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2305.03296
Weixiang Zhao
Weixiang Zhao, Yanyan Zhao, Shilong Wang, Bing Qin
TransESC: Smoothing Emotional Support Conversation via Turn-Level State Transition
Accepted to Findings of ACL 2023
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Emotion Support Conversation (ESC) is an emerging and challenging task with the goal of reducing the emotional distress of people. Previous attempts fail to maintain smooth transitions between utterances in ESC because they ignore to grasp the fine-grained transition information at each dialogue turn. To solve this p...
[ { "created": "Fri, 5 May 2023 05:50:26 GMT", "version": "v1" } ]
2023-05-08
[ [ "Zhao", "Weixiang", "" ], [ "Zhao", "Yanyan", "" ], [ "Wang", "Shilong", "" ], [ "Qin", "Bing", "" ] ]
Emotion Support Conversation (ESC) is an emerging and challenging task with the goal of reducing the emotional distress of people. Previous attempts fail to maintain smooth transitions between utterances in ESC because they ignore to grasp the fine-grained transition information at each dialogue turn. To solve this pro...
2205.12475
Xiangyang Li
Xiangyang Li, Xiang Long, Yu Xia, Sujian Li
Low Resource Style Transfer via Domain Adaptive Meta Learning
Accept in NAACL 2022(oral)
null
null
null
cs.CL cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Text style transfer (TST) without parallel data has achieved some practical success. However, most of the existing unsupervised text style transfer methods suffer from (i) requiring massive amounts of non-parallel data to guide transferring different text styles. (ii) colossal performance degradation when fine-tuning...
[ { "created": "Wed, 25 May 2022 03:58:24 GMT", "version": "v1" } ]
2022-05-26
[ [ "Li", "Xiangyang", "" ], [ "Long", "Xiang", "" ], [ "Xia", "Yu", "" ], [ "Li", "Sujian", "" ] ]
Text style transfer (TST) without parallel data has achieved some practical success. However, most of the existing unsupervised text style transfer methods suffer from (i) requiring massive amounts of non-parallel data to guide transferring different text styles. (ii) colossal performance degradation when fine-tuning t...
2309.06061
Ehsan Toreini
Ehsan Toreini and Maryam Mehrnezhad and Aad van Moorsel
Verifiable Fairness: Privacy-preserving Computation of Fairness for Machine Learning Systems
accepted in International Workshop on Private, Secure, and Trustworthy AI (PriST-AI), ESORICS'23 workshop
null
null
null
cs.CR cs.CY cs.LG
http://creativecommons.org/licenses/by/4.0/
Fair machine learning is a thriving and vibrant research topic. In this paper, we propose Fairness as a Service (FaaS), a secure, verifiable and privacy-preserving protocol to computes and verify the fairness of any machine learning (ML) model. In the deisgn of FaaS, the data and outcomes are represented through cryp...
[ { "created": "Tue, 12 Sep 2023 09:00:03 GMT", "version": "v1" } ]
2023-09-13
[ [ "Toreini", "Ehsan", "" ], [ "Mehrnezhad", "Maryam", "" ], [ "van Moorsel", "Aad", "" ] ]
Fair machine learning is a thriving and vibrant research topic. In this paper, we propose Fairness as a Service (FaaS), a secure, verifiable and privacy-preserving protocol to computes and verify the fairness of any machine learning (ML) model. In the deisgn of FaaS, the data and outcomes are represented through crypto...
2101.10074
Setareh Maghsudi
Setareh Maghsudi, Andrew Lan, Jie Xu, and Mihaela van der Schaar
Personalized Education in the AI Era: What to Expect Next?
null
null
10.1109/MSP.2021.3055032
null
cs.CY cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The objective of personalized learning is to design an effective knowledge acquisition track that matches the learner's strengths and bypasses her weaknesses to ultimately meet her desired goal. This concept emerged several years ago and is being adopted by a rapidly-growing number of educational institutions around ...
[ { "created": "Tue, 19 Jan 2021 12:23:32 GMT", "version": "v1" } ]
2021-02-16
[ [ "Maghsudi", "Setareh", "" ], [ "Lan", "Andrew", "" ], [ "Xu", "Jie", "" ], [ "van der Schaar", "Mihaela", "" ] ]
The objective of personalized learning is to design an effective knowledge acquisition track that matches the learner's strengths and bypasses her weaknesses to ultimately meet her desired goal. This concept emerged several years ago and is being adopted by a rapidly-growing number of educational institutions around th...
1707.06685
Dylan McDermott
Ohad Kammar and Dylan McDermott
A monadic solution to the Cartwright-Felleisen-Wadler conjecture
Talk proposal uploaded for archival purposes
null
null
null
cs.PL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Given a programming language, can we give a monadic denotational semantics that is stable under language extension? Models containing only a single monad are not stable. Models based on type-and-effect systems, in which there is a monad for every set of operations in the language, are. Cartwright and Felleisen, and W...
[ { "created": "Thu, 20 Jul 2017 19:26:41 GMT", "version": "v1" } ]
2017-07-24
[ [ "Kammar", "Ohad", "" ], [ "McDermott", "Dylan", "" ] ]
Given a programming language, can we give a monadic denotational semantics that is stable under language extension? Models containing only a single monad are not stable. Models based on type-and-effect systems, in which there is a monad for every set of operations in the language, are. Cartwright and Felleisen, and Wad...
1901.07216
Bing Lin
Bing Lin, Fangning Zhu, Jianshan Zhang, Jiaqing Chen, Xing Chen, Neal N. Xiong, Jaime Lloret Mauri
A Time-driven Data Placement Strategy for a Scientific Workflow Combining Edge Computing and Cloud Computing
null
null
null
null
cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Compared to traditional distributed computing environments such as grids, cloud computing provides a more cost-effective way to deploy scientific workflows. Each task of a scientific workflow requires several large datasets that are located in different datacenters from the cloud computing environment, resulting in s...
[ { "created": "Tue, 22 Jan 2019 09:04:48 GMT", "version": "v1" }, { "created": "Thu, 24 Jan 2019 06:49:42 GMT", "version": "v2" } ]
2019-01-25
[ [ "Lin", "Bing", "" ], [ "Zhu", "Fangning", "" ], [ "Zhang", "Jianshan", "" ], [ "Chen", "Jiaqing", "" ], [ "Chen", "Xing", "" ], [ "Xiong", "Neal N.", "" ], [ "Mauri", "Jaime Lloret", "" ] ]
Compared to traditional distributed computing environments such as grids, cloud computing provides a more cost-effective way to deploy scientific workflows. Each task of a scientific workflow requires several large datasets that are located in different datacenters from the cloud computing environment, resulting in ser...
2306.17054
Hanhan Zhou
Chang-Lin Chen, Hanhan Zhou, Jiayu Chen, Mohammad Pedramfar, Vaneet Aggarwal, Tian Lan, Zheqing Zhu, Chi Zhou, Tim Gasser, Pol Mauri Ruiz, Vijay Menon, Neeraj Kumar, and Hongbo Dong
Two-tiered Online Optimization of Region-wide Datacenter Resource Allocation via Deep Reinforcement Learning
null
null
null
null
cs.NI
http://creativecommons.org/licenses/by/4.0/
This paper addresses the important need for advanced techniques in continuously allocating workloads on shared infrastructures in data centers, a problem arising due to the growing popularity and scale of cloud computing. It particularly emphasizes the scarcity of research ensuring guaranteed capacity in capacity res...
[ { "created": "Thu, 29 Jun 2023 16:00:06 GMT", "version": "v1" } ]
2023-06-30
[ [ "Chen", "Chang-Lin", "" ], [ "Zhou", "Hanhan", "" ], [ "Chen", "Jiayu", "" ], [ "Pedramfar", "Mohammad", "" ], [ "Aggarwal", "Vaneet", "" ], [ "Lan", "Tian", "" ], [ "Zhu", "Zheqing", "" ], [ "Zhou"...
This paper addresses the important need for advanced techniques in continuously allocating workloads on shared infrastructures in data centers, a problem arising due to the growing popularity and scale of cloud computing. It particularly emphasizes the scarcity of research ensuring guaranteed capacity in capacity reser...
2103.01933
Tianmin Shu
Aviv Netanyahu, Tianmin Shu, Boris Katz, Andrei Barbu, Joshua B. Tenenbaum
PHASE: PHysically-grounded Abstract Social Events for Machine Social Perception
The first two authors contributed equally; AAAI 2021; 13 pages, 7 figures; Project page: https://www.tshu.io/PHASE
null
null
null
cs.AI cs.CV cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The ability to perceive and reason about social interactions in the context of physical environments is core to human social intelligence and human-machine cooperation. However, no prior dataset or benchmark has systematically evaluated physically grounded perception of complex social interactions that go beyond shor...
[ { "created": "Tue, 2 Mar 2021 18:44:57 GMT", "version": "v1" }, { "created": "Fri, 19 Mar 2021 20:13:29 GMT", "version": "v2" } ]
2021-03-23
[ [ "Netanyahu", "Aviv", "" ], [ "Shu", "Tianmin", "" ], [ "Katz", "Boris", "" ], [ "Barbu", "Andrei", "" ], [ "Tenenbaum", "Joshua B.", "" ] ]
The ability to perceive and reason about social interactions in the context of physical environments is core to human social intelligence and human-machine cooperation. However, no prior dataset or benchmark has systematically evaluated physically grounded perception of complex social interactions that go beyond short ...
2110.15538
Dang Nguyen
Dang Nguyen and Trang Nguyen and Khai Nguyen and Dinh Phung and Hung Bui and Nhat Ho
On Cross-Layer Alignment for Model Fusion of Heterogeneous Neural Networks
Accepted to ICASSP 2023, 30 pages, 4 figures, 21 tables
null
null
null
cs.LG cs.CV
http://creativecommons.org/licenses/by/4.0/
Layer-wise model fusion via optimal transport, named OTFusion, applies soft neuron association for unifying different pre-trained networks to save computational resources. While enjoying its success, OTFusion requires the input networks to have the same number of layers. To address this issue, we propose a novel mode...
[ { "created": "Fri, 29 Oct 2021 05:02:23 GMT", "version": "v1" }, { "created": "Sun, 27 Feb 2022 05:18:54 GMT", "version": "v2" }, { "created": "Mon, 20 Feb 2023 04:41:24 GMT", "version": "v3" } ]
2023-02-21
[ [ "Nguyen", "Dang", "" ], [ "Nguyen", "Trang", "" ], [ "Nguyen", "Khai", "" ], [ "Phung", "Dinh", "" ], [ "Bui", "Hung", "" ], [ "Ho", "Nhat", "" ] ]
Layer-wise model fusion via optimal transport, named OTFusion, applies soft neuron association for unifying different pre-trained networks to save computational resources. While enjoying its success, OTFusion requires the input networks to have the same number of layers. To address this issue, we propose a novel model ...
2004.02554
Haris Aziz
Haris Aziz
Simultaneously Achieving Ex-ante and Ex-post Fairness
null
null
null
null
cs.GT cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present a polynomial-time algorithm that computes an ex-ante envy-free lottery over envy-free up to one item (EF1) deterministic allocations. It has the following advantages over a recently proposed algorithm: it does not rely on the linear programming machinery including separation oracles; it is SD-efficient (bo...
[ { "created": "Mon, 6 Apr 2020 11:05:32 GMT", "version": "v1" }, { "created": "Tue, 7 Apr 2020 02:18:25 GMT", "version": "v2" }, { "created": "Sun, 28 Jun 2020 23:34:53 GMT", "version": "v3" } ]
2020-06-30
[ [ "Aziz", "Haris", "" ] ]
We present a polynomial-time algorithm that computes an ex-ante envy-free lottery over envy-free up to one item (EF1) deterministic allocations. It has the following advantages over a recently proposed algorithm: it does not rely on the linear programming machinery including separation oracles; it is SD-efficient (both...
2103.00331
Daniela Kuinchtner
Daniela Kuinchtner, Afonso Sales, Felipe Meneguzzi
CP-MDP: A CANDECOMP-PARAFAC Decomposition Approach to Solve a Markov Decision Process Multidimensional Problem
null
null
null
null
cs.AI
http://creativecommons.org/licenses/by/4.0/
Markov Decision Process (MDP) is the underlying model for optimal planning for decision-theoretic agents in stochastic environments. Although much research focuses on solving MDP problems both in tabular form or using factored representations, none focused on tensor decomposition methods. Solving MDPs using tensor al...
[ { "created": "Sat, 27 Feb 2021 21:33:19 GMT", "version": "v1" } ]
2021-03-02
[ [ "Kuinchtner", "Daniela", "" ], [ "Sales", "Afonso", "" ], [ "Meneguzzi", "Felipe", "" ] ]
Markov Decision Process (MDP) is the underlying model for optimal planning for decision-theoretic agents in stochastic environments. Although much research focuses on solving MDP problems both in tabular form or using factored representations, none focused on tensor decomposition methods. Solving MDPs using tensor alge...
2308.01088
Gianluca Amprimo
Gianluca Amprimo, Giulia Masi, Giuseppe Pettiti, Gabriella Olmo, Lorenzo Priano and Claudia Ferraris
Hand tracking for clinical applications: validation of the Google MediaPipe Hand (GMH) and the depth-enhanced GMH-D frameworks
null
null
null
null
cs.CV cs.AI
http://creativecommons.org/licenses/by/4.0/
Accurate 3D tracking of hand and fingers movements poses significant challenges in computer vision. The potential applications span across multiple domains, including human-computer interaction, virtual reality, industry, and medicine. While gesture recognition has achieved remarkable accuracy, quantifying fine movem...
[ { "created": "Wed, 2 Aug 2023 11:44:49 GMT", "version": "v1" } ]
2023-08-03
[ [ "Amprimo", "Gianluca", "" ], [ "Masi", "Giulia", "" ], [ "Pettiti", "Giuseppe", "" ], [ "Olmo", "Gabriella", "" ], [ "Priano", "Lorenzo", "" ], [ "Ferraris", "Claudia", "" ] ]
Accurate 3D tracking of hand and fingers movements poses significant challenges in computer vision. The potential applications span across multiple domains, including human-computer interaction, virtual reality, industry, and medicine. While gesture recognition has achieved remarkable accuracy, quantifying fine movemen...
2404.15522
Mihir Parmar
Mihir Parmar, Nisarg Patel, Neeraj Varshney, Mutsumi Nakamura, Man Luo, Santosh Mashetty, Arindam Mitra, Chitta Baral
LogicBench: Towards Systematic Evaluation of Logical Reasoning Ability of Large Language Models
Accepted at ACL(Main) 2024 | First version available @ https://openreview.net/forum?id=7NR2ZVzZxx
null
null
null
cs.CL cs.AI
http://creativecommons.org/licenses/by/4.0/
Recently developed large language models (LLMs) have been shown to perform remarkably well on a wide range of language understanding tasks. But, can they really "reason" over the natural language? This question has been receiving significant research attention and many reasoning skills such as commonsense, numerical,...
[ { "created": "Tue, 23 Apr 2024 21:08:49 GMT", "version": "v1" }, { "created": "Thu, 6 Jun 2024 08:15:54 GMT", "version": "v2" } ]
2024-06-07
[ [ "Parmar", "Mihir", "" ], [ "Patel", "Nisarg", "" ], [ "Varshney", "Neeraj", "" ], [ "Nakamura", "Mutsumi", "" ], [ "Luo", "Man", "" ], [ "Mashetty", "Santosh", "" ], [ "Mitra", "Arindam", "" ], [ "B...
Recently developed large language models (LLMs) have been shown to perform remarkably well on a wide range of language understanding tasks. But, can they really "reason" over the natural language? This question has been receiving significant research attention and many reasoning skills such as commonsense, numerical, a...
2106.10563
Sarah Fakhoury
Sarah Fakhoury, Devjeet Roy, Harry Pines, Tyler Cleveland, Cole Peterson, Venera Arnaoudova, Bonita Sharif, Jonathan Maletic
gazel: Supporting Source Code Edits in Eye-Tracking Studies
4 pages, 2 figures
International Conference on Software Engineering (ICSE) 2021
10.1109/ICSE-Companion52605.2021.00038
null
cs.SE cs.HC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Eye tracking tools are used in software engineering research to study various software development activities. However, a major limitation of these tools is their inability to track gaze data for activities that involve source code editing. We present a novel solution to support eye tracking experiments for tasks inv...
[ { "created": "Sat, 19 Jun 2021 19:37:20 GMT", "version": "v1" } ]
2021-06-22
[ [ "Fakhoury", "Sarah", "" ], [ "Roy", "Devjeet", "" ], [ "Pines", "Harry", "" ], [ "Cleveland", "Tyler", "" ], [ "Peterson", "Cole", "" ], [ "Arnaoudova", "Venera", "" ], [ "Sharif", "Bonita", "" ], [ ...
Eye tracking tools are used in software engineering research to study various software development activities. However, a major limitation of these tools is their inability to track gaze data for activities that involve source code editing. We present a novel solution to support eye tracking experiments for tasks invol...
1912.06126
Kyle Genova
Kyle Genova, Forrester Cole, Avneesh Sud, Aaron Sarna, Thomas Funkhouser
Local Deep Implicit Functions for 3D Shape
Camera ready version for CVPR 2020 Oral. Prior to review, this paper was referred to as DSIF, "Deep Structured Implicit Functions." 11 pages, 9 figures. Project video at https://youtu.be/3RAITzNWVJs
null
null
null
cs.CV cs.GR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The goal of this project is to learn a 3D shape representation that enables accurate surface reconstruction, compact storage, efficient computation, consistency for similar shapes, generalization across diverse shape categories, and inference from depth camera observations. Towards this end, we introduce Local Deep I...
[ { "created": "Thu, 12 Dec 2019 18:50:46 GMT", "version": "v1" }, { "created": "Fri, 12 Jun 2020 03:26:47 GMT", "version": "v2" } ]
2020-06-15
[ [ "Genova", "Kyle", "" ], [ "Cole", "Forrester", "" ], [ "Sud", "Avneesh", "" ], [ "Sarna", "Aaron", "" ], [ "Funkhouser", "Thomas", "" ] ]
The goal of this project is to learn a 3D shape representation that enables accurate surface reconstruction, compact storage, efficient computation, consistency for similar shapes, generalization across diverse shape categories, and inference from depth camera observations. Towards this end, we introduce Local Deep Imp...
1909.00136
Junhui Li
Jie Zhu, Junhui Li, Muhua Zhu, Longhua Qian, Min Zhang, Guodong Zhou
Modeling Graph Structure in Transformer for Better AMR-to-Text Generation
Accepted by EMNLP 2019
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recent studies on AMR-to-text generation often formalize the task as a sequence-to-sequence (seq2seq) learning problem by converting an Abstract Meaning Representation (AMR) graph into a word sequence. Graph structures are further modeled into the seq2seq framework in order to utilize the structural information in th...
[ { "created": "Sat, 31 Aug 2019 05:45:20 GMT", "version": "v1" } ]
2019-09-04
[ [ "Zhu", "Jie", "" ], [ "Li", "Junhui", "" ], [ "Zhu", "Muhua", "" ], [ "Qian", "Longhua", "" ], [ "Zhang", "Min", "" ], [ "Zhou", "Guodong", "" ] ]
Recent studies on AMR-to-text generation often formalize the task as a sequence-to-sequence (seq2seq) learning problem by converting an Abstract Meaning Representation (AMR) graph into a word sequence. Graph structures are further modeled into the seq2seq framework in order to utilize the structural information in the ...
2306.06747
Yuanyuan Yuan
Yuanyuan Yuan, Shuai Wang, and Zhendong Su
Precise and Generalized Robustness Certification for Neural Networks
The extended version of a paper to appear in the Proceedings of the 32nd USENIX Security Symposium, 2023, (USENIX Security '23), 19 pages
null
null
null
cs.CR cs.CV cs.LG
http://creativecommons.org/licenses/by/4.0/
The objective of neural network (NN) robustness certification is to determine if a NN changes its predictions when mutations are made to its inputs. While most certification research studies pixel-level or a few geometrical-level and blurring operations over images, this paper proposes a novel framework, GCERT, which...
[ { "created": "Sun, 11 Jun 2023 19:00:41 GMT", "version": "v1" } ]
2023-06-13
[ [ "Yuan", "Yuanyuan", "" ], [ "Wang", "Shuai", "" ], [ "Su", "Zhendong", "" ] ]
The objective of neural network (NN) robustness certification is to determine if a NN changes its predictions when mutations are made to its inputs. While most certification research studies pixel-level or a few geometrical-level and blurring operations over images, this paper proposes a novel framework, GCERT, which c...
2103.14051
Hadi Jamali-Rad
Attila Szabo, Hadi Jamali-Rad, Siva-Datta Mannava
Tilted Cross Entropy (TCE): Promoting Fairness in Semantic Segmentation
10 pages
null
null
null
cs.CV cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Traditional empirical risk minimization (ERM) for semantic segmentation can disproportionately advantage or disadvantage certain target classes in favor of an (unfair but) improved overall performance. Inspired by the recently introduced tilted ERM (TERM), we propose tilted cross-entropy (TCE) loss and adapt it to th...
[ { "created": "Thu, 25 Mar 2021 18:00:50 GMT", "version": "v1" } ]
2021-03-29
[ [ "Szabo", "Attila", "" ], [ "Jamali-Rad", "Hadi", "" ], [ "Mannava", "Siva-Datta", "" ] ]
Traditional empirical risk minimization (ERM) for semantic segmentation can disproportionately advantage or disadvantage certain target classes in favor of an (unfair but) improved overall performance. Inspired by the recently introduced tilted ERM (TERM), we propose tilted cross-entropy (TCE) loss and adapt it to the ...
1604.04699
Medhat Elsayed Mr.
Medhat H. M. Elsayed and Amr Mohamed
Distributed interference management using Q-Learning in Cognitive Femtocell networks: New USRP-based Implementation
null
null
null
null
cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Femtocell networks have become a promising solution in supporting high data rates for 5G systems, where cell densification is performed using the small femtocells. However, femtocell networks have many challenges. One of the major challenges of femtocell networks is the interference management problem, where deployme...
[ { "created": "Sat, 16 Apr 2016 06:25:21 GMT", "version": "v1" } ]
2016-04-19
[ [ "Elsayed", "Medhat H. M.", "" ], [ "Mohamed", "Amr", "" ] ]
Femtocell networks have become a promising solution in supporting high data rates for 5G systems, where cell densification is performed using the small femtocells. However, femtocell networks have many challenges. One of the major challenges of femtocell networks is the interference management problem, where deployment...
2104.04676
Xutan Peng
Xutan Peng, Guanyi Chen, Chenghua Lin, Mark Stevenson
Highly Efficient Knowledge Graph Embedding Learning with Orthogonal Procrustes Analysis
To appear at NAACL 2021
NAACL-HLT 2021
10.18653/v1/2021.naacl-main.187
null
cs.LG cs.AI cs.CL stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Knowledge Graph Embeddings (KGEs) have been intensively explored in recent years due to their promise for a wide range of applications. However, existing studies focus on improving the final model performance without acknowledging the computational cost of the proposed approaches, in terms of execution time and envir...
[ { "created": "Sat, 10 Apr 2021 03:55:45 GMT", "version": "v1" }, { "created": "Sat, 17 Apr 2021 12:17:05 GMT", "version": "v2" } ]
2022-01-25
[ [ "Peng", "Xutan", "" ], [ "Chen", "Guanyi", "" ], [ "Lin", "Chenghua", "" ], [ "Stevenson", "Mark", "" ] ]
Knowledge Graph Embeddings (KGEs) have been intensively explored in recent years due to their promise for a wide range of applications. However, existing studies focus on improving the final model performance without acknowledging the computational cost of the proposed approaches, in terms of execution time and environ...
1602.07349
Tomaso Aste
Wolfram Barfuss, Guido Previde Massara, T. Di Matteo, Tomaso Aste
Parsimonious modeling with Information Filtering Networks
17 pages, 10 figures, 3 tables
Phys. Rev. E 94, 062306 (2016)
10.1103/PhysRevE.94.062306
null
cs.IT math.IT stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We introduce a methodology to construct parsimonious probabilistic models. This method makes use of Information Filtering Networks to produce a robust estimate of the global sparse inverse covariance from a simple sum of local inverse covariances computed on small sub-parts of the network. Being based on local and lo...
[ { "created": "Tue, 23 Feb 2016 23:03:56 GMT", "version": "v1" }, { "created": "Thu, 30 Jun 2016 15:11:14 GMT", "version": "v2" }, { "created": "Wed, 23 Nov 2016 15:32:05 GMT", "version": "v3" } ]
2017-02-21
[ [ "Barfuss", "Wolfram", "" ], [ "Massara", "Guido Previde", "" ], [ "Di Matteo", "T.", "" ], [ "Aste", "Tomaso", "" ] ]
We introduce a methodology to construct parsimonious probabilistic models. This method makes use of Information Filtering Networks to produce a robust estimate of the global sparse inverse covariance from a simple sum of local inverse covariances computed on small sub-parts of the network. Being based on local and low-...
2403.16535
Lu Shi
Zifan Wang, Yufei Jia, Lu Shi, Haoyu Wang, Haizhou Zhao, Xueyang Li, Jinni Zhou, Jun Ma, and Guyue Zhou
Arm-Constrained Curriculum Learning for Loco-Manipulation of the Wheel-Legged Robot
null
null
null
null
cs.RO
http://creativecommons.org/licenses/by/4.0/
Incorporating a robotic manipulator into a wheel-legged robot enhances its agility and expands its potential for practical applications. However, the presence of potential instability and uncertainties presents additional challenges for control objectives. In this paper, we introduce an arm-constrained curriculum lea...
[ { "created": "Mon, 25 Mar 2024 08:26:20 GMT", "version": "v1" }, { "created": "Thu, 28 Mar 2024 09:30:23 GMT", "version": "v2" } ]
2024-03-29
[ [ "Wang", "Zifan", "" ], [ "Jia", "Yufei", "" ], [ "Shi", "Lu", "" ], [ "Wang", "Haoyu", "" ], [ "Zhao", "Haizhou", "" ], [ "Li", "Xueyang", "" ], [ "Zhou", "Jinni", "" ], [ "Ma", "Jun", "" ...
Incorporating a robotic manipulator into a wheel-legged robot enhances its agility and expands its potential for practical applications. However, the presence of potential instability and uncertainties presents additional challenges for control objectives. In this paper, we introduce an arm-constrained curriculum learn...
1710.07480
Gabriel Eilertsen
Gabriel Eilertsen, Joel Kronander, Gyorgy Denes, Rafa{\l} K. Mantiuk, Jonas Unger
HDR image reconstruction from a single exposure using deep CNNs
15 pages, 19 figures, Siggraph Asia 2017. Project webpage located at http://hdrv.org/hdrcnn/ where paper with high quality images is available, as well as supplementary material (document, images, video and source code)
ACM Trans. Graph. 36, 6, Article 178 (2017)
10.1145/3130800.3130816
null
cs.CV cs.GR cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Camera sensors can only capture a limited range of luminance simultaneously, and in order to create high dynamic range (HDR) images a set of different exposures are typically combined. In this paper we address the problem of predicting information that have been lost in saturated image areas, in order to enable HDR r...
[ { "created": "Fri, 20 Oct 2017 10:48:22 GMT", "version": "v1" } ]
2017-11-28
[ [ "Eilertsen", "Gabriel", "" ], [ "Kronander", "Joel", "" ], [ "Denes", "Gyorgy", "" ], [ "Mantiuk", "Rafał K.", "" ], [ "Unger", "Jonas", "" ] ]
Camera sensors can only capture a limited range of luminance simultaneously, and in order to create high dynamic range (HDR) images a set of different exposures are typically combined. In this paper we address the problem of predicting information that have been lost in saturated image areas, in order to enable HDR rec...
1705.08314
Roberto Henschel
Roberto Henschel, Laura Leal-Taix\'e, Daniel Cremers, Bodo Rosenhahn
Fusion of Head and Full-Body Detectors for Multi-Object Tracking
10 pages, 4 figures; Winner of the MOT17 challenge; CVPRW 2018
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In order to track all persons in a scene, the tracking-by-detection paradigm has proven to be a very effective approach. Yet, relying solely on a single detector is also a major limitation, as useful image information might be ignored. Consequently, this work demonstrates how to fuse two detectors into a tracking sys...
[ { "created": "Tue, 23 May 2017 14:29:53 GMT", "version": "v1" }, { "created": "Wed, 26 Jul 2017 10:02:18 GMT", "version": "v2" }, { "created": "Fri, 8 Sep 2017 19:04:02 GMT", "version": "v3" }, { "created": "Tue, 24 Apr 2018 09:24:49 GMT", "version": "v4" } ]
2018-04-25
[ [ "Henschel", "Roberto", "" ], [ "Leal-Taixé", "Laura", "" ], [ "Cremers", "Daniel", "" ], [ "Rosenhahn", "Bodo", "" ] ]
In order to track all persons in a scene, the tracking-by-detection paradigm has proven to be a very effective approach. Yet, relying solely on a single detector is also a major limitation, as useful image information might be ignored. Consequently, this work demonstrates how to fuse two detectors into a tracking syste...
1803.04617
Amin Banitalebi-Dehkordi
Amin Banitalebi, Said Nader-Esfahani, and Alireza Nasiri Avanaki
Robust LSB Watermarking Optimized for Local Structural Similarity
ICEE, 2011
null
null
null
cs.MM eess.IV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Growth of the Internet and networked multimedia systems has emphasized the need for copyright protection of the media. Media can be images, audio clips, videos and etc. Digital watermarking is today extensively used for many applications such as authentication of ownership or identification of illegal copies. Digital...
[ { "created": "Tue, 13 Mar 2018 04:49:18 GMT", "version": "v1" } ]
2018-03-14
[ [ "Banitalebi", "Amin", "" ], [ "Nader-Esfahani", "Said", "" ], [ "Avanaki", "Alireza Nasiri", "" ] ]
Growth of the Internet and networked multimedia systems has emphasized the need for copyright protection of the media. Media can be images, audio clips, videos and etc. Digital watermarking is today extensively used for many applications such as authentication of ownership or identification of illegal copies. Digital w...
2310.03188
Zhe Zhao
Zhe Zhao, Qingyun Liu, Huan Gui, Bang An, Lichan Hong, Ed H. Chi
Talking Models: Distill Pre-trained Knowledge to Downstream Models via Interactive Communication
19 pages, 3 figures
null
null
null
cs.AI
http://creativecommons.org/licenses/by/4.0/
Many recent breakthroughs in machine learning have been enabled by the pre-trained foundation models. By scaling up model parameters, training data, and computation resources, foundation models have significantly advanced the state-of-the-art in many applications. However, it is still an open question of how to use t...
[ { "created": "Wed, 4 Oct 2023 22:22:21 GMT", "version": "v1" } ]
2023-10-06
[ [ "Zhao", "Zhe", "" ], [ "Liu", "Qingyun", "" ], [ "Gui", "Huan", "" ], [ "An", "Bang", "" ], [ "Hong", "Lichan", "" ], [ "Chi", "Ed H.", "" ] ]
Many recent breakthroughs in machine learning have been enabled by the pre-trained foundation models. By scaling up model parameters, training data, and computation resources, foundation models have significantly advanced the state-of-the-art in many applications. However, it is still an open question of how to use the...
1811.06047
Nachiket Deo
Nachiket Deo and Mohan M. Trivedi
Looking at the Driver/Rider in Autonomous Vehicles to Predict Take-Over Readiness
Submitted to IEEE transactions on Intelligent Vehicles
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Continuous estimation the driver's take-over readiness is critical for safe and timely transfer of control during the failure modes of autonomous vehicles. In this paper, we propose a data-driven approach for estimating the driver's take-over readiness based purely on observable cues from in-vehicle vision sensors. W...
[ { "created": "Wed, 14 Nov 2018 20:29:37 GMT", "version": "v1" } ]
2018-11-16
[ [ "Deo", "Nachiket", "" ], [ "Trivedi", "Mohan M.", "" ] ]
Continuous estimation the driver's take-over readiness is critical for safe and timely transfer of control during the failure modes of autonomous vehicles. In this paper, we propose a data-driven approach for estimating the driver's take-over readiness based purely on observable cues from in-vehicle vision sensors. We ...
2105.14875
Jakaria Rabbi
Ovishake Sen, Mohtasim Fuad, MD. Nazrul Islam, Jakaria Rabbi, Mehedi Masud, MD. Kamrul Hasan, Md. Abdul Awal, Awal Ahmed Fime, Md. Tahmid Hasan Fuad, Delowar Sikder, and MD. Akil Raihan Iftee
Bangla Natural Language Processing: A Comprehensive Analysis of Classical, Machine Learning, and Deep Learning Based Methods
Accedpted in IEEE Access and it has 46 pages. Link: https://ieeexplore.ieee.org/document/9751052 (Early Access - April 10, 2022)
null
10.1109/ACCESS.2022.3165563
null
cs.CL cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The Bangla language is the seventh most spoken language, with 265 million native and non-native speakers worldwide. However, English is the predominant language for online resources and technical knowledge, journals, and documentation. Consequently, many Bangla-speaking people, who have limited command of English, fa...
[ { "created": "Mon, 31 May 2021 10:58:58 GMT", "version": "v1" }, { "created": "Tue, 8 Jun 2021 09:40:12 GMT", "version": "v2" }, { "created": "Sat, 9 Apr 2022 19:01:54 GMT", "version": "v3" } ]
2022-04-12
[ [ "Sen", "Ovishake", "" ], [ "Fuad", "Mohtasim", "" ], [ "Islam", "MD. Nazrul", "" ], [ "Rabbi", "Jakaria", "" ], [ "Masud", "Mehedi", "" ], [ "Hasan", "MD. Kamrul", "" ], [ "Awal", "Md. Abdul", "" ], [ ...
The Bangla language is the seventh most spoken language, with 265 million native and non-native speakers worldwide. However, English is the predominant language for online resources and technical knowledge, journals, and documentation. Consequently, many Bangla-speaking people, who have limited command of English, face...
1304.3489
Emad Saad
Emad Saad
Logical Stochastic Optimization
arXiv admin note: substantial text overlap with arXiv:1304.2384, arXiv:1304.2797, arXiv:1304.1684, arXiv:1304.3144
null
null
null
cs.AI
http://creativecommons.org/licenses/by-nc-sa/3.0/
We present a logical framework to represent and reason about stochastic optimization problems based on probability answer set programming. This is established by allowing probability optimization aggregates, e.g., minimum and maximum in the language of probability answer set programming to allow minimization or maxim...
[ { "created": "Sat, 6 Apr 2013 06:54:24 GMT", "version": "v1" } ]
2013-04-15
[ [ "Saad", "Emad", "" ] ]
We present a logical framework to represent and reason about stochastic optimization problems based on probability answer set programming. This is established by allowing probability optimization aggregates, e.g., minimum and maximum in the language of probability answer set programming to allow minimization or maximiz...
1202.1148
Manfred Kufleitner
Volker Diekert, Manfred Kufleitner, Klaus Reinhardt, Tobias Walter
Regular Languages are Church-Rosser Congruential
null
null
null
null
cs.FL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper proves a long standing conjecture in formal language theory. It shows that all regular languages are Church-Rosser congruential. The class of Church-Rosser congruential languages was introduced by McNaughton, Narendran, and Otto in 1988. A language L is Church-Rosser congruential, if there exists a finite ...
[ { "created": "Mon, 6 Feb 2012 14:21:56 GMT", "version": "v1" } ]
2012-02-07
[ [ "Diekert", "Volker", "" ], [ "Kufleitner", "Manfred", "" ], [ "Reinhardt", "Klaus", "" ], [ "Walter", "Tobias", "" ] ]
This paper proves a long standing conjecture in formal language theory. It shows that all regular languages are Church-Rosser congruential. The class of Church-Rosser congruential languages was introduced by McNaughton, Narendran, and Otto in 1988. A language L is Church-Rosser congruential, if there exists a finite co...
1502.05860
Anupam Das
Anupam Das (\'Ecole Normale Sup\'erieure de Lyon (ENS Lyon), France)
On the relative proof complexity of deep inference via atomic flows
27 pages, 2 figures, full version of conference paper
Logical Methods in Computer Science, Volume 11, Issue 1 (March 6, 2015) lmcs:735
10.2168/LMCS-11(1:4)2015
null
cs.LO math.LO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We consider the proof complexity of the minimal complete fragment, KS, of standard deep inference systems for propositional logic. To examine the size of proofs we employ atomic flows, diagrams that trace structural changes through a proof but ignore logical information. As results we obtain a polynomial simulation o...
[ { "created": "Fri, 20 Feb 2015 12:53:38 GMT", "version": "v1" }, { "created": "Thu, 5 Mar 2015 12:28:52 GMT", "version": "v2" } ]
2019-03-14
[ [ "Das", "Anupam", "", "École Normale Supérieure de Lyon" ] ]
We consider the proof complexity of the minimal complete fragment, KS, of standard deep inference systems for propositional logic. To examine the size of proofs we employ atomic flows, diagrams that trace structural changes through a proof but ignore logical information. As results we obtain a polynomial simulation of ...
2407.13030
Anna-Maria Velentza
Anna-Maria Velentza (1 and 2), Efthymia Kefalouka (1) and Nikolaos Fachantidis (1 and 2) ((1) School of Educational & Social Policies, University of Macedonia, GR, (2) Laboratory of Informatics and Robotics Applications in Education and Society (LIRES), University of Macedonia, GR)
Socially Assistive Robot in Sexual Health: Group and Individual Student-Robot Interaction Activities Promoting Disclosure, Learning and Positive Attitudes
null
null
null
null
cs.RO cs.CY
http://creativecommons.org/licenses/by-nc-nd/4.0/
Comprehensive sex education (SE) is crucial in promoting sexual health and responsible behavior among students, particularly in elementary schools. Despite its significance, teaching SE can be challenging due to students' attitudes, shyness, and emotional barriers. Socially assistive robots (SARs) sometimes are perce...
[ { "created": "Wed, 17 Jul 2024 21:36:21 GMT", "version": "v1" } ]
2024-07-19
[ [ "Velentza", "Anna-Maria", "", "1 and 2" ], [ "Kefalouka", "Efthymia", "", "1 and 2" ], [ "Fachantidis", "Nikolaos", "", "1 and 2" ] ]
Comprehensive sex education (SE) is crucial in promoting sexual health and responsible behavior among students, particularly in elementary schools. Despite its significance, teaching SE can be challenging due to students' attitudes, shyness, and emotional barriers. Socially assistive robots (SARs) sometimes are perceiv...
1907.10669
Francesco Malandrino
Francesco Malandrino and Carla-Fabiana Chiasserini and Claudio Casetti and Giada Landi and Marco Capitani
An Optimization-enhanced MANO for Energy-efficient 5G Networks
arXiv admin note: substantial text overlap with arXiv:1804.05187
null
null
null
cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
5G network nodes, fronthaul and backhaul alike, will have both forwarding and computational capabilities. This makes energy-efficient network management more challenging, as decisions such as activating or deactivating a node impact on both the ability of the network to route traffic and the amount of processing it c...
[ { "created": "Tue, 23 Jul 2019 07:20:49 GMT", "version": "v1" } ]
2019-07-26
[ [ "Malandrino", "Francesco", "" ], [ "Chiasserini", "Carla-Fabiana", "" ], [ "Casetti", "Claudio", "" ], [ "Landi", "Giada", "" ], [ "Capitani", "Marco", "" ] ]
5G network nodes, fronthaul and backhaul alike, will have both forwarding and computational capabilities. This makes energy-efficient network management more challenging, as decisions such as activating or deactivating a node impact on both the ability of the network to route traffic and the amount of processing it can...
2212.04491
Workneh Yilma Ayele
Workneh Yilma Ayele
Improving the Utilization of Digital Services - Evaluating Contest - Driven Open Data Development and the Adoption of Cloud Services
The abstract is summarized to fit arxiv's character length requirement; DSV Report Series, Series No. 18-008
null
null
null
cs.DC
http://creativecommons.org/licenses/by/4.0/
There is a growing interest in utilizing digital services, such as software apps and cloud-based software services. The utilization of digital services is increasing more rapidly than any other segment of world trade. The availability of open data unlocks the possibility of generating market possibilities in the publ...
[ { "created": "Tue, 6 Dec 2022 23:30:27 GMT", "version": "v1" } ]
2022-12-13
[ [ "Ayele", "Workneh Yilma", "" ] ]
There is a growing interest in utilizing digital services, such as software apps and cloud-based software services. The utilization of digital services is increasing more rapidly than any other segment of world trade. The availability of open data unlocks the possibility of generating market possibilities in the public...
2405.11014
Abdelhadi Soudi
Abdelhadi Soudi, Violetta Cavalli-Sforza and Abderrahim Jamari
The Arabic Noun System Generation
In Proceedings of The International Conference on Arabic Processing, Lamanouba University, April 2002, Tunisia
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
In this paper, we show that the multiple-stem approach to nouns with a broken plural pattern allows for greater generalizations to be stated in the morphological system. Such an approach dispenses with truncating/deleting rules and other complex rules that are required to account for the highly allomorphic broken plu...
[ { "created": "Fri, 17 May 2024 17:33:10 GMT", "version": "v1" } ]
2024-05-21
[ [ "Soudi", "Abdelhadi", "" ], [ "Cavalli-Sforza", "Violetta", "" ], [ "Jamari", "Abderrahim", "" ] ]
In this paper, we show that the multiple-stem approach to nouns with a broken plural pattern allows for greater generalizations to be stated in the morphological system. Such an approach dispenses with truncating/deleting rules and other complex rules that are required to account for the highly allomorphic broken plura...
2210.03623
Keshav Gupta
Keshav Gupta, Peter Zhi Xuan Li, Sertac Karaman, Vivienne Sze
Efficient Computation of Map-scale Continuous Mutual Information on Chip in Real Time
null
null
10.1109/IROS51168.2021.9636603
null
cs.AR cs.RO
http://creativecommons.org/licenses/by/4.0/
Exploration tasks are essential to many emerging robotics applications, ranging from search and rescue to space exploration. The planning problem for exploration requires determining the best locations for future measurements that will enhance the fidelity of the map, for example, by reducing its total entropy. A wid...
[ { "created": "Fri, 7 Oct 2022 15:27:32 GMT", "version": "v1" } ]
2022-10-10
[ [ "Gupta", "Keshav", "" ], [ "Li", "Peter Zhi Xuan", "" ], [ "Karaman", "Sertac", "" ], [ "Sze", "Vivienne", "" ] ]
Exploration tasks are essential to many emerging robotics applications, ranging from search and rescue to space exploration. The planning problem for exploration requires determining the best locations for future measurements that will enhance the fidelity of the map, for example, by reducing its total entropy. A widel...
2210.17309
Zachary Fulker
Zachary Fulker, Patrick Forber, Rory Smead, Christoph Riedl
Spontaneous emergence of groups and signaling diversity in dynamic networks
null
null
null
null
cs.SI econ.TH physics.soc-ph q-bio.MN q-bio.PE
http://creativecommons.org/licenses/by/4.0/
We study the coevolution of network structure and signaling behavior. We model agents who can preferentially associate with others in a dynamic network while they also learn to play a simple sender-receiver game. We have four major findings. First, signaling interactions in dynamic networks are sufficient to cause th...
[ { "created": "Sat, 22 Oct 2022 14:35:54 GMT", "version": "v1" }, { "created": "Fri, 12 Jan 2024 16:09:20 GMT", "version": "v2" } ]
2024-01-15
[ [ "Fulker", "Zachary", "" ], [ "Forber", "Patrick", "" ], [ "Smead", "Rory", "" ], [ "Riedl", "Christoph", "" ] ]
We study the coevolution of network structure and signaling behavior. We model agents who can preferentially associate with others in a dynamic network while they also learn to play a simple sender-receiver game. We have four major findings. First, signaling interactions in dynamic networks are sufficient to cause the ...
2002.06063
Parameswaran Kamalaruban Dr.
Parameswaran Kamalaruban, Yu-Ting Huang, Ya-Ping Hsieh, Paul Rolland, Cheng Shi, Volkan Cevher
Robust Reinforcement Learning via Adversarial training with Langevin Dynamics
null
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We introduce a sampling perspective to tackle the challenging task of training robust Reinforcement Learning (RL) agents. Leveraging the powerful Stochastic Gradient Langevin Dynamics, we present a novel, scalable two-player RL algorithm, which is a sampling variant of the two-player policy gradient method. Our algor...
[ { "created": "Fri, 14 Feb 2020 14:59:14 GMT", "version": "v1" }, { "created": "Thu, 5 Nov 2020 19:09:36 GMT", "version": "v2" } ]
2020-11-09
[ [ "Kamalaruban", "Parameswaran", "" ], [ "Huang", "Yu-Ting", "" ], [ "Hsieh", "Ya-Ping", "" ], [ "Rolland", "Paul", "" ], [ "Shi", "Cheng", "" ], [ "Cevher", "Volkan", "" ] ]
We introduce a sampling perspective to tackle the challenging task of training robust Reinforcement Learning (RL) agents. Leveraging the powerful Stochastic Gradient Langevin Dynamics, we present a novel, scalable two-player RL algorithm, which is a sampling variant of the two-player policy gradient method. Our algorit...
2110.06972
Shagun Sodhani
Shagun Sodhani, Franziska Meier, Joelle Pineau, Amy Zhang
Block Contextual MDPs for Continual Learning
26pages, Under Review
null
null
null
cs.LG cs.AI
http://creativecommons.org/licenses/by/4.0/
In reinforcement learning (RL), when defining a Markov Decision Process (MDP), the environment dynamics is implicitly assumed to be stationary. This assumption of stationarity, while simplifying, can be unrealistic in many scenarios. In the continual reinforcement learning scenario, the sequence of tasks is another s...
[ { "created": "Wed, 13 Oct 2021 18:30:30 GMT", "version": "v1" } ]
2021-10-15
[ [ "Sodhani", "Shagun", "" ], [ "Meier", "Franziska", "" ], [ "Pineau", "Joelle", "" ], [ "Zhang", "Amy", "" ] ]
In reinforcement learning (RL), when defining a Markov Decision Process (MDP), the environment dynamics is implicitly assumed to be stationary. This assumption of stationarity, while simplifying, can be unrealistic in many scenarios. In the continual reinforcement learning scenario, the sequence of tasks is another sou...
2112.08547
Debanjan Mahata
Mayank Kulkarni, Debanjan Mahata, Ravneet Arora, Rajarshi Bhowmik
Learning Rich Representation of Keyphrases from Text
null
null
null
null
cs.CL cs.IR cs.LG
http://creativecommons.org/licenses/by/4.0/
In this work, we explore how to train task-specific language models aimed towards learning rich representation of keyphrases from text documents. We experiment with different masking strategies for pre-training transformer language models (LMs) in discriminative as well as generative settings. In the discriminative s...
[ { "created": "Thu, 16 Dec 2021 01:09:51 GMT", "version": "v1" }, { "created": "Sun, 10 Jul 2022 13:39:57 GMT", "version": "v2" } ]
2022-07-12
[ [ "Kulkarni", "Mayank", "" ], [ "Mahata", "Debanjan", "" ], [ "Arora", "Ravneet", "" ], [ "Bhowmik", "Rajarshi", "" ] ]
In this work, we explore how to train task-specific language models aimed towards learning rich representation of keyphrases from text documents. We experiment with different masking strategies for pre-training transformer language models (LMs) in discriminative as well as generative settings. In the discriminative set...
2403.03879
Meryem Amaouche
Meryem Amaouche and Ouassim Karrakchou and Mounir Ghogho and Anouar El Ghazzaly and Mohamed Alami and Ahmed Ameur
Redefining cystoscopy with ai: bladder cancer diagnosis using an efficient hybrid cnn-transformer model
7 pages, 5 figures
null
null
null
cs.CV cs.AI
http://creativecommons.org/licenses/by/4.0/
Bladder cancer ranks within the top 10 most diagnosed cancers worldwide and is among the most expensive cancers to treat due to the high recurrence rates which require lifetime follow-ups. The primary tool for diagnosis is cystoscopy, which heavily relies on doctors' expertise and interpretation. Therefore, annually,...
[ { "created": "Wed, 6 Mar 2024 17:38:33 GMT", "version": "v1" } ]
2024-03-07
[ [ "Amaouche", "Meryem", "" ], [ "Karrakchou", "Ouassim", "" ], [ "Ghogho", "Mounir", "" ], [ "Ghazzaly", "Anouar El", "" ], [ "Alami", "Mohamed", "" ], [ "Ameur", "Ahmed", "" ] ]
Bladder cancer ranks within the top 10 most diagnosed cancers worldwide and is among the most expensive cancers to treat due to the high recurrence rates which require lifetime follow-ups. The primary tool for diagnosis is cystoscopy, which heavily relies on doctors' expertise and interpretation. Therefore, annually, n...
2404.05089
Alexandre Muzio
Alexandre Muzio, Alex Sun, Churan He
SEER-MoE: Sparse Expert Efficiency through Regularization for Mixture-of-Experts
8+3 pages
null
null
null
cs.CL cs.LG
http://creativecommons.org/licenses/by/4.0/
The advancement of deep learning has led to the emergence of Mixture-of-Experts (MoEs) models, known for their dynamic allocation of computational resources based on input. Despite their promise, MoEs face challenges, particularly in terms of memory requirements. To address this, our work introduces SEER-MoE, a novel...
[ { "created": "Sun, 7 Apr 2024 22:13:43 GMT", "version": "v1" } ]
2024-04-09
[ [ "Muzio", "Alexandre", "" ], [ "Sun", "Alex", "" ], [ "He", "Churan", "" ] ]
The advancement of deep learning has led to the emergence of Mixture-of-Experts (MoEs) models, known for their dynamic allocation of computational resources based on input. Despite their promise, MoEs face challenges, particularly in terms of memory requirements. To address this, our work introduces SEER-MoE, a novel t...
0902.3223
Jose Brito
Jose Brito, Mauricio Lila, Flavio Montenegro, Nelson Maculan
An Exact Algorithm for the Stratification Problem with Proportional Allocation
null
null
null
null
cs.LG cs.DM cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We report a new optimal resolution for the statistical stratification problem under proportional sampling allocation among strata. Consider a finite population of N units, a random sample of n units selected from this population and a number L of strata. Thus, we have to define which units belong to each stratum so a...
[ { "created": "Wed, 18 Feb 2009 19:12:59 GMT", "version": "v1" } ]
2009-02-24
[ [ "Brito", "Jose", "" ], [ "Lila", "Mauricio", "" ], [ "Montenegro", "Flavio", "" ], [ "Maculan", "Nelson", "" ] ]
We report a new optimal resolution for the statistical stratification problem under proportional sampling allocation among strata. Consider a finite population of N units, a random sample of n units selected from this population and a number L of strata. Thus, we have to define which units belong to each stratum so as ...
1508.06805
Jeffrey Goeders
Jeffrey Goeders, Steven J. E. Wilton
Allowing Software Developers to Debug HLS Hardware
Presented at Second International Workshop on FPGAs for Software Programmers (FSP 2015) (arXiv:1508.06320)
null
null
FSP/2015/01
cs.SE cs.AR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
High-Level Synthesis (HLS) is emerging as a mainstream design methodology, allowing software designers to enjoy the benefits of a hardware implementation. Significant work has led to effective compilers that produce high-quality hardware designs from software specifications. However, in order to fully benefit from th...
[ { "created": "Thu, 27 Aug 2015 11:22:04 GMT", "version": "v1" } ]
2015-08-28
[ [ "Goeders", "Jeffrey", "" ], [ "Wilton", "Steven J. E.", "" ] ]
High-Level Synthesis (HLS) is emerging as a mainstream design methodology, allowing software designers to enjoy the benefits of a hardware implementation. Significant work has led to effective compilers that produce high-quality hardware designs from software specifications. However, in order to fully benefit from the ...
1301.7397
Thomas Lukasiewicz
Thomas Lukasiewicz
Magic Inference Rules for Probabilistic Deduction under Taxonomic Knowledge
Appears in Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence (UAI1998)
null
null
UAI-P-1998-PG-354-361
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present locally complete inference rules for probabilistic deduction from taxonomic and probabilistic knowledge-bases over conjunctive events. Crucially, in contrast to similar inference rules in the literature, our inference rules are locally complete for conjunctive events and under additional taxonomic knowledg...
[ { "created": "Wed, 30 Jan 2013 15:05:34 GMT", "version": "v1" } ]
2013-02-01
[ [ "Lukasiewicz", "Thomas", "" ] ]
We present locally complete inference rules for probabilistic deduction from taxonomic and probabilistic knowledge-bases over conjunctive events. Crucially, in contrast to similar inference rules in the literature, our inference rules are locally complete for conjunctive events and under additional taxonomic knowledge....
1708.05790
Corren McCoy
Corren G. McCoy, Michael L. Nelson, Michele C. Weigle
University Twitter Engagement: Using Twitter Followers to Rank Universities
14 pages, 4 figures
null
null
null
cs.DL cs.SI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We examine and rank a set of 264 U.S. universities extracted from the National Collegiate Athletic Association (NCAA) Division I membership and global lists published in U.S. News, Times Higher Education, Academic Ranking of World Universities, and Money Magazine. Our University Twitter Engagement (UTE) rank is based...
[ { "created": "Sat, 19 Aug 2017 01:33:28 GMT", "version": "v1" } ]
2017-08-22
[ [ "McCoy", "Corren G.", "" ], [ "Nelson", "Michael L.", "" ], [ "Weigle", "Michele C.", "" ] ]
We examine and rank a set of 264 U.S. universities extracted from the National Collegiate Athletic Association (NCAA) Division I membership and global lists published in U.S. News, Times Higher Education, Academic Ranking of World Universities, and Money Magazine. Our University Twitter Engagement (UTE) rank is based o...
1812.10901
Yankai Lin
Yankai Lin, Xu Han, Ruobing Xie, Zhiyuan Liu, Maosong Sun
Knowledge Representation Learning: A Quantitative Review
58 pages
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Knowledge representation learning (KRL) aims to represent entities and relations in knowledge graph in low-dimensional semantic space, which have been widely used in massive knowledge-driven tasks. In this article, we introduce the reader to the motivations for KRL, and overview existing approaches for KRL. Afterward...
[ { "created": "Fri, 28 Dec 2018 06:15:53 GMT", "version": "v1" } ]
2018-12-31
[ [ "Lin", "Yankai", "" ], [ "Han", "Xu", "" ], [ "Xie", "Ruobing", "" ], [ "Liu", "Zhiyuan", "" ], [ "Sun", "Maosong", "" ] ]
Knowledge representation learning (KRL) aims to represent entities and relations in knowledge graph in low-dimensional semantic space, which have been widely used in massive knowledge-driven tasks. In this article, we introduce the reader to the motivations for KRL, and overview existing approaches for KRL. Afterwards,...
2112.03088
Roland Oruche
Roland Oruche, Lisa Egede, Tracy Baker, Fearghal O'Donncha
Transfer learning to improve streamflow forecasts in data sparse regions
9 pages, 5 figures, 1 table
null
null
null
cs.LG cs.AI
http://creativecommons.org/licenses/by/4.0/
Effective water resource management requires information on water availability, both in terms of quality and quantity, spatially and temporally. In this paper, we study the methodology behind Transfer Learning (TL) through fine-tuning and parameter transferring for better generalization performance of streamflow pred...
[ { "created": "Mon, 6 Dec 2021 14:52:53 GMT", "version": "v1" } ]
2021-12-07
[ [ "Oruche", "Roland", "" ], [ "Egede", "Lisa", "" ], [ "Baker", "Tracy", "" ], [ "O'Donncha", "Fearghal", "" ] ]
Effective water resource management requires information on water availability, both in terms of quality and quantity, spatially and temporally. In this paper, we study the methodology behind Transfer Learning (TL) through fine-tuning and parameter transferring for better generalization performance of streamflow predic...
1707.09775
Endel Poder
Endel Poder
Capacity limitations of visual search in deep convolutional neural networks
10 pages, 4 figures
null
null
null
cs.CV q-bio.NC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Deep convolutional neural networks follow roughly the architecture of biological visual systems and have shown a performance comparable to human observers in object recognition tasks. In this study, I tested three pretrained deep neural networks in visual search for simple visual features, and for feature configurati...
[ { "created": "Mon, 31 Jul 2017 09:14:14 GMT", "version": "v1" }, { "created": "Mon, 29 Mar 2021 09:53:06 GMT", "version": "v2" } ]
2021-03-30
[ [ "Poder", "Endel", "" ] ]
Deep convolutional neural networks follow roughly the architecture of biological visual systems and have shown a performance comparable to human observers in object recognition tasks. In this study, I tested three pretrained deep neural networks in visual search for simple visual features, and for feature configuration...
1906.02280
Laura D'Arcy
Laura D'Arcy, Padraig Corcoran, Alun Preece
Deep Q-Learning for Directed Acyclic Graph Generation
Accepted to Learning and Reasoning with Graph-Structured Representations, ICML 2019 Workshop
null
null
null
cs.LG stat.ML
http://creativecommons.org/publicdomain/zero/1.0/
We present a method to generate directed acyclic graphs (DAGs) using deep reinforcement learning, specifically deep Q-learning. Generating graphs with specified structures is an important and challenging task in various application fields, however most current graph generation methods produce graphs with undirected e...
[ { "created": "Wed, 5 Jun 2019 19:56:44 GMT", "version": "v1" } ]
2019-06-07
[ [ "D'Arcy", "Laura", "" ], [ "Corcoran", "Padraig", "" ], [ "Preece", "Alun", "" ] ]
We present a method to generate directed acyclic graphs (DAGs) using deep reinforcement learning, specifically deep Q-learning. Generating graphs with specified structures is an important and challenging task in various application fields, however most current graph generation methods produce graphs with undirected edg...
2307.07729
Takao Yamanaka
Hinata Aoki and Takao Yamanaka
Improving NeRF with Height Data for Utilization of GIS Data
ICIP2023
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Neural Radiance Fields (NeRF) has been applied to various tasks related to representations of 3D scenes. Most studies based on NeRF have focused on a small object, while a few studies have tried to reconstruct large-scale scenes although these methods tend to require large computational cost. For the application of N...
[ { "created": "Sat, 15 Jul 2023 06:49:09 GMT", "version": "v1" } ]
2023-07-18
[ [ "Aoki", "Hinata", "" ], [ "Yamanaka", "Takao", "" ] ]
Neural Radiance Fields (NeRF) has been applied to various tasks related to representations of 3D scenes. Most studies based on NeRF have focused on a small object, while a few studies have tried to reconstruct large-scale scenes although these methods tend to require large computational cost. For the application of NeR...
2108.00158
Kong Zhaoming
Zhaoming Kong, Lichao Sun, Hao Peng, Liang Zhan, Yong Chen, Lifang He
Multiplex Graph Networks for Multimodal Brain Network Analysis
null
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
In this paper, we propose MGNet, a simple and effective multiplex graph convolutional network (GCN) model for multimodal brain network analysis. The proposed method integrates tensor representation into the multiplex GCN model to extract the latent structures of a set of multimodal brain networks, which allows an int...
[ { "created": "Sat, 31 Jul 2021 06:01:29 GMT", "version": "v1" } ]
2021-08-03
[ [ "Kong", "Zhaoming", "" ], [ "Sun", "Lichao", "" ], [ "Peng", "Hao", "" ], [ "Zhan", "Liang", "" ], [ "Chen", "Yong", "" ], [ "He", "Lifang", "" ] ]
In this paper, we propose MGNet, a simple and effective multiplex graph convolutional network (GCN) model for multimodal brain network analysis. The proposed method integrates tensor representation into the multiplex GCN model to extract the latent structures of a set of multimodal brain networks, which allows an intui...
2405.13699
Lorenzo Perini
Lorenzo Perini, Maja Rudolph, Sabrina Schmedding, Chen Qiu
Uncertainty-aware Evaluation of Auxiliary Anomalies with the Expected Anomaly Posterior
null
null
null
null
cs.LG cs.AI
http://creativecommons.org/licenses/by/4.0/
Anomaly detection is the task of identifying examples that do not behave as expected. Because anomalies are rare and unexpected events, collecting real anomalous examples is often challenging in several applications. In addition, learning an anomaly detector with limited (or no) anomalies often yields poor prediction...
[ { "created": "Wed, 22 May 2024 14:43:29 GMT", "version": "v1" } ]
2024-05-24
[ [ "Perini", "Lorenzo", "" ], [ "Rudolph", "Maja", "" ], [ "Schmedding", "Sabrina", "" ], [ "Qiu", "Chen", "" ] ]
Anomaly detection is the task of identifying examples that do not behave as expected. Because anomalies are rare and unexpected events, collecting real anomalous examples is often challenging in several applications. In addition, learning an anomaly detector with limited (or no) anomalies often yields poor prediction p...
2004.09989
Renato Baptista
Renato Baptista, Alexandre Saint, Kassem Al Ismaeil, Djamila Aouada
Towards Generalization of 3D Human Pose Estimation In The Wild
null
null
null
null
cs.CV eess.IV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we propose 3DBodyTex.Pose, a dataset that addresses the task of 3D human pose estimation in-the-wild. Generalization to in-the-wild images remains limited due to the lack of adequate datasets. Existent ones are usually collected in indoor controlled environments where motion capture systems are used to...
[ { "created": "Tue, 21 Apr 2020 13:31:58 GMT", "version": "v1" } ]
2020-04-22
[ [ "Baptista", "Renato", "" ], [ "Saint", "Alexandre", "" ], [ "Ismaeil", "Kassem Al", "" ], [ "Aouada", "Djamila", "" ] ]
In this paper, we propose 3DBodyTex.Pose, a dataset that addresses the task of 3D human pose estimation in-the-wild. Generalization to in-the-wild images remains limited due to the lack of adequate datasets. Existent ones are usually collected in indoor controlled environments where motion capture systems are used to o...
2001.08370
Mohamed El Amine Seddik
Mohamed El Amine Seddik, Cosme Louart, Mohamed Tamaazousti, Romain Couillet
Random Matrix Theory Proves that Deep Learning Representations of GAN-data Behave as Gaussian Mixtures
null
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper shows that deep learning (DL) representations of data produced by generative adversarial nets (GANs) are random vectors which fall within the class of so-called \textit{concentrated} random vectors. Further exploiting the fact that Gram matrices, of the type $G = X^T X$ with $X=[x_1,\ldots,x_n]\in \mathbb{...
[ { "created": "Tue, 21 Jan 2020 22:17:09 GMT", "version": "v1" } ]
2020-01-24
[ [ "Seddik", "Mohamed El Amine", "" ], [ "Louart", "Cosme", "" ], [ "Tamaazousti", "Mohamed", "" ], [ "Couillet", "Romain", "" ] ]
This paper shows that deep learning (DL) representations of data produced by generative adversarial nets (GANs) are random vectors which fall within the class of so-called \textit{concentrated} random vectors. Further exploiting the fact that Gram matrices, of the type $G = X^T X$ with $X=[x_1,\ldots,x_n]\in \mathbb{R}...
1802.01174
Dominika Tkaczyk
Dominika Tkaczyk, Andrew Collins, Joeran Beel
A Method for Discovering and Extracting Author Contributions Information from Scientific Biomedical Publications
null
null
null
null
cs.DL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Creating scientific publications is a complex process, typically composed of a number of different activities, such as designing the experiments, data preparation, programming software and writing and editing the manuscript. The information about the contributions of individual authors of a paper is important in the ...
[ { "created": "Sun, 4 Feb 2018 18:55:38 GMT", "version": "v1" } ]
2018-02-06
[ [ "Tkaczyk", "Dominika", "" ], [ "Collins", "Andrew", "" ], [ "Beel", "Joeran", "" ] ]
Creating scientific publications is a complex process, typically composed of a number of different activities, such as designing the experiments, data preparation, programming software and writing and editing the manuscript. The information about the contributions of individual authors of a paper is important in the co...
1812.06952
Jeroen Zuiddam
Matthias Christandl, P\'eter Vrana, Jeroen Zuiddam
Barriers for fast matrix multiplication from irreversibility
Updated Example 13
Theory of Computing 17(2), 2021, 1--32
10.4086/toc.2021.v017a002
null
cs.CC math.AC quant-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Determining the asymptotic algebraic complexity of matrix multiplication, succinctly represented by the matrix multiplication exponent $\omega$, is a central problem in algebraic complexity theory. The best upper bounds on $\omega$, leading to the state-of-the-art $\omega \leq 2.37..$, have been obtained via the lase...
[ { "created": "Mon, 17 Dec 2018 18:49:18 GMT", "version": "v1" }, { "created": "Sun, 8 Sep 2019 16:14:26 GMT", "version": "v2" }, { "created": "Thu, 24 Dec 2020 15:36:07 GMT", "version": "v3" }, { "created": "Sat, 5 Mar 2022 13:05:55 GMT", "version": "v4" } ]
2022-03-08
[ [ "Christandl", "Matthias", "" ], [ "Vrana", "Péter", "" ], [ "Zuiddam", "Jeroen", "" ] ]
Determining the asymptotic algebraic complexity of matrix multiplication, succinctly represented by the matrix multiplication exponent $\omega$, is a central problem in algebraic complexity theory. The best upper bounds on $\omega$, leading to the state-of-the-art $\omega \leq 2.37..$, have been obtained via the laser ...
0905.4068
{\L}ukasz Je\.z
{\L}ukasz Je\.z
A 4/3-competitive randomized algorithm for online scheduling of packets with agreeable deadlines
11 pages, 3-4 figures; new version due to STACS submission
null
null
null
cs.DS
http://creativecommons.org/licenses/by/3.0/
In 2005 Li et al. gave a phi-competitive deterministic online algorithm for scheduling of packets with agreeable deadlines with a very interesting analysis. This is known to be optimal due to a lower bound by Hajek. We claim that the algorithm by Li et al. can be slightly simplified, while retaining its competitive r...
[ { "created": "Mon, 25 May 2009 19:43:24 GMT", "version": "v1" }, { "created": "Thu, 1 Oct 2009 15:45:18 GMT", "version": "v2" }, { "created": "Tue, 5 Jan 2010 19:34:28 GMT", "version": "v3" }, { "created": "Wed, 3 Feb 2010 12:42:48 GMT", "version": "v4" } ]
2010-02-03
[ [ "Jeż", "Łukasz", "" ] ]
In 2005 Li et al. gave a phi-competitive deterministic online algorithm for scheduling of packets with agreeable deadlines with a very interesting analysis. This is known to be optimal due to a lower bound by Hajek. We claim that the algorithm by Li et al. can be slightly simplified, while retaining its competitive rat...
2210.09992
Chun-Kit Ngan
Chun-Kit Ngan, Alexander Brodsky
Optimal Event Monitoring through Internet Mashup over Multivariate Time Series
null
null
null
null
cs.AI
http://creativecommons.org/licenses/by-sa/4.0/
We propose a Web-Mashup Application Service Framework for Multivariate Time Series Analytics (MTSA) that supports the services of model definitions, querying, parameter learning, model evaluations, data monitoring, decision recommendations, and web portals. This framework maintains the advantage of combining the stre...
[ { "created": "Tue, 18 Oct 2022 16:56:17 GMT", "version": "v1" } ]
2022-10-19
[ [ "Ngan", "Chun-Kit", "" ], [ "Brodsky", "Alexander", "" ] ]
We propose a Web-Mashup Application Service Framework for Multivariate Time Series Analytics (MTSA) that supports the services of model definitions, querying, parameter learning, model evaluations, data monitoring, decision recommendations, and web portals. This framework maintains the advantage of combining the streng...
2204.08780
Sven Richter
Sven Richter, Frank Bieder, Sascha Wirges and Christoph Stiller
Sensor Data Fusion in Top-View Grid Maps using Evidential Reasoning with Advanced Conflict Resolution
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present a new method to combine evidential top-view grid maps estimated based on heterogeneous sensor sources. Dempster's combination rule that is usually applied in this context provides undesired results with highly conflicting inputs. Therefore, we use more advanced evidential reasoning techniques and improve t...
[ { "created": "Tue, 19 Apr 2022 10:02:21 GMT", "version": "v1" } ]
2022-04-20
[ [ "Richter", "Sven", "" ], [ "Bieder", "Frank", "" ], [ "Wirges", "Sascha", "" ], [ "Stiller", "Christoph", "" ] ]
We present a new method to combine evidential top-view grid maps estimated based on heterogeneous sensor sources. Dempster's combination rule that is usually applied in this context provides undesired results with highly conflicting inputs. Therefore, we use more advanced evidential reasoning techniques and improve the...
1102.3410
Reza Khosravi-Farsani
Reza K. Farsani, Farokh Marvasti
Capacity Bounds for Multiuser Channels with Non-Causal Channel State Information at the Transmitters
12 pages, It is also shown that our derived achievable rate region for the two-user BC with CSI strictly contains those of [11, Sec. V] and [12, p. 7-53]
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, capacity inner and outer bounds are established for the multiuser channels with Channel State Information (CSI) known non-causally at the transmitters: The Multiple Access Channel (MAC), the Broadcast Channel (BC) with common information, and the Relay Channel (RC). For each channel, the actual capacit...
[ { "created": "Wed, 16 Feb 2011 19:29:53 GMT", "version": "v1" }, { "created": "Tue, 17 May 2011 15:02:06 GMT", "version": "v2" } ]
2013-02-17
[ [ "Farsani", "Reza K.", "" ], [ "Marvasti", "Farokh", "" ] ]
In this paper, capacity inner and outer bounds are established for the multiuser channels with Channel State Information (CSI) known non-causally at the transmitters: The Multiple Access Channel (MAC), the Broadcast Channel (BC) with common information, and the Relay Channel (RC). For each channel, the actual capacity ...
2205.05874
David Mac\^edo
David Mac\^edo, Cleber Zanchettin, Teresa Ludermir
Distinction Maximization Loss: Efficiently Improving Out-of-Distribution Detection and Uncertainty Estimation by Replacing the Loss and Calibrating
null
null
null
null
cs.LG cs.AI cs.CV cs.NE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Building robust deterministic neural networks remains a challenge. On the one hand, some approaches improve out-of-distribution detection at the cost of reducing classification accuracy in some situations. On the other hand, some methods simultaneously increase classification accuracy, uncertainty estimation, and out...
[ { "created": "Thu, 12 May 2022 04:37:35 GMT", "version": "v1" }, { "created": "Thu, 19 May 2022 12:04:27 GMT", "version": "v2" }, { "created": "Thu, 28 Jul 2022 12:53:20 GMT", "version": "v3" }, { "created": "Mon, 1 Aug 2022 05:04:23 GMT", "version": "v4" }, { "cr...
2022-08-09
[ [ "Macêdo", "David", "" ], [ "Zanchettin", "Cleber", "" ], [ "Ludermir", "Teresa", "" ] ]
Building robust deterministic neural networks remains a challenge. On the one hand, some approaches improve out-of-distribution detection at the cost of reducing classification accuracy in some situations. On the other hand, some methods simultaneously increase classification accuracy, uncertainty estimation, and out-o...
2107.09973
Mirco Theile
Mirco Theile, Jonathan Ponniah, Or Dantsker, Marco Caccamo
Multi-Agent Belief Sharing through Autonomous Hierarchical Multi-Level Clustering
Submitted to IEEE Transactions on Robotics, article extends on https://doi.org/10.2514/6.2021-0656
null
null
null
cs.RO cs.MA cs.SY eess.SY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Coordination in multi-agent systems is challenging for agile robots such as unmanned aerial vehicles (UAVs), where relative agent positions frequently change due to unconstrained movement. The problem is exacerbated through the individual take-off and landing of agents for battery recharging leading to a varying numb...
[ { "created": "Wed, 21 Jul 2021 09:37:21 GMT", "version": "v1" } ]
2021-07-22
[ [ "Theile", "Mirco", "" ], [ "Ponniah", "Jonathan", "" ], [ "Dantsker", "Or", "" ], [ "Caccamo", "Marco", "" ] ]
Coordination in multi-agent systems is challenging for agile robots such as unmanned aerial vehicles (UAVs), where relative agent positions frequently change due to unconstrained movement. The problem is exacerbated through the individual take-off and landing of agents for battery recharging leading to a varying number...
0808.2670
Mat\'u\v{s} Medo
Tao Zhou, Zoltan Kuscsik, Jian-Guo Liu, Matus Medo, Joseph R. Wakeling, Yi-Cheng Zhang
Solving the apparent diversity-accuracy dilemma of recommender systems
10 pages, 9 figures, 4 tables (final version with supporting information included)
PNAS 107, 4511-4515, 2010
10.1073/pnas.1000488107
null
cs.IR physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recommender systems use data on past user preferences to predict possible future likes and interests. A key challenge is that while the most useful individual recommendations are to be found among diverse niche objects, the most reliably accurate results are obtained by methods that recommend objects based on user or...
[ { "created": "Tue, 19 Aug 2008 23:17:40 GMT", "version": "v1" }, { "created": "Tue, 24 Mar 2009 16:14:59 GMT", "version": "v2" }, { "created": "Fri, 12 Mar 2010 16:27:39 GMT", "version": "v3" } ]
2010-03-15
[ [ "Zhou", "Tao", "" ], [ "Kuscsik", "Zoltan", "" ], [ "Liu", "Jian-Guo", "" ], [ "Medo", "Matus", "" ], [ "Wakeling", "Joseph R.", "" ], [ "Zhang", "Yi-Cheng", "" ] ]
Recommender systems use data on past user preferences to predict possible future likes and interests. A key challenge is that while the most useful individual recommendations are to be found among diverse niche objects, the most reliably accurate results are obtained by methods that recommend objects based on user or o...
2404.00570
Xingxuan Li
Xingxuan Li, Xuan-Phi Nguyen, Shafiq Joty, Lidong Bing
ParaICL: Towards Robust Parallel In-Context Learning
Work in progress
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Large language models (LLMs) have become the norm in natural language processing (NLP), excelling in few-shot in-context learning (ICL) with their remarkable abilities. Nonetheless, the success of ICL largely hinges on the choice of few-shot demonstration examples, making the selection process increasingly crucial. E...
[ { "created": "Sun, 31 Mar 2024 05:56:15 GMT", "version": "v1" } ]
2024-04-02
[ [ "Li", "Xingxuan", "" ], [ "Nguyen", "Xuan-Phi", "" ], [ "Joty", "Shafiq", "" ], [ "Bing", "Lidong", "" ] ]
Large language models (LLMs) have become the norm in natural language processing (NLP), excelling in few-shot in-context learning (ICL) with their remarkable abilities. Nonetheless, the success of ICL largely hinges on the choice of few-shot demonstration examples, making the selection process increasingly crucial. Exi...
2203.00499
Anna Ziegler
Anna Ziegler (1 and 2), Niklas Georg (1 and 2), Wolfgang Ackermann (1), Sebastian Sch\"ops (1 and 2) ((1) Institute for Accelerator Science and Electromagnetic Fields (TEMF) at Technische Universit\"at Darmstadt, (2) Centre for Computational Engineering at Technische Universit\"at Darmstadt)
Mode Recognition by Shape Morphing for Maxwell's Eigenvalue Problem
null
null
10.1109/TAP.2023.3249907
null
cs.CE cs.NA math.NA physics.acc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In electrical engineering, for example during the design of superconducting radio-frequency cavities, eigenmodes must be identified based on their field patterns. This allows to understand the working principle, optimize the performance of a device and distinguish desired from parasitic modes. For cavities with simpl...
[ { "created": "Tue, 1 Mar 2022 14:49:06 GMT", "version": "v1" } ]
2023-05-17
[ [ "Ziegler", "Anna", "", "1 and 2" ], [ "Georg", "Niklas", "", "1 and 2" ], [ "Ackermann", "Wolfgang", "", "1 and 2" ], [ "Schöps", "Sebastian", "", "1 and 2" ] ]
In electrical engineering, for example during the design of superconducting radio-frequency cavities, eigenmodes must be identified based on their field patterns. This allows to understand the working principle, optimize the performance of a device and distinguish desired from parasitic modes. For cavities with simple ...
1911.12796
Kaidi Xu
Shaokai Ye, Kailu Wu, Mu Zhou, Yunfei Yang, Sia huat Tan, Kaidi Xu, Jiebo Song, Chenglong Bao, Kaisheng Ma
Light-weight Calibrator: a Separable Component for Unsupervised Domain Adaptation
Accepted by CVPR2020
null
null
null
cs.CV cs.LG eess.IV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Existing domain adaptation methods aim at learning features that can be generalized among domains. These methods commonly require to update source classifier to adapt to the target domain and do not properly handle the trade off between the source domain and the target domain. In this work, instead of training a clas...
[ { "created": "Thu, 28 Nov 2019 17:18:03 GMT", "version": "v1" }, { "created": "Fri, 28 Feb 2020 14:12:02 GMT", "version": "v2" } ]
2020-03-02
[ [ "Ye", "Shaokai", "" ], [ "Wu", "Kailu", "" ], [ "Zhou", "Mu", "" ], [ "Yang", "Yunfei", "" ], [ "Tan", "Sia huat", "" ], [ "Xu", "Kaidi", "" ], [ "Song", "Jiebo", "" ], [ "Bao", "Chenglong", ...
Existing domain adaptation methods aim at learning features that can be generalized among domains. These methods commonly require to update source classifier to adapt to the target domain and do not properly handle the trade off between the source domain and the target domain. In this work, instead of training a classi...
2402.03204
Qichen Wang
Tianzhang Cai, Qichen Wang, Shuai Zhang, \"Ozlem Tu\u{g}fe Demir, Cicek Cavdar
Multi-agent Reinforcement Learning for Energy Saving in Multi-Cell Massive MIMO Systems
null
null
null
null
cs.IT cs.AI cs.LG math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We develop a multi-agent reinforcement learning (MARL) algorithm to minimize the total energy consumption of multiple massive MIMO (multiple-input multiple-output) base stations (BSs) in a multi-cell network while preserving the overall quality-of-service (QoS) by making decisions on the multi-level advanced sleep mo...
[ { "created": "Mon, 5 Feb 2024 17:15:00 GMT", "version": "v1" } ]
2024-02-06
[ [ "Cai", "Tianzhang", "" ], [ "Wang", "Qichen", "" ], [ "Zhang", "Shuai", "" ], [ "Demir", "Özlem Tuğfe", "" ], [ "Cavdar", "Cicek", "" ] ]
We develop a multi-agent reinforcement learning (MARL) algorithm to minimize the total energy consumption of multiple massive MIMO (multiple-input multiple-output) base stations (BSs) in a multi-cell network while preserving the overall quality-of-service (QoS) by making decisions on the multi-level advanced sleep mode...
2002.07262
Norman Danner
Norman Danner and Daniel R. Licata
Denotational semantics as a foundation for cost recurrence extraction for functional languages
Revisions, mostly minor, some more discussion of related work. To appear in Journal of Functional Programming
Journal of Functional Programming 32, 2022
10.1017/S095679682200003X
null
cs.PL
http://creativecommons.org/licenses/by/4.0/
A standard informal method for analyzing the asymptotic complexity of a program is to extract a recurrence that describes its cost in terms of the size of its input, and then to compute a closed-form upper bound on that recurrence. We give a formal account of that method for functional programs in a higher-order lang...
[ { "created": "Mon, 17 Feb 2020 21:36:38 GMT", "version": "v1" }, { "created": "Thu, 4 Mar 2021 14:18:57 GMT", "version": "v2" }, { "created": "Fri, 20 May 2022 15:50:23 GMT", "version": "v3" } ]
2022-08-09
[ [ "Danner", "Norman", "" ], [ "Licata", "Daniel R.", "" ] ]
A standard informal method for analyzing the asymptotic complexity of a program is to extract a recurrence that describes its cost in terms of the size of its input, and then to compute a closed-form upper bound on that recurrence. We give a formal account of that method for functional programs in a higher-order langua...
2203.16401
Jakob Grahn
Jakob Grahn, Filippo Maria Bianchi
Recognition of polar lows in Sentinel-1 SAR images with deep learning
11 pages (+4 supplementary), 11 figures (+2 supplementary)
null
10.1109/TGRS.2022.3204886
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we explore the possibility of detecting polar lows in C-band SAR images by means of deep learning. Specifically, we introduce a novel dataset consisting of Sentinel-1 images divided into two classes, representing the presence and absence of a maritime mesocyclone, respectively. The dataset is construct...
[ { "created": "Wed, 30 Mar 2022 15:32:39 GMT", "version": "v1" }, { "created": "Tue, 26 Apr 2022 08:59:08 GMT", "version": "v2" }, { "created": "Thu, 11 Aug 2022 13:33:16 GMT", "version": "v3" }, { "created": "Mