuring their knowledge. However, existing approaches for knowledge measurement have certain limitati...
2304.00862
Pablo Dorta-Gonzalez
Pablo Dorta-Gonz\'alez and Mar\'ia Isabel Dorta-Gonz\'alez
The funding effect on citation and social attention: the UN Sustainable Development Goals (SDGs) as a case study
This article has been approved for publication in Online Information Review on March 13th, 2023 (25 pages, 4 figures, 5 tables)
null
10.1108/OIR-05-2022-0300
null
cs.DL stat.AP
http://creativecommons.org/licenses/by/4.0/
Purpose: Academic citation and social attention measure different dimensions in the impact of research results. We quantify the contribution of funding to both indicators considering the differences attributable to the research field and access type. Design/methodology/approach: Citation and social attention accumula...
[ { "created": "Mon, 3 Apr 2023 10:22:29 GMT", "version": "v1" } ]
2023-04-04
[ [ "Dorta-González", "Pablo", "" ], [ "Dorta-González", "María Isabel", "" ] ]
Purpose: Academic citation and social attention measure different dimensions in the impact of research results. We quantify the contribution of funding to both indicators considering the differences attributable to the research field and access type. Design/methodology/approach: Citation and social attention accumulate...
2106.14016
Li Liu
Jianrong Wang, Nan Gu, Mei Yu, Xuewei Li, Qiang Fang, Li Liu
An Attention Self-supervised Contrastive Learning based Three-stage Model for Hand Shape Feature Representation in Cued Speech
null
null
null
null
cs.MM
http://creativecommons.org/publicdomain/zero/1.0/
Cued Speech (CS) is a communication system for deaf people or hearing impaired people, in which a speaker uses it to aid a lipreader in phonetic level by clarifying potentially ambiguous mouth movements with hand shape and positions. Feature extraction of multi-modal CS is a key step in CS recognition. Recent supervi...
[ { "created": "Sat, 26 Jun 2021 13:20:33 GMT", "version": "v1" } ]
2021-06-29
[ [ "Wang", "Jianrong", "" ], [ "Gu", "Nan", "" ], [ "Yu", "Mei", "" ], [ "Li", "Xuewei", "" ], [ "Fang", "Qiang", "" ], [ "Liu", "Li", "" ] ]
Cued Speech (CS) is a communication system for deaf people or hearing impaired people, in which a speaker uses it to aid a lipreader in phonetic level by clarifying potentially ambiguous mouth movements with hand shape and positions. Feature extraction of multi-modal CS is a key step in CS recognition. Recent supervise...
2408.08133
Victor Verreet
Victor Verreet, Lennert De Smet, Luc De Raedt, Emanuele Sansone
EXPLAIN, AGREE, LEARN: Scaling Learning for Neural Probabilistic Logic
null
null
null
null
cs.LG cs.AI
http://creativecommons.org/licenses/by/4.0/
Neural probabilistic logic systems follow the neuro-symbolic (NeSy) paradigm by combining the perceptive and learning capabilities of neural networks with the robustness of probabilistic logic. Learning corresponds to likelihood optimization of the neural networks. However, to obtain the likelihood exactly, expensive...
[ { "created": "Thu, 15 Aug 2024 13:07:51 GMT", "version": "v1" } ]
2024-08-16
[ [ "Verreet", "Victor", "" ], [ "De Smet", "Lennert", "" ], [ "De Raedt", "Luc", "" ], [ "Sansone", "Emanuele", "" ] ]
Neural probabilistic logic systems follow the neuro-symbolic (NeSy) paradigm by combining the perceptive and learning capabilities of neural networks with the robustness of probabilistic logic. Learning corresponds to likelihood optimization of the neural networks. However, to obtain the likelihood exactly, expensive p...
2305.13401
Haotian Ye
Haotian Ye, Yihong Liu, Hinrich Sch\"utze
A study of conceptual language similarity: comparison and evaluation
null
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
An interesting line of research in natural language processing (NLP) aims to incorporate linguistic typology to bridge linguistic diversity and assist the research of low-resource languages. While most works construct linguistic similarity measures based on lexical or typological features, such as word order and verb...
[ { "created": "Mon, 22 May 2023 18:28:02 GMT", "version": "v1" } ]
2023-05-24
[ [ "Ye", "Haotian", "" ], [ "Liu", "Yihong", "" ], [ "Schütze", "Hinrich", "" ] ]
An interesting line of research in natural language processing (NLP) aims to incorporate linguistic typology to bridge linguistic diversity and assist the research of low-resource languages. While most works construct linguistic similarity measures based on lexical or typological features, such as word order and verbal...
1812.03237
Md Mehedi Hassan Onik
Md Mehedi Hassan Onik, Mahdi H. Miraz, Chul-Soo Kim
A Recruitment and Human Resource Management Technique Using Blockchain Technology for Industry 4.0
Onik, M. M. H., Miraz, M. H., & Kim, C. S. (2018, April). A recruitment and human resource management technique using Blockchain technology for Industry 4.0. In Proceedings of the Smart Cities Symposium (SCS-2018), Manama, Bahrain (pp. 11-16). IET
null
10.1049/cp.2018.1371
null
cs.CR cs.CY cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Application of Information Technology (IT) in the domain of Human Resource Management (HRM) systems is a sine qua non for any organization for successfully adopting and implementing Fourth Industrial Revolution (Industry 4.0). However, these systems are required to ensure non-biased, efficient, transparent and secure...
[ { "created": "Fri, 7 Dec 2018 23:09:06 GMT", "version": "v1" } ]
2019-02-13
[ [ "Onik", "Md Mehedi Hassan", "" ], [ "Miraz", "Mahdi H.", "" ], [ "Kim", "Chul-Soo", "" ] ]
Application of Information Technology (IT) in the domain of Human Resource Management (HRM) systems is a sine qua non for any organization for successfully adopting and implementing Fourth Industrial Revolution (Industry 4.0). However, these systems are required to ensure non-biased, efficient, transparent and secure e...
2305.09696
Tianping Zhang
Tianping Zhang, Shaowen Wang, Shuicheng Yan, Jian Li, Qian Liu
Generative Table Pre-training Empowers Models for Tabular Prediction
null
null
null
null
cs.LG cs.AI cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recently, the topic of table pre-training has attracted considerable research interest. However, how to employ table pre-training to boost the performance of tabular prediction remains an open challenge. In this paper, we propose TapTap, the first attempt that leverages table pre-training to empower models for tabula...
[ { "created": "Tue, 16 May 2023 06:37:38 GMT", "version": "v1" } ]
2023-05-18
[ [ "Zhang", "Tianping", "" ], [ "Wang", "Shaowen", "" ], [ "Yan", "Shuicheng", "" ], [ "Li", "Jian", "" ], [ "Liu", "Qian", "" ] ]
Recently, the topic of table pre-training has attracted considerable research interest. However, how to employ table pre-training to boost the performance of tabular prediction remains an open challenge. In this paper, we propose TapTap, the first attempt that leverages table pre-training to empower models for tabular ...
2011.05602
Zheng Zhu
Jintao Ke, Siyuan Feng, Zheng Zhu, Hai Yang, Jieping Ye
Joint predictions of multi-modal ride-hailing demands: a deep multi-task multigraph learning-based approach
null
null
10.1016/j.trc.2021.103063
null
cs.LG cs.AI
http://creativecommons.org/licenses/by/4.0/
Ride-hailing platforms generally provide various service options to customers, such as solo ride services, shared ride services, etc. It is generally expected that demands for different service modes are correlated, and the prediction of demand for one service mode can benefit from historical observations of demands ...
[ { "created": "Wed, 11 Nov 2020 07:10:50 GMT", "version": "v1" } ]
2022-04-27
[ [ "Ke", "Jintao", "" ], [ "Feng", "Siyuan", "" ], [ "Zhu", "Zheng", "" ], [ "Yang", "Hai", "" ], [ "Ye", "Jieping", "" ] ]
Ride-hailing platforms generally provide various service options to customers, such as solo ride services, shared ride services, etc. It is generally expected that demands for different service modes are correlated, and the prediction of demand for one service mode can benefit from historical observations of demands fo...
2104.13369
Michal Yarom
Oran Lang, Yossi Gandelsman, Michal Yarom, Yoav Wald, Gal Elidan, Avinatan Hassidim, William T. Freeman, Phillip Isola, Amir Globerson, Michal Irani, Inbar Mosseri
Explaining in Style: Training a GAN to explain a classifier in StyleSpace
Accepted to ICCV 2021. Project page: https://explaining-in-style.github.io/, Code: https://github.com/google/explaining-in-style
null
null
null
cs.CV cs.LG cs.NE eess.IV stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Image classification models can depend on multiple different semantic attributes of the image. An explanation of the decision of the classifier needs to both discover and visualize these properties. Here we present StylEx, a method for doing this, by training a generative model to specifically explain multiple attrib...
[ { "created": "Tue, 27 Apr 2021 17:57:19 GMT", "version": "v1" }, { "created": "Wed, 1 Sep 2021 08:04:54 GMT", "version": "v2" } ]
2021-09-02
[ [ "Lang", "Oran", "" ], [ "Gandelsman", "Yossi", "" ], [ "Yarom", "Michal", "" ], [ "Wald", "Yoav", "" ], [ "Elidan", "Gal", "" ], [ "Hassidim", "Avinatan", "" ], [ "Freeman", "William T.", "" ], [ "I...
Image classification models can depend on multiple different semantic attributes of the image. An explanation of the decision of the classifier needs to both discover and visualize these properties. Here we present StylEx, a method for doing this, by training a generative model to specifically explain multiple attribut...
2003.02495
Mustafa Emara
Mustafa Emara, Miltiades C. Filippou, Dario Sabella
MEC-enhanced Information Freshness for Safety-critical C-V2X Communications
Accepted at ICC 2020, CLEEN workshop
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Information freshness is a status update timeliness indicator of utmost importance to several real-time applications, such as connected and autonomous driving. The Ageof- Information (AoI) metric is widely considered as useful to quantify the information freshness of delivered messages to the involved entities. Recen...
[ { "created": "Thu, 5 Mar 2020 09:20:10 GMT", "version": "v1" } ]
2020-03-06
[ [ "Emara", "Mustafa", "" ], [ "Filippou", "Miltiades C.", "" ], [ "Sabella", "Dario", "" ] ]
Information freshness is a status update timeliness indicator of utmost importance to several real-time applications, such as connected and autonomous driving. The Ageof- Information (AoI) metric is widely considered as useful to quantify the information freshness of delivered messages to the involved entities. Recentl...
2306.01470
Ryo Karakida
Tomohiro Hayase, Ryo Karakida
Understanding MLP-Mixer as a Wide and Sparse MLP
Accepted in ICML 2024
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Multi-layer perceptron (MLP) is a fundamental component of deep learning, and recent MLP-based architectures, especially the MLP-Mixer, have achieved significant empirical success. Nevertheless, our understanding of why and how the MLP-Mixer outperforms conventional MLPs remains largely unexplored. In this work, we r...
[ { "created": "Fri, 2 Jun 2023 11:51:24 GMT", "version": "v1" }, { "created": "Mon, 6 May 2024 20:03:17 GMT", "version": "v2" } ]
2024-05-08
[ [ "Hayase", "Tomohiro", "" ], [ "Karakida", "Ryo", "" ] ]
Multi-layer perceptron (MLP) is a fundamental component of deep learning, and recent MLP-based architectures, especially the MLP-Mixer, have achieved significant empirical success. Nevertheless, our understanding of why and how the MLP-Mixer outperforms conventional MLPs remains largely unexplored. In this work, we rev...
2211.15557
Andy Applebaum
Melody Wolk, Andy Applebaum, Camron Dennler, Patrick Dwyer, Marina Moskowitz, Harold Nguyen, Nicole Nichols, Nicole Park, Paul Rachwalski, Frank Rau, Adrian Webster
Beyond CAGE: Investigating Generalization of Learned Autonomous Network Defense Policies
NeurIPS 2022 Workshop: Reinforcement Learning for Real Life
null
null
null
cs.LG cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Advancements in reinforcement learning (RL) have inspired new directions in intelligent automation of network defense. However, many of these advancements have either outpaced their application to network security or have not considered the challenges associated with implementing them in the real-world. To understand...
[ { "created": "Mon, 28 Nov 2022 17:01:24 GMT", "version": "v1" }, { "created": "Wed, 30 Nov 2022 14:35:42 GMT", "version": "v2" } ]
2022-12-01
[ [ "Wolk", "Melody", "" ], [ "Applebaum", "Andy", "" ], [ "Dennler", "Camron", "" ], [ "Dwyer", "Patrick", "" ], [ "Moskowitz", "Marina", "" ], [ "Nguyen", "Harold", "" ], [ "Nichols", "Nicole", "" ], [ ...
Advancements in reinforcement learning (RL) have inspired new directions in intelligent automation of network defense. However, many of these advancements have either outpaced their application to network security or have not considered the challenges associated with implementing them in the real-world. To understand t...
2103.00383
Gautam Krishna
Gautam Krishna, Mason Carnahan, Shilpa Shamapant, Yashitha Surendranath, Saumya Jain, Arundhati Ghosh, Co Tran, Jose del R Millan and Ahmed H Tewfik
Brain Signals to Rescue Aphasia, Apraxia and Dysarthria Speech Recognition
Accepted to IEEE EMBC 2021
null
null
null
cs.SD cs.LG eess.AS q-bio.QM
http://creativecommons.org/licenses/by/4.0/
In this paper, we propose a deep learning-based algorithm to improve the performance of automatic speech recognition (ASR) systems for aphasia, apraxia, and dysarthria speech by utilizing electroencephalography (EEG) features recorded synchronously with aphasia, apraxia, and dysarthria speech. We demonstrate a signif...
[ { "created": "Sun, 28 Feb 2021 03:27:02 GMT", "version": "v1" }, { "created": "Sun, 18 Jul 2021 00:02:25 GMT", "version": "v2" } ]
2021-07-20
[ [ "Krishna", "Gautam", "" ], [ "Carnahan", "Mason", "" ], [ "Shamapant", "Shilpa", "" ], [ "Surendranath", "Yashitha", "" ], [ "Jain", "Saumya", "" ], [ "Ghosh", "Arundhati", "" ], [ "Tran", "Co", "" ], [...
In this paper, we propose a deep learning-based algorithm to improve the performance of automatic speech recognition (ASR) systems for aphasia, apraxia, and dysarthria speech by utilizing electroencephalography (EEG) features recorded synchronously with aphasia, apraxia, and dysarthria speech. We demonstrate a signific...
2008.13710
Eden Belouadah
Eden Belouadah, Adrian Popescu, Ioannis Kanellos
Initial Classifier Weights Replay for Memoryless Class Incremental Learning
Accepted in BMVC2020
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Incremental Learning (IL) is useful when artificial systems need to deal with streams of data and do not have access to all data at all times. The most challenging setting requires a constant complexity of the deep model and an incremental model update without access to a bounded memory of past data. Then, the repres...
[ { "created": "Mon, 31 Aug 2020 16:18:12 GMT", "version": "v1" } ]
2020-09-01
[ [ "Belouadah", "Eden", "" ], [ "Popescu", "Adrian", "" ], [ "Kanellos", "Ioannis", "" ] ]
Incremental Learning (IL) is useful when artificial systems need to deal with streams of data and do not have access to all data at all times. The most challenging setting requires a constant complexity of the deep model and an incremental model update without access to a bounded memory of past data. Then, the represen...
1709.08696
David Mestel
David Mestel
Widths of regular and context-free languages
22 pages
39th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2019)
10.4230/LIPIcs.FSTTCS.2019.49
null
cs.FL cs.DM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Given a partially-ordered finite alphabet $\Sigma$ and a language $L\subseteq \Sigma^*$, how large can an antichain in $L$ be (where $L$ is given the lexicographic ordering)? More precisely, since $L$ will in general be infinite, we should ask about the rate of growth of maximum antichains consisting of words of leng...
[ { "created": "Mon, 25 Sep 2017 19:45:03 GMT", "version": "v1" }, { "created": "Fri, 24 Nov 2017 14:31:01 GMT", "version": "v2" }, { "created": "Sat, 17 Nov 2018 05:19:14 GMT", "version": "v3" }, { "created": "Fri, 15 Feb 2019 10:06:16 GMT", "version": "v4" }, { "c...
2019-12-10
[ [ "Mestel", "David", "" ] ]
Given a partially-ordered finite alphabet $\Sigma$ and a language $L\subseteq \Sigma^*$, how large can an antichain in $L$ be (where $L$ is given the lexicographic ordering)? More precisely, since $L$ will in general be infinite, we should ask about the rate of growth of maximum antichains consisting of words of length...
2009.11142
Patrick Rodler
Patrick Rodler and Erich Teppan
The Scheduling Job-Set Optimization Problem: A Model-Based Diagnosis Approach
See also the online proceedings of the International Workshop on Principles of Diagnosis (DX-2020): http://www.dx-2020.org/papers/DX-2020_paper_18.pdf
null
null
null
cs.AI
http://creativecommons.org/licenses/by-sa/4.0/
A common issue for companies is that the volume of product orders may at times exceed the production capacity. We formally introduce two novel problems dealing with the question which orders to discard or postpone in order to meet certain (timeliness) goals, and try to approach them by means of model-based diagnosis....
[ { "created": "Wed, 23 Sep 2020 13:38:36 GMT", "version": "v1" }, { "created": "Thu, 4 Aug 2022 12:36:06 GMT", "version": "v2" } ]
2022-08-05
[ [ "Rodler", "Patrick", "" ], [ "Teppan", "Erich", "" ] ]
A common issue for companies is that the volume of product orders may at times exceed the production capacity. We formally introduce two novel problems dealing with the question which orders to discard or postpone in order to meet certain (timeliness) goals, and try to approach them by means of model-based diagnosis. I...
1704.05232
Ragesh Jaiswal
Anup Bhattacharya and Yoav Freund and Ragesh Jaiswal
On the k-Means/Median Cost Function
This update includes minor improvements and a new section on Dimension Estimation
null
null
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this work, we study the $k$-means cost function. Given a dataset $X \subseteq \mathbb{R}^d$ and an integer $k$, the goal of the Euclidean $k$-means problem is to find a set of $k$ centers $C \subseteq \mathbb{R}^d$ such that $\Phi(C, X) \equiv \sum_{x \in X} \min_{c \in C} ||x - c||^2$ is minimized. Let $\Delta(X,...
[ { "created": "Tue, 18 Apr 2017 08:34:34 GMT", "version": "v1" }, { "created": "Thu, 9 Sep 2021 06:36:13 GMT", "version": "v2" } ]
2021-09-10
[ [ "Bhattacharya", "Anup", "" ], [ "Freund", "Yoav", "" ], [ "Jaiswal", "Ragesh", "" ] ]
In this work, we study the $k$-means cost function. Given a dataset $X \subseteq \mathbb{R}^d$ and an integer $k$, the goal of the Euclidean $k$-means problem is to find a set of $k$ centers $C \subseteq \mathbb{R}^d$ such that $\Phi(C, X) \equiv \sum_{x \in X} \min_{c \in C} ||x - c||^2$ is minimized. Let $\Delta(X,k)...
2311.10089
Yaniv Taigman
Shelly Sheynin, Adam Polyak, Uriel Singer, Yuval Kirstain, Amit Zohar, Oron Ashual, Devi Parikh, Yaniv Taigman
Emu Edit: Precise Image Editing via Recognition and Generation Tasks
null
null
null
null
cs.CV cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Instruction-based image editing holds immense potential for a variety of applications, as it enables users to perform any editing operation using a natural language instruction. However, current models in this domain often struggle with accurately executing user instructions. We present Emu Edit, a multi-task image e...
[ { "created": "Thu, 16 Nov 2023 18:55:58 GMT", "version": "v1" } ]
2023-11-17
[ [ "Sheynin", "Shelly", "" ], [ "Polyak", "Adam", "" ], [ "Singer", "Uriel", "" ], [ "Kirstain", "Yuval", "" ], [ "Zohar", "Amit", "" ], [ "Ashual", "Oron", "" ], [ "Parikh", "Devi", "" ], [ "Taigman",...
Instruction-based image editing holds immense potential for a variety of applications, as it enables users to perform any editing operation using a natural language instruction. However, current models in this domain often struggle with accurately executing user instructions. We present Emu Edit, a multi-task image edi...
2201.08296
Ian T Foster
Ian Foster and Carl Kesselman
CUF-Links: Continuous and Ubiquitous FAIRness Linkages for reproducible research
null
Computer, vol. 55, no. 8, pp. 20-30, Aug. 2022
10.1109/MC.2022.3160876
null
cs.SE cs.SI
http://creativecommons.org/licenses/by/4.0/
Despite much creative work on methods and tools, reproducibility -- the ability to repeat the computational steps used to obtain a research result -- remains elusive. One reason for these difficulties is that extant tools for capturing research processes do not align well with the rich working practices of scientists...
[ { "created": "Thu, 20 Jan 2022 17:03:37 GMT", "version": "v1" } ]
2022-08-30
[ [ "Foster", "Ian", "" ], [ "Kesselman", "Carl", "" ] ]
Despite much creative work on methods and tools, reproducibility -- the ability to repeat the computational steps used to obtain a research result -- remains elusive. One reason for these difficulties is that extant tools for capturing research processes do not align well with the rich working practices of scientists. ...
2403.19867
Hoa Vu
Huy Pham, Hoang Ta, Hoa T. Vu
Finding Decision Tree Splits in Streaming and Massively Parallel Models
null
null
null
null
cs.DS cs.AI cs.LG
http://creativecommons.org/licenses/by/4.0/
In this work, we provide data stream algorithms that compute optimal splits in decision tree learning. In particular, given a data stream of observations $x_i$ and their labels $y_i$, the goal is to find the optimal split point $j$ that divides the data into two sets such that the mean squared error (for regression) ...
[ { "created": "Thu, 28 Mar 2024 22:26:38 GMT", "version": "v1" }, { "created": "Wed, 17 Apr 2024 07:57:44 GMT", "version": "v2" } ]
2024-04-18
[ [ "Pham", "Huy", "" ], [ "Ta", "Hoang", "" ], [ "Vu", "Hoa T.", "" ] ]
In this work, we provide data stream algorithms that compute optimal splits in decision tree learning. In particular, given a data stream of observations $x_i$ and their labels $y_i$, the goal is to find the optimal split point $j$ that divides the data into two sets such that the mean squared error (for regression) or...
1903.11960
Luca Franceschi
Luca Franceschi, Mathias Niepert, Massimiliano Pontil, Xiao He
Learning Discrete Structures for Graph Neural Networks
ICML 2019, code at https://github.com/lucfra/LDS - Revision of Sec. 3
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Graph neural networks (GNNs) are a popular class of machine learning models whose major advantage is their ability to incorporate a sparse and discrete dependency structure between data points. Unfortunately, GNNs can only be used when such a graph-structure is available. In practice, however, real-world graphs are o...
[ { "created": "Thu, 28 Mar 2019 13:30:24 GMT", "version": "v1" }, { "created": "Mon, 29 Apr 2019 09:53:04 GMT", "version": "v2" }, { "created": "Fri, 17 May 2019 09:43:48 GMT", "version": "v3" }, { "created": "Fri, 19 Jun 2020 09:44:16 GMT", "version": "v4" } ]
2020-06-22
[ [ "Franceschi", "Luca", "" ], [ "Niepert", "Mathias", "" ], [ "Pontil", "Massimiliano", "" ], [ "He", "Xiao", "" ] ]
Graph neural networks (GNNs) are a popular class of machine learning models whose major advantage is their ability to incorporate a sparse and discrete dependency structure between data points. Unfortunately, GNNs can only be used when such a graph-structure is available. In practice, however, real-world graphs are oft...
1409.1461
David Flatow
David Flatow, Mor Naaman, Ke Eddie Xie, Yana Volkovich, Yaron Kanza
On the Accuracy of Hyper-local Geotagging of Social Media Content
10 pages
null
null
null
cs.IR cs.SI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Social media users share billions of items per year, only a small fraction of which is geotagged. We present a data- driven approach for identifying non-geotagged content items that can be associated with a hyper-local geographic area by modeling the location distributions of hyper-local n-grams that appear in the te...
[ { "created": "Thu, 4 Sep 2014 15:10:32 GMT", "version": "v1" }, { "created": "Sun, 1 Feb 2015 05:52:55 GMT", "version": "v2" } ]
2015-02-03
[ [ "Flatow", "David", "" ], [ "Naaman", "Mor", "" ], [ "Xie", "Ke Eddie", "" ], [ "Volkovich", "Yana", "" ], [ "Kanza", "Yaron", "" ] ]
Social media users share billions of items per year, only a small fraction of which is geotagged. We present a data- driven approach for identifying non-geotagged content items that can be associated with a hyper-local geographic area by modeling the location distributions of hyper-local n-grams that appear in the text...
2103.16516
Aj Piergiovanni
AJ Piergiovanni and Michael S. Ryoo
Recognizing Actions in Videos from Unseen Viewpoints
null
CVPR 2021
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Standard methods for video recognition use large CNNs designed to capture spatio-temporal data. However, training these models requires a large amount of labeled training data, containing a wide variety of actions, scenes, settings and camera viewpoints. In this paper, we show that current convolutional neural networ...
[ { "created": "Tue, 30 Mar 2021 17:17:54 GMT", "version": "v1" } ]
2021-03-31
[ [ "Piergiovanni", "AJ", "" ], [ "Ryoo", "Michael S.", "" ] ]
Standard methods for video recognition use large CNNs designed to capture spatio-temporal data. However, training these models requires a large amount of labeled training data, containing a wide variety of actions, scenes, settings and camera viewpoints. In this paper, we show that current convolutional neural network ...
1203.2900
Dominique Duval
Jean-Guillaume Dumas (LJK), Dominique Duval (LJK), Laurent Fousse (LJK), Jean-Claude Reynaud (RC)
Decorated proofs for computational effects: Exceptions
11 pages
null
null
null
cs.LO math.CT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We define a proof system for exceptions which is close to the syntax for exceptions, in the sense that the exceptions do not appear explicitly in the type of any expression. This proof system is sound with respect to the intended denotational semantics of exceptions. With this inference system we prove several proper...
[ { "created": "Tue, 13 Mar 2012 19:21:55 GMT", "version": "v1" } ]
2012-03-15
[ [ "Dumas", "Jean-Guillaume", "", "LJK" ], [ "Duval", "Dominique", "", "LJK" ], [ "Fousse", "Laurent", "", "LJK" ], [ "Reynaud", "Jean-Claude", "", "RC" ] ]
We define a proof system for exceptions which is close to the syntax for exceptions, in the sense that the exceptions do not appear explicitly in the type of any expression. This proof system is sound with respect to the intended denotational semantics of exceptions. With this inference system we prove several properti...
1312.5345
Wei-Cheng Liao
Wei-Cheng Liao, Mingyi Hong, Hamid Farmanbar, Xu Li, Zhi-Quan Luo, and Hang Zhang
Min Flow Rate Maximization for Software Defined Radio Access Networks
Submitted to JSAC special issue on 5G Wireless Communication Systems
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We consider a heterogeneous network (HetNet) of base stations (BSs) connected via a backhaul network of routers and wired/wireless links with limited capacity. The optimal provision of such networks requires proper resource allocation across the radio access links in conjunction with appropriate traffic engineering w...
[ { "created": "Wed, 18 Dec 2013 21:30:51 GMT", "version": "v1" } ]
2013-12-20
[ [ "Liao", "Wei-Cheng", "" ], [ "Hong", "Mingyi", "" ], [ "Farmanbar", "Hamid", "" ], [ "Li", "Xu", "" ], [ "Luo", "Zhi-Quan", "" ], [ "Zhang", "Hang", "" ] ]
We consider a heterogeneous network (HetNet) of base stations (BSs) connected via a backhaul network of routers and wired/wireless links with limited capacity. The optimal provision of such networks requires proper resource allocation across the radio access links in conjunction with appropriate traffic engineering wit...
2006.11719
Liu Yang
Zizhen Wang, Yixing Fan, Jiafeng Guo, Liu Yang, Ruqing Zhang, Yanyan Lan, Xueqi Cheng, Hui Jiang, Xiaozhao Wang
Match$^2$: A Matching over Matching Model for Similar Question Identification
Accepted by SIGIR 2020. 10 pages
null
null
null
cs.IR cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Community Question Answering (CQA) has become a primary means for people to acquire knowledge, where people are free to ask questions or submit answers. To enhance the efficiency of the service, similar question identification becomes a core task in CQA which aims to find a similar question from the archived reposito...
[ { "created": "Sun, 21 Jun 2020 05:59:34 GMT", "version": "v1" } ]
2020-06-23
[ [ "Wang", "Zizhen", "" ], [ "Fan", "Yixing", "" ], [ "Guo", "Jiafeng", "" ], [ "Yang", "Liu", "" ], [ "Zhang", "Ruqing", "" ], [ "Lan", "Yanyan", "" ], [ "Cheng", "Xueqi", "" ], [ "Jiang", "Hui", ...
Community Question Answering (CQA) has become a primary means for people to acquire knowledge, where people are free to ask questions or submit answers. To enhance the efficiency of the service, similar question identification becomes a core task in CQA which aims to find a similar question from the archived repository...
2407.14504
Bahram Jalali
Yiming Zhou, Callen MacPhee, Tingyi Zhou, Bahram Jalali
Nonlinear Schr\"odinger Network
null
null
null
null
cs.LG
http://creativecommons.org/licenses/by-nc-nd/4.0/
Deep neural networks (DNNs) have achieved exceptional performance across various fields by learning complex nonlinear mappings from large-scale datasets. However, they encounter challenges such as high computational costs and limited interpretability. To address these issues, hybrid approaches that integrate physics ...
[ { "created": "Fri, 19 Jul 2024 17:58:00 GMT", "version": "v1" }, { "created": "Wed, 24 Jul 2024 04:33:55 GMT", "version": "v2" } ]
2024-07-25
[ [ "Zhou", "Yiming", "" ], [ "MacPhee", "Callen", "" ], [ "Zhou", "Tingyi", "" ], [ "Jalali", "Bahram", "" ] ]
Deep neural networks (DNNs) have achieved exceptional performance across various fields by learning complex nonlinear mappings from large-scale datasets. However, they encounter challenges such as high computational costs and limited interpretability. To address these issues, hybrid approaches that integrate physics wi...
2309.00184
Md Abu Sayed
Md Abu Sayed, Moqsadur Rahman, Mohammad Ariful Islam Khan, Deepak Tosh
A Survey of Network Requirements for Enabling Effective Cyber Deception
null
null
null
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In the evolving landscape of cybersecurity, the utilization of cyber deception has gained prominence as a proactive defense strategy against sophisticated attacks. This paper presents a comprehensive survey that investigates the crucial network requirements essential for the successful implementation of effective cyb...
[ { "created": "Fri, 1 Sep 2023 00:38:57 GMT", "version": "v1" }, { "created": "Fri, 27 Oct 2023 01:10:00 GMT", "version": "v2" }, { "created": "Mon, 8 Jan 2024 05:09:31 GMT", "version": "v3" } ]
2024-01-09
[ [ "Sayed", "Md Abu", "" ], [ "Rahman", "Moqsadur", "" ], [ "Khan", "Mohammad Ariful Islam", "" ], [ "Tosh", "Deepak", "" ] ]
In the evolving landscape of cybersecurity, the utilization of cyber deception has gained prominence as a proactive defense strategy against sophisticated attacks. This paper presents a comprehensive survey that investigates the crucial network requirements essential for the successful implementation of effective cyber...
2209.05580
Joshua Ott
Joshua Ott, Sung-Kyun Kim, Amanda Bouman, Oriana Peltzer, Mamoru Sobue, Harrison Delecki, Mykel J. Kochenderfer, Joel Burdick, Ali-akbar Agha-mohammadi
Risk-aware Meta-level Decision Making for Exploration Under Uncertainty
IEEE International Conference on Control, Decision and Information Technologies
null
null
null
cs.RO cs.AI
http://creativecommons.org/licenses/by-nc-nd/4.0/
Robotic exploration of unknown environments is fundamentally a problem of decision making under uncertainty where the robot must account for uncertainty in sensor measurements, localization, action execution, as well as many other factors. For large-scale exploration applications, autonomous systems must overcome the...
[ { "created": "Mon, 12 Sep 2022 20:05:14 GMT", "version": "v1" }, { "created": "Sun, 10 Dec 2023 19:12:46 GMT", "version": "v2" }, { "created": "Tue, 30 Apr 2024 15:38:46 GMT", "version": "v3" } ]
2024-05-01
[ [ "Ott", "Joshua", "" ], [ "Kim", "Sung-Kyun", "" ], [ "Bouman", "Amanda", "" ], [ "Peltzer", "Oriana", "" ], [ "Sobue", "Mamoru", "" ], [ "Delecki", "Harrison", "" ], [ "Kochenderfer", "Mykel J.", "" ], ...
Robotic exploration of unknown environments is fundamentally a problem of decision making under uncertainty where the robot must account for uncertainty in sensor measurements, localization, action execution, as well as many other factors. For large-scale exploration applications, autonomous systems must overcome the c...
2009.14759
Yuxuan Wu
Yuxuan Wu and Hideki Nakayama
Graph-based Heuristic Search for Module Selection Procedure in Neural Module Network
in Neural Module Network[C]//Proceedings of the Asian Conference on Computer Vision. 2020
null
null
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Neural Module Network (NMN) is a machine learning model for solving the visual question answering tasks. NMN uses programs to encode modules' structures, and its modularized architecture enables it to solve logical problems more reasonably. However, because of the non-differentiable procedure of module selection, NMN...
[ { "created": "Wed, 30 Sep 2020 15:55:44 GMT", "version": "v1" } ]
2020-11-30
[ [ "Wu", "Yuxuan", "" ], [ "Nakayama", "Hideki", "" ] ]
Neural Module Network (NMN) is a machine learning model for solving the visual question answering tasks. NMN uses programs to encode modules' structures, and its modularized architecture enables it to solve logical problems more reasonably. However, because of the non-differentiable procedure of module selection, NMN i...
1308.3693
Louis Francois Pau
L.-F. Pau
Business and social evaluation of denial of service attacks of communications networks in view of scaling economic counter-measures
null
The virtual battlefield : perspectives on cyber warfare , Cryptology and information security Series, Vol 3, IOS Press, Amsterdam, 2009, pp. 282-293
null
null
cs.CY cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper gives an analytical method to determine the economic and indirect implications of denial of service and distributed denial of service attacks. It is based on time preference dynamics applied to the monetary mass for the restoration of capabilities, on long term investments to rebuild capabilities, and of t...
[ { "created": "Tue, 13 Aug 2013 18:38:25 GMT", "version": "v1" } ]
2013-08-19
[ [ "Pau", "L. -F.", "" ] ]
This paper gives an analytical method to determine the economic and indirect implications of denial of service and distributed denial of service attacks. It is based on time preference dynamics applied to the monetary mass for the restoration of capabilities, on long term investments to rebuild capabilities, and of the...
1705.01784
Changjun Wang
Zhigang Cao, Bo Chen, Xujin Chen, Changjun Wang
A Network Game of Dynamic Traffic
Extended Abstract in Proceedings of the 18th ACM Conference on Economics and Computation
null
null
null
cs.GT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We study a network congestion game of discrete-time dynamic traffic of atomic agents with a single origin-destination pair. Any agent freely makes a dynamic decision at each vertex (e.g., road crossing) and traffic is regulated with given priorities on edges (e.g., road segments). We first constructively prove that t...
[ { "created": "Thu, 4 May 2017 10:33:03 GMT", "version": "v1" } ]
2017-05-05
[ [ "Cao", "Zhigang", "" ], [ "Chen", "Bo", "" ], [ "Chen", "Xujin", "" ], [ "Wang", "Changjun", "" ] ]
We study a network congestion game of discrete-time dynamic traffic of atomic agents with a single origin-destination pair. Any agent freely makes a dynamic decision at each vertex (e.g., road crossing) and traffic is regulated with given priorities on edges (e.g., road segments). We first constructively prove that the...
2302.09189
Teruaki Hayashi
Koike Hiroaki and Teruaki Hayashi
Extraction of Constituent Factors of Digestion Efficiency in Information Transfer by Media Composed of Texts and Images
This paper is the revised version of the 29th annual conference of the Natural Language Processing Society in Japan, in Japanese language
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
The development and spread of information and communication technologies have increased and diversified information. However, the increase in the volume and the selection of information does not necessarily promote understanding. In addition, conventional evaluations of information transfer have focused only on the a...
[ { "created": "Fri, 17 Feb 2023 23:45:02 GMT", "version": "v1" } ]
2023-02-21
[ [ "Hiroaki", "Koike", "" ], [ "Hayashi", "Teruaki", "" ] ]
The development and spread of information and communication technologies have increased and diversified information. However, the increase in the volume and the selection of information does not necessarily promote understanding. In addition, conventional evaluations of information transfer have focused only on the arr...
1507.07648
Rehan Abdul Aziz
Rehan Abdul Aziz and Geoffrey Chu and Christian Muise and Peter Stuckey
Projected Model Counting
null
null
null
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Model counting is the task of computing the number of assignments to variables V that satisfy a given propositional theory F. Model counting is an essential tool in probabilistic reasoning. In this paper, we introduce the problem of model counting projected on a subset P of original variables that we call 'priority' ...
[ { "created": "Tue, 28 Jul 2015 05:45:05 GMT", "version": "v1" } ]
2015-07-29
[ [ "Aziz", "Rehan Abdul", "" ], [ "Chu", "Geoffrey", "" ], [ "Muise", "Christian", "" ], [ "Stuckey", "Peter", "" ] ]
Model counting is the task of computing the number of assignments to variables V that satisfy a given propositional theory F. Model counting is an essential tool in probabilistic reasoning. In this paper, we introduce the problem of model counting projected on a subset P of original variables that we call 'priority' va...
1811.07958
Brent Griffin
Brent A. Griffin and Jason J. Corso
Tukey-Inspired Video Object Segmentation
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We investigate the problem of strictly unsupervised video object segmentation, i.e., the separation of a primary object from background in video without a user-provided object mask or any training on an annotated dataset. We find foreground objects in low-level vision data using a John Tukey-inspired measure of "outl...
[ { "created": "Mon, 19 Nov 2018 20:15:27 GMT", "version": "v1" }, { "created": "Fri, 30 Nov 2018 02:37:11 GMT", "version": "v2" } ]
2018-12-03
[ [ "Griffin", "Brent A.", "" ], [ "Corso", "Jason J.", "" ] ]
We investigate the problem of strictly unsupervised video object segmentation, i.e., the separation of a primary object from background in video without a user-provided object mask or any training on an annotated dataset. We find foreground objects in low-level vision data using a John Tukey-inspired measure of "outlie...
1705.11175
Nathanael Lemessa Baisa
Nathanael L. Baisa, Deepayan Bhowmik and Andrew Wallace
Long-term Correlation Tracking using Multi-layer Hybrid Features in Sparse and Dense Environments
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Tracking a target of interest in both sparse and crowded environments is a challenging problem, not yet successfully addressed in the literature. In this paper, we propose a new long-term visual tracking algorithm, learning discriminative correlation filters and using an online classifier, to track a target of intere...
[ { "created": "Wed, 31 May 2017 16:44:45 GMT", "version": "v1" }, { "created": "Fri, 2 Jun 2017 00:37:05 GMT", "version": "v2" }, { "created": "Mon, 27 Nov 2017 14:54:39 GMT", "version": "v3" }, { "created": "Mon, 16 Apr 2018 09:43:49 GMT", "version": "v4" }, { "cr...
2019-02-05
[ [ "Baisa", "Nathanael L.", "" ], [ "Bhowmik", "Deepayan", "" ], [ "Wallace", "Andrew", "" ] ]
Tracking a target of interest in both sparse and crowded environments is a challenging problem, not yet successfully addressed in the literature. In this paper, we propose a new long-term visual tracking algorithm, learning discriminative correlation filters and using an online classifier, to track a target of interest...
2111.00684
Lu Lin
Lu Lin, Ethan Blaser and Hongning Wang
Graph Structural Attack by Perturbing Spectral Distance
Proceedings of the 28th ACM SIGKDD international conference on knowledge discovery & data mining (KDD'22)
null
null
null
cs.LG cs.AI cs.CR cs.SI
http://creativecommons.org/licenses/by/4.0/
Graph Convolutional Networks (GCNs) have fueled a surge of research interest due to their encouraging performance on graph learning tasks, but they are also shown vulnerability to adversarial attacks. In this paper, an effective graph structural attack is investigated to disrupt graph spectral filters in the Fourier ...
[ { "created": "Mon, 1 Nov 2021 04:02:34 GMT", "version": "v1" }, { "created": "Wed, 3 Nov 2021 14:54:33 GMT", "version": "v2" }, { "created": "Sun, 2 Oct 2022 21:39:21 GMT", "version": "v3" } ]
2022-10-04
[ [ "Lin", "Lu", "" ], [ "Blaser", "Ethan", "" ], [ "Wang", "Hongning", "" ] ]
Graph Convolutional Networks (GCNs) have fueled a surge of research interest due to their encouraging performance on graph learning tasks, but they are also shown vulnerability to adversarial attacks. In this paper, an effective graph structural attack is investigated to disrupt graph spectral filters in the Fourier do...
2210.13578
Reza Rawassizadeh
Xiang Ji and Yesim Sungu-Eryilmaz and Elaheh Momeni and Reza Rawassizadeh
Speeding Up Question Answering Task of Language Models via Inverted Index
null
null
null
null
cs.CL cs.IR cs.LG
http://creativecommons.org/licenses/by/4.0/
Natural language processing applications, such as conversational agents and their question-answering capabilities, are widely used in the real world. Despite the wide popularity of large language models (LLMs), few real-world conversational agents take advantage of LLMs. Extensive resources consumed by LLMs disable d...
[ { "created": "Mon, 24 Oct 2022 19:59:17 GMT", "version": "v1" } ]
2022-10-26
[ [ "Ji", "Xiang", "" ], [ "Sungu-Eryilmaz", "Yesim", "" ], [ "Momeni", "Elaheh", "" ], [ "Rawassizadeh", "Reza", "" ] ]
Natural language processing applications, such as conversational agents and their question-answering capabilities, are widely used in the real world. Despite the wide popularity of large language models (LLMs), few real-world conversational agents take advantage of LLMs. Extensive resources consumed by LLMs disable dev...
1708.09630
Rohollah Moghadam
Rohollah Moghadam and Hamidreza Modares
Resilient Autonomous Control of Distributed Multi-agent Systems in Contested Environments
null
null
null
null
cs.MA cs.LG cs.SY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
An autonomous and resilient controller is proposed for leader-follower multi-agent systems under uncertainties and cyber-physical attacks. The leader is assumed non-autonomous with a nonzero control input, which allows changing the team behavior or mission in response to environmental changes. A resilient learning-ba...
[ { "created": "Thu, 31 Aug 2017 09:21:08 GMT", "version": "v1" }, { "created": "Sat, 30 Sep 2017 13:52:23 GMT", "version": "v2" }, { "created": "Sun, 31 Dec 2017 05:51:31 GMT", "version": "v3" }, { "created": "Mon, 9 Apr 2018 02:25:13 GMT", "version": "v4" } ]
2018-04-10
[ [ "Moghadam", "Rohollah", "" ], [ "Modares", "Hamidreza", "" ] ]
An autonomous and resilient controller is proposed for leader-follower multi-agent systems under uncertainties and cyber-physical attacks. The leader is assumed non-autonomous with a nonzero control input, which allows changing the team behavior or mission in response to environmental changes. A resilient learning-base...
2402.18201
Sen Xu
Sen Xu, Shikui Wei, Tao Ruan, and Lixin Liao
Learning Invariant Inter-pixel Correlations for Superpixel Generation
Accepted by AAAI24
Proceedings of the AAAI Conference on Artificial Intelligence, 38(6), 6351-6359 (2024)
10.1609/aaai.v38i6.28454
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Deep superpixel algorithms have made remarkable strides by substituting hand-crafted features with learnable ones. Nevertheless, we observe that existing deep superpixel methods, serving as mid-level representation operations, remain sensitive to the statistical properties (e.g., color distribution, high-level semant...
[ { "created": "Wed, 28 Feb 2024 09:46:56 GMT", "version": "v1" }, { "created": "Tue, 9 Apr 2024 07:18:41 GMT", "version": "v2" } ]
2024-04-10
[ [ "Xu", "Sen", "" ], [ "Wei", "Shikui", "" ], [ "Ruan", "Tao", "" ], [ "Liao", "Lixin", "" ] ]
Deep superpixel algorithms have made remarkable strides by substituting hand-crafted features with learnable ones. Nevertheless, we observe that existing deep superpixel methods, serving as mid-level representation operations, remain sensitive to the statistical properties (e.g., color distribution, high-level semantic...
2109.06862
Saibo Geng
Saibo Geng, R\'emi Lebret, Karl Aberer
Legal Transformer Models May Not Always Help
null
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
Deep learning-based Natural Language Processing methods, especially transformers, have achieved impressive performance in the last few years. Applying those state-of-the-art NLP methods to legal activities to automate or simplify some simple work is of great value. This work investigates the value of domain adaptive ...
[ { "created": "Tue, 14 Sep 2021 17:53:55 GMT", "version": "v1" }, { "created": "Wed, 15 Sep 2021 07:14:15 GMT", "version": "v2" } ]
2021-09-16
[ [ "Geng", "Saibo", "" ], [ "Lebret", "Rémi", "" ], [ "Aberer", "Karl", "" ] ]
Deep learning-based Natural Language Processing methods, especially transformers, have achieved impressive performance in the last few years. Applying those state-of-the-art NLP methods to legal activities to automate or simplify some simple work is of great value. This work investigates the value of domain adaptive pr...
2211.16356
Runjia Li
Runjia Li, Yang Yu, Charlie Haywood
Real-time Blind Deblurring Based on Lightweight Deep-Wiener-Network
imcomplete figures
null
null
null
cs.CV eess.IV
http://creativecommons.org/licenses/by/4.0/
In this paper, we address the problem of blind deblurring with high efficiency. We propose a set of lightweight deep-wiener-network to finish the task with real-time speed. The Network contains a deep neural network for estimating parameters of wiener networks and a wiener network for deblurring. Experimental evaluat...
[ { "created": "Tue, 29 Nov 2022 16:42:01 GMT", "version": "v1" }, { "created": "Wed, 11 Jan 2023 21:24:51 GMT", "version": "v2" }, { "created": "Tue, 14 Feb 2023 12:38:06 GMT", "version": "v3" } ]
2023-02-15
[ [ "Li", "Runjia", "" ], [ "Yu", "Yang", "" ], [ "Haywood", "Charlie", "" ] ]
In this paper, we address the problem of blind deblurring with high efficiency. We propose a set of lightweight deep-wiener-network to finish the task with real-time speed. The Network contains a deep neural network for estimating parameters of wiener networks and a wiener network for deblurring. Experimental evaluatio...
1907.04228
Michael Bullock
Michael S. Bullock, Christos N. Gagatsos, Saikat Guha, and Boulat A. Bash
Fundamental limits of quantum-secure covert communication over bosonic channels
null
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We investigate the fundamental limit of quantum-secure covert communication over the lossy thermal noise bosonic channel, the quantum-mechanical model underlying many practical channels. We assume that the adversary has unlimited quantum information processing capabilities as well as access to all transmitted photons...
[ { "created": "Tue, 9 Jul 2019 15:09:16 GMT", "version": "v1" } ]
2019-07-10
[ [ "Bullock", "Michael S.", "" ], [ "Gagatsos", "Christos N.", "" ], [ "Guha", "Saikat", "" ], [ "Bash", "Boulat A.", "" ] ]
We investigate the fundamental limit of quantum-secure covert communication over the lossy thermal noise bosonic channel, the quantum-mechanical model underlying many practical channels. We assume that the adversary has unlimited quantum information processing capabilities as well as access to all transmitted photons t...
1607.07911
Thomas Kalinowski
Rachel Wulan Nirmalasari Wijaya, Andrea Semani\v{c}ov\'a-Fe\v{n}ov\v{c}\'ikov\'a, Joe Ryan, Thomas Kalinowski
$H$-supermagic labelings for firecrackers, banana trees and flowers
null
Australasian Journal of Combinatorics, 69(3), 442-451, 2017
null
null
cs.DM math.CO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A simple graph $G=(V,E)$ admits an $H$-covering if every edge in $E$ is contained in a subgraph $H'=(V',E')$ of $G$ which is isomorphic to $H$. In this case we say that $G$ is $H$-supermagic if there is a bijection $f:V\cup E\to\{1,\ldots\lvert V\rvert+\lvert E\rvert\}$ such that $f(V)=\{1,\ldots,\lvert V\rvert\}$ an...
[ { "created": "Tue, 26 Jul 2016 22:46:49 GMT", "version": "v1" }, { "created": "Tue, 27 Jun 2017 06:08:20 GMT", "version": "v2" } ]
2018-01-17
[ [ "Wijaya", "Rachel Wulan Nirmalasari", "" ], [ "Semaničová-Feňovčíková", "Andrea", "" ], [ "Ryan", "Joe", "" ], [ "Kalinowski", "Thomas", "" ] ]
A simple graph $G=(V,E)$ admits an $H$-covering if every edge in $E$ is contained in a subgraph $H'=(V',E')$ of $G$ which is isomorphic to $H$. In this case we say that $G$ is $H$-supermagic if there is a bijection $f:V\cup E\to\{1,\ldots\lvert V\rvert+\lvert E\rvert\}$ such that $f(V)=\{1,\ldots,\lvert V\rvert\}$ and ...
1210.0271
Lawrence Ong
Roy Timo, Gottfried Lechner, Lawrence Ong, Sarah J. Johnson
Multi-Way Relay Networks: Orthogonal Uplink, Source-Channel Separation and Code Design
Authors' final version (accepted and to appear in IEEE Transactions on Communications)
IEEE Transactions on Communications, Vol. 61, No. 2, pp. 753-768, Feb. 2013
10.1109/TCOMM.2012.121112.110730
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We consider a multi-way relay network with an orthogonal uplink and correlated sources, and we characterise reliable communication (in the usual Shannon sense) with a single-letter expression. The characterisation is obtained using a joint source-channel random-coding argument, which is based on a combination of Wyne...
[ { "created": "Mon, 1 Oct 2012 01:09:32 GMT", "version": "v1" } ]
2013-09-18
[ [ "Timo", "Roy", "" ], [ "Lechner", "Gottfried", "" ], [ "Ong", "Lawrence", "" ], [ "Johnson", "Sarah J.", "" ] ]
We consider a multi-way relay network with an orthogonal uplink and correlated sources, and we characterise reliable communication (in the usual Shannon sense) with a single-letter expression. The characterisation is obtained using a joint source-channel random-coding argument, which is based on a combination of Wyner ...
2108.05575
Gosse Minnema
Gosse Minnema
Kicktionary-LOME: A Domain-Specific Multilingual Frame Semantic Parsing Model for Football Language
null
null
null
null
cs.CL
http://creativecommons.org/licenses/by-sa/4.0/
This technical report introduces an adapted version of the LOME frame semantic parsing model (Xia et al., EACL 2021) which is capable of automatically annotating texts according to the "Kicktionary" domain-specific framenet resource. Several methods for training a model even with limited available training data are p...
[ { "created": "Thu, 12 Aug 2021 07:47:13 GMT", "version": "v1" } ]
2021-08-13
[ [ "Minnema", "Gosse", "" ] ]
This technical report introduces an adapted version of the LOME frame semantic parsing model (Xia et al., EACL 2021) which is capable of automatically annotating texts according to the "Kicktionary" domain-specific framenet resource. Several methods for training a model even with limited available training data are pro...
1106.5451
Ilango Sriram
Ilango Sriram and Dave Cliff
Hybrid complex network topologies are preferred for component-subscription in large-scale data-centres
null
CompleNet 2010, CCIS vol. 116, pp. 130-137, Springer Heidelberg, 2011
null
null
cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We report on experiments exploring the interplay between the topology of the complex network of dependent components in a large-scale data-centre, and the robustness and scaling properties of that data-centre. In a previous paper [1] we used the SPECI large-scale data-centre simulator [2] to compare the robustness an...
[ { "created": "Mon, 27 Jun 2011 17:16:41 GMT", "version": "v1" } ]
2011-06-28
[ [ "Sriram", "Ilango", "" ], [ "Cliff", "Dave", "" ] ]
We report on experiments exploring the interplay between the topology of the complex network of dependent components in a large-scale data-centre, and the robustness and scaling properties of that data-centre. In a previous paper [1] we used the SPECI large-scale data-centre simulator [2] to compare the robustness and ...
1802.06767
Kyrylo Malakhov
A. V. Palagin, N.G. Petrenko, V.Yu. Velychko, K.S. Malakhov
The problem of the development ontology-driven architecture of intellectual software systems
in Russian; "Bibliography" section updated for correct identification of references by the Google Scholar parser software; 6 pages; 6 figures
Visnik of the Volodymyr Dahl East ukrainian national university 13 (2011) 179-184 Luhansk
null
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The paper describes the architecture of the intelligence system for automated design of ontological knowledge bases of domain areas and the software model of the management GUI (Graphical User Interface) subsystem
[ { "created": "Sat, 17 Feb 2018 10:24:01 GMT", "version": "v1" }, { "created": "Thu, 22 Feb 2018 12:57:27 GMT", "version": "v2" } ]
2018-02-23
[ [ "Palagin", "A. V.", "" ], [ "Petrenko", "N. G.", "" ], [ "Velychko", "V. Yu.", "" ], [ "Malakhov", "K. S.", "" ] ]
The paper describes the architecture of the intelligence system for automated design of ontological knowledge bases of domain areas and the software model of the management GUI (Graphical User Interface) subsystem
1311.2079
Myunghwan Kim
Myunghwan Kim and Jure Leskovec
Nonparametric Multi-group Membership Model for Dynamic Networks
In Advances in Neural Information Processing Systems 25 (2013)
null
null
null
cs.SI physics.soc-ph stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Relational data-like graphs, networks, and matrices-is often dynamic, where the relational structure evolves over time. A fundamental problem in the analysis of time-varying network data is to extract a summary of the common structure and the dynamics of the underlying relations between the entities. Here we build on...
[ { "created": "Fri, 8 Nov 2013 21:00:51 GMT", "version": "v1" } ]
2013-11-12
[ [ "Kim", "Myunghwan", "" ], [ "Leskovec", "Jure", "" ] ]
Relational data-like graphs, networks, and matrices-is often dynamic, where the relational structure evolves over time. A fundamental problem in the analysis of time-varying network data is to extract a summary of the common structure and the dynamics of the underlying relations between the entities. Here we build on t...
2406.04152
Steven Arzt
Steven Arzt, Linda Schreiber, Dominik Appelt
Position: How Regulation Will Change Software Security Research
5 pages, submitted to SE2023 workshop at FSE 2024
null
null
null
cs.SE
http://creativecommons.org/licenses/by-sa/4.0/
Software security has been an important research topic over the years. The community has proposed processes and tools for secure software development and security analysis. However, a significant number of vulnerabilities remains in real-world software-driven systems and products. To alleviate this problem, legisla...
[ { "created": "Thu, 6 Jun 2024 15:16:44 GMT", "version": "v1" } ]
2024-06-07
[ [ "Arzt", "Steven", "" ], [ "Schreiber", "Linda", "" ], [ "Appelt", "Dominik", "" ] ]
Software security has been an important research topic over the years. The community has proposed processes and tools for secure software development and security analysis. However, a significant number of vulnerabilities remains in real-world software-driven systems and products. To alleviate this problem, legislation...
2111.07898
Sushrut Thorat
Sushrut Thorat, Giacomo Aldegheri, Tim C. Kietzmann
Category-orthogonal object features guide information processing in recurrent neural networks trained for object categorization
13 pages, 9 figures, peer-reviewed and accepted at the SVRHM 2021 workshop at NeurIPS (+ 2 additional sections in the Appendix presenting newer supplementary results). SVRHM 2021 Workshop@ NeurIPS. 2021
null
null
null
cs.CV cs.AI cs.LG
http://creativecommons.org/licenses/by/4.0/
Recurrent neural networks (RNNs) have been shown to perform better than feedforward architectures in visual object categorization tasks, especially in challenging conditions such as cluttered images. However, little is known about the exact computational role of recurrent information flow in these conditions. Here we...
[ { "created": "Mon, 15 Nov 2021 16:52:07 GMT", "version": "v1" }, { "created": "Tue, 10 May 2022 17:36:28 GMT", "version": "v2" } ]
2022-05-11
[ [ "Thorat", "Sushrut", "" ], [ "Aldegheri", "Giacomo", "" ], [ "Kietzmann", "Tim C.", "" ] ]
Recurrent neural networks (RNNs) have been shown to perform better than feedforward architectures in visual object categorization tasks, especially in challenging conditions such as cluttered images. However, little is known about the exact computational role of recurrent information flow in these conditions. Here we t...
2407.09950
Hossein Mousavi
Seyed Muhammad Hossein Mousavi
PSO Fuzzy XGBoost Classifier Boosted with Neural Gas Features on EEG Signals in Emotion Recognition
PSO, Fuzzy, XGBoost, Neural Gas Network (NGN), Feature Selection, EEG Signals, Emotion Recognition
null
null
null
cs.LG cs.NE
http://creativecommons.org/licenses/by/4.0/
Emotion recognition is the technology-driven process of identifying and categorizing human emotions from various data sources, such as facial expressions, voice patterns, body motion, and physiological signals, such as EEG. These physiological indicators, though rich in data, present challenges due to their complexit...
[ { "created": "Sat, 13 Jul 2024 17:15:23 GMT", "version": "v1" } ]
2024-07-16
[ [ "Mousavi", "Seyed Muhammad Hossein", "" ] ]
Emotion recognition is the technology-driven process of identifying and categorizing human emotions from various data sources, such as facial expressions, voice patterns, body motion, and physiological signals, such as EEG. These physiological indicators, though rich in data, present challenges due to their complexity ...
1909.06892
Shubham Jain
Shubham Jain, Sumeet Kumar Gupta, Anand Raghunathan
TiM-DNN: Ternary in-Memory accelerator for Deep Neural Networks
12 pages, 18 figures, Accepted in IEEE Transactions on Very Large Scale Integration (VLSI) Systems 2020
null
null
null
cs.LG cs.AR cs.CV cs.ET
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The use of lower precision has emerged as a popular technique to optimize the compute and storage requirements of complex Deep Neural Networks (DNNs). In the quest for lower precision, recent studies have shown that ternary DNNs (which represent weights and activations by signed ternary values) represent a promising ...
[ { "created": "Sun, 15 Sep 2019 21:43:19 GMT", "version": "v1" }, { "created": "Mon, 30 Sep 2019 03:59:26 GMT", "version": "v2" }, { "created": "Tue, 5 May 2020 02:42:18 GMT", "version": "v3" } ]
2020-05-06
[ [ "Jain", "Shubham", "" ], [ "Gupta", "Sumeet Kumar", "" ], [ "Raghunathan", "Anand", "" ] ]
The use of lower precision has emerged as a popular technique to optimize the compute and storage requirements of complex Deep Neural Networks (DNNs). In the quest for lower precision, recent studies have shown that ternary DNNs (which represent weights and activations by signed ternary values) represent a promising sw...
2110.00841
Aishwarya Sarkar
Aishwarya Sarkar, Jien Zhang, Chaoqun Lu, Ali Jannesari
Transfer Learning Approaches for Knowledge Discovery in Grid-based Geo-Spatiotemporal Data
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Extracting and meticulously analyzing geo-spatiotemporal features is crucial to recognize intricate underlying causes of natural events, such as floods. Limited evidence about hidden factors leading to climate change makes it challenging to predict regional water discharge accurately. In addition, the explosive growt...
[ { "created": "Sat, 2 Oct 2021 16:55:34 GMT", "version": "v1" }, { "created": "Fri, 29 Oct 2021 23:54:37 GMT", "version": "v2" }, { "created": "Tue, 2 Nov 2021 01:27:50 GMT", "version": "v3" } ]
2021-11-03
[ [ "Sarkar", "Aishwarya", "" ], [ "Zhang", "Jien", "" ], [ "Lu", "Chaoqun", "" ], [ "Jannesari", "Ali", "" ] ]
Extracting and meticulously analyzing geo-spatiotemporal features is crucial to recognize intricate underlying causes of natural events, such as floods. Limited evidence about hidden factors leading to climate change makes it challenging to predict regional water discharge accurately. In addition, the explosive growth ...
2407.06346
Fred Lu
Fred Lu, Ryan R. Curtin, Edward Raff, Francis Ferraro, James Holt
High-Dimensional Distributed Sparse Classification with Scalable Communication-Efficient Global Updates
KDD 2024, Research Track
null
10.1145/3637528.3672038
null
cs.LG cs.DC stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
As the size of datasets used in statistical learning continues to grow, distributed training of models has attracted increasing attention. These methods partition the data and exploit parallelism to reduce memory and runtime, but suffer increasingly from communication costs as the data size or the number of iteration...
[ { "created": "Mon, 8 Jul 2024 19:34:39 GMT", "version": "v1" } ]
2024-07-10
[ [ "Lu", "Fred", "" ], [ "Curtin", "Ryan R.", "" ], [ "Raff", "Edward", "" ], [ "Ferraro", "Francis", "" ], [ "Holt", "James", "" ] ]
As the size of datasets used in statistical learning continues to grow, distributed training of models has attracted increasing attention. These methods partition the data and exploit parallelism to reduce memory and runtime, but suffer increasingly from communication costs as the data size or the number of iterations ...
2310.05146
John Chong Min Tan
John Chong Min Tan, Mehul Motani
Large Language Model (LLM) as a System of Multiple Expert Agents: An Approach to solve the Abstraction and Reasoning Corpus (ARC) Challenge
6 main pages, 1 page references, 18 pages appendix
null
null
null
cs.AI cs.CL
http://creativecommons.org/licenses/by/4.0/
We attempt to solve the Abstraction and Reasoning Corpus (ARC) Challenge using Large Language Models (LLMs) as a system of multiple expert agents. Using the flexibility of LLMs to be prompted to do various novel tasks using zero-shot, few-shot, context-grounded prompting, we explore the feasibility of using LLMs to s...
[ { "created": "Sun, 8 Oct 2023 12:37:28 GMT", "version": "v1" } ]
2023-10-10
[ [ "Tan", "John Chong Min", "" ], [ "Motani", "Mehul", "" ] ]
We attempt to solve the Abstraction and Reasoning Corpus (ARC) Challenge using Large Language Models (LLMs) as a system of multiple expert agents. Using the flexibility of LLMs to be prompted to do various novel tasks using zero-shot, few-shot, context-grounded prompting, we explore the feasibility of using LLMs to sol...
2010.04434
Tielin Zhang
Tielin Zhang and Shuncheng Jia and Xiang Cheng and Bo Xu
Tuning Convolutional Spiking Neural Network with Biologically-plausible Reward Propagation
Final Version. Accepted by IEEE Transactions on Neural Networks and Learning Systems
null
null
null
cs.NE cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Spiking Neural Networks (SNNs) contain more biologically realistic structures and biologically-inspired learning principles than those in standard Artificial Neural Networks (ANNs). SNNs are considered the third generation of ANNs, powerful on the robust computation with a low computational cost. The neurons in SNNs ...
[ { "created": "Fri, 9 Oct 2020 08:42:13 GMT", "version": "v1" }, { "created": "Thu, 12 Nov 2020 06:06:27 GMT", "version": "v2" }, { "created": "Mon, 31 May 2021 13:50:56 GMT", "version": "v3" } ]
2021-06-01
[ [ "Zhang", "Tielin", "" ], [ "Jia", "Shuncheng", "" ], [ "Cheng", "Xiang", "" ], [ "Xu", "Bo", "" ] ]
Spiking Neural Networks (SNNs) contain more biologically realistic structures and biologically-inspired learning principles than those in standard Artificial Neural Networks (ANNs). SNNs are considered the third generation of ANNs, powerful on the robust computation with a low computational cost. The neurons in SNNs ar...
2202.11269
Qingsong Wen
Chaoli Zhang, Zhiqiang Zhou, Yingying Zhang, Linxiao Yang, Kai He, Qingsong Wen, Liang Sun
NetRCA: An Effective Network Fault Cause Localization Algorithm
Accepted by ICASSP 2022. NetRCA is the solution of the First Place of 2022 ICASSP AIOps Challenge. All authors are contributed equally, and Qingsong Wen is the team leader (Team Name: MindOps). The website of 2022 ICASSP AIOps Challenge is https://www.aiops.sribd.cn/home/introduction
null
null
null
cs.LG cs.AI cs.NI eess.SP stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Localizing the root cause of network faults is crucial to network operation and maintenance. However, due to the complicated network architectures and wireless environments, as well as limited labeled data, accurately localizing the true root cause is challenging. In this paper, we propose a novel algorithm named Net...
[ { "created": "Wed, 23 Feb 2022 02:03:35 GMT", "version": "v1" }, { "created": "Mon, 7 Mar 2022 00:15:13 GMT", "version": "v2" } ]
2022-03-08
[ [ "Zhang", "Chaoli", "" ], [ "Zhou", "Zhiqiang", "" ], [ "Zhang", "Yingying", "" ], [ "Yang", "Linxiao", "" ], [ "He", "Kai", "" ], [ "Wen", "Qingsong", "" ], [ "Sun", "Liang", "" ] ]
Localizing the root cause of network faults is crucial to network operation and maintenance. However, due to the complicated network architectures and wireless environments, as well as limited labeled data, accurately localizing the true root cause is challenging. In this paper, we propose a novel algorithm named NetRC...
1908.01441
Kazuo Misue
Kazuo Misue and Katsuya Akasaka
Graph Drawing with Morphing Partial Edges
Appears in the Proceedings of the 27th International Symposium on Graph Drawing and Network Visualization (GD 2019)
null
null
null
cs.DS cs.CG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A partial edge drawing (PED) of a graph is a variation of a node-link diagram. PED draws a link, which is a partial visual representation of an edge, and reduces visual clutter of the node-link diagram. However, more time is required to read a PED to infer undrawn parts. The authors propose a morphing edge drawing (M...
[ { "created": "Mon, 5 Aug 2019 01:56:23 GMT", "version": "v1" }, { "created": "Tue, 6 Aug 2019 05:06:19 GMT", "version": "v2" }, { "created": "Mon, 12 Aug 2019 12:16:00 GMT", "version": "v3" }, { "created": "Thu, 22 Aug 2019 05:28:23 GMT", "version": "v4" }, { "cre...
2019-10-03
[ [ "Misue", "Kazuo", "" ], [ "Akasaka", "Katsuya", "" ] ]
A partial edge drawing (PED) of a graph is a variation of a node-link diagram. PED draws a link, which is a partial visual representation of an edge, and reduces visual clutter of the node-link diagram. However, more time is required to read a PED to infer undrawn parts. The authors propose a morphing edge drawing (MED...
2106.15125
Yi-Fan Song
Yi-Fan Song, Zhang Zhang, Caifeng Shan, Liang Wang
Constructing Stronger and Faster Baselines for Skeleton-based Action Recognition
15 pages, 12 tables, 10 figures, Accepted by IEEE T-PAMI. arXiv admin note: text overlap with arXiv:2010.09978
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
One essential problem in skeleton-based action recognition is how to extract discriminative features over all skeleton joints. However, the complexity of the recent State-Of-The-Art (SOTA) models for this task tends to be exceedingly sophisticated and over-parameterized. The low efficiency in model training and infer...
[ { "created": "Tue, 29 Jun 2021 07:09:11 GMT", "version": "v1" }, { "created": "Thu, 3 Mar 2022 11:03:52 GMT", "version": "v2" } ]
2022-03-04
[ [ "Song", "Yi-Fan", "" ], [ "Zhang", "Zhang", "" ], [ "Shan", "Caifeng", "" ], [ "Wang", "Liang", "" ] ]
One essential problem in skeleton-based action recognition is how to extract discriminative features over all skeleton joints. However, the complexity of the recent State-Of-The-Art (SOTA) models for this task tends to be exceedingly sophisticated and over-parameterized. The low efficiency in model training and inferen...
2002.05966
Hao Cheng
Hao Cheng, Wentong Liao, Michael Ying Yang, Monika Sester, Bodo Rosenhahn
MCENET: Multi-Context Encoder Network for Homogeneous Agent Trajectory Prediction in Mixed Traffic
8 pages, 5 figures, code is available on https://github.com/haohao11/MCENET
null
null
null
cs.CV cs.CY cs.MA
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Trajectory prediction in urban mixed-traffic zones (a.k.a. shared spaces) is critical for many intelligent transportation systems, such as intent detection for autonomous driving. However, there are many challenges to predict the trajectories of heterogeneous road agents (pedestrians, cyclists and vehicles) at a micr...
[ { "created": "Fri, 14 Feb 2020 11:04:41 GMT", "version": "v1" }, { "created": "Mon, 17 Feb 2020 15:53:02 GMT", "version": "v2" }, { "created": "Tue, 3 Mar 2020 13:39:05 GMT", "version": "v3" }, { "created": "Sun, 5 Apr 2020 12:08:51 GMT", "version": "v4" }, { "cre...
2020-06-24
[ [ "Cheng", "Hao", "" ], [ "Liao", "Wentong", "" ], [ "Yang", "Michael Ying", "" ], [ "Sester", "Monika", "" ], [ "Rosenhahn", "Bodo", "" ] ]
Trajectory prediction in urban mixed-traffic zones (a.k.a. shared spaces) is critical for many intelligent transportation systems, such as intent detection for autonomous driving. However, there are many challenges to predict the trajectories of heterogeneous road agents (pedestrians, cyclists and vehicles) at a micros...
2206.11436
Siamak Ghodsi
Siamak Ghodsi, Harith Alani, and Eirini Ntoutsi
Context matters for fairness -- a case study on the effect of spatial distribution shifts
null
null
null
null
cs.LG cs.AI
http://creativecommons.org/licenses/by/4.0/
With the ever growing involvement of data-driven AI-based decision making technologies in our daily social lives, the fairness of these systems is becoming a crucial phenomenon. However, an important and often challenging aspect in utilizing such systems is to distinguish validity for the range of their application e...
[ { "created": "Thu, 23 Jun 2022 01:09:46 GMT", "version": "v1" }, { "created": "Fri, 24 Jun 2022 21:09:45 GMT", "version": "v2" } ]
2022-06-28
[ [ "Ghodsi", "Siamak", "" ], [ "Alani", "Harith", "" ], [ "Ntoutsi", "Eirini", "" ] ]
With the ever growing involvement of data-driven AI-based decision making technologies in our daily social lives, the fairness of these systems is becoming a crucial phenomenon. However, an important and often challenging aspect in utilizing such systems is to distinguish validity for the range of their application esp...
2210.12067
Ramin Hasani
Noel Loo, Ramin Hasani, Alexander Amini, Daniela Rus
Efficient Dataset Distillation Using Random Feature Approximation
Accepted to the Conference on the Advances in Neural Information Processing Systems (NeurIPS) 2022
null
null
null
cs.LG cs.AI cs.NE stat.ML
http://creativecommons.org/licenses/by-nc-sa/4.0/
Dataset distillation compresses large datasets into smaller synthetic coresets which retain performance with the aim of reducing the storage and computational burden of processing the entire dataset. Today's best-performing algorithm, \textit{Kernel Inducing Points} (KIP), which makes use of the correspondence betwee...
[ { "created": "Fri, 21 Oct 2022 15:56:13 GMT", "version": "v1" } ]
2022-10-24
[ [ "Loo", "Noel", "" ], [ "Hasani", "Ramin", "" ], [ "Amini", "Alexander", "" ], [ "Rus", "Daniela", "" ] ]
Dataset distillation compresses large datasets into smaller synthetic coresets which retain performance with the aim of reducing the storage and computational burden of processing the entire dataset. Today's best-performing algorithm, \textit{Kernel Inducing Points} (KIP), which makes use of the correspondence between ...
2112.10038
Peng Xu Mr
Peng Xu
Android-COCO: Android Malware Detection with Graph Neural Network for Byte- and Native-Code
10 pages, 3 figures, 3 tables
null
null
null
cs.CR
http://creativecommons.org/licenses/by-nc-sa/4.0/
With the popularity of Android growing exponentially, the amount of malware has significantly exploded. It is arguably one of the most viral problems on mobile platforms. Recently, various approaches have been introduced to detect Android malware, the majority of these are either based on the Manifest File features o...
[ { "created": "Sun, 19 Dec 2021 01:46:01 GMT", "version": "v1" }, { "created": "Mon, 24 Jan 2022 14:11:00 GMT", "version": "v2" } ]
2022-01-25
[ [ "Xu", "Peng", "" ] ]
With the popularity of Android growing exponentially, the amount of malware has significantly exploded. It is arguably one of the most viral problems on mobile platforms. Recently, various approaches have been introduced to detect Android malware, the majority of these are either based on the Manifest File features or ...
0911.1765
Ion Mandoiu
Justin Kennedy, Ion I. Mandoiu, and Bogdan Pasaniuc
GEDI: Scalable Algorithms for Genotype Error Detection and Imputation
null
null
null
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Genome-wide association studies generate very large datasets that require scalable analysis algorithms. In this report we describe the GEDI software package, which implements efficient algorithms for performing several common tasks in the analysis of population genotype data, including genotype error detection and co...
[ { "created": "Mon, 9 Nov 2009 23:35:41 GMT", "version": "v1" } ]
2016-09-08
[ [ "Kennedy", "Justin", "" ], [ "Mandoiu", "Ion I.", "" ], [ "Pasaniuc", "Bogdan", "" ] ]
Genome-wide association studies generate very large datasets that require scalable analysis algorithms. In this report we describe the GEDI software package, which implements efficient algorithms for performing several common tasks in the analysis of population genotype data, including genotype error detection and corr...
2210.05148
Kin Wai Cheuk
Kin Wai Cheuk, Ryosuke Sawata, Toshimitsu Uesaka, Naoki Murata, Naoya Takahashi, Shusuke Takahashi, Dorien Herremans, Yuki Mitsufuji
DiffRoll: Diffusion-based Generative Music Transcription with Unsupervised Pretraining Capability
null
Proceedings of ICASSP - IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 1-5. IEEE, 2023
null
null
cs.SD cs.AI cs.LG eess.AS
http://creativecommons.org/licenses/by/4.0/
In this paper we propose a novel generative approach, DiffRoll, to tackle automatic music transcription (AMT). Instead of treating AMT as a discriminative task in which the model is trained to convert spectrograms into piano rolls, we think of it as a conditional generative task where we train our model to generate r...
[ { "created": "Tue, 11 Oct 2022 05:02:11 GMT", "version": "v1" }, { "created": "Thu, 20 Oct 2022 05:47:43 GMT", "version": "v2" } ]
2024-06-03
[ [ "Cheuk", "Kin Wai", "" ], [ "Sawata", "Ryosuke", "" ], [ "Uesaka", "Toshimitsu", "" ], [ "Murata", "Naoki", "" ], [ "Takahashi", "Naoya", "" ], [ "Takahashi", "Shusuke", "" ], [ "Herremans", "Dorien", "" ...
In this paper we propose a novel generative approach, DiffRoll, to tackle automatic music transcription (AMT). Instead of treating AMT as a discriminative task in which the model is trained to convert spectrograms into piano rolls, we think of it as a conditional generative task where we train our model to generate rea...
2305.13723
Yunyi Zhang
Yunyi Zhang, Minhao Jiang, Yu Meng, Yu Zhang, Jiawei Han
PIEClass: Weakly-Supervised Text Classification with Prompting and Noise-Robust Iterative Ensemble Training
Accepted to EMNLP 2023 Main Conference
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
Weakly-supervised text classification trains a classifier using the label name of each target class as the only supervision, which largely reduces human annotation efforts. Most existing methods first use the label names as static keyword-based features to generate pseudo labels, which are then used for final classif...
[ { "created": "Tue, 23 May 2023 06:19:14 GMT", "version": "v1" }, { "created": "Fri, 20 Oct 2023 15:14:34 GMT", "version": "v2" } ]
2023-10-23
[ [ "Zhang", "Yunyi", "" ], [ "Jiang", "Minhao", "" ], [ "Meng", "Yu", "" ], [ "Zhang", "Yu", "" ], [ "Han", "Jiawei", "" ] ]
Weakly-supervised text classification trains a classifier using the label name of each target class as the only supervision, which largely reduces human annotation efforts. Most existing methods first use the label names as static keyword-based features to generate pseudo labels, which are then used for final classifie...
2302.04225
Panagiotis Mpakos
Panagiotis Mpakos, Dimitrios Galanopoulos, Petros Anastasiadis, Nikela Papadopoulou, Nectarios Koziris, Georgios Goumas
Feature-based SpMV Performance Analysis on Contemporary Devices
to appear at IPDPS'23
null
null
null
cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The SpMV kernel is characterized by high performance variation per input matrix and computing platform. While GPUs were considered State-of-the-Art for SpMV, with the emergence of advanced multicore CPUs and low-power FPGA accelerators, we need to revisit its performance and energy efficiency. This paper provides a h...
[ { "created": "Wed, 8 Feb 2023 17:51:58 GMT", "version": "v1" } ]
2023-02-09
[ [ "Mpakos", "Panagiotis", "" ], [ "Galanopoulos", "Dimitrios", "" ], [ "Anastasiadis", "Petros", "" ], [ "Papadopoulou", "Nikela", "" ], [ "Koziris", "Nectarios", "" ], [ "Goumas", "Georgios", "" ] ]
The SpMV kernel is characterized by high performance variation per input matrix and computing platform. While GPUs were considered State-of-the-Art for SpMV, with the emergence of advanced multicore CPUs and low-power FPGA accelerators, we need to revisit its performance and energy efficiency. This paper provides a hig...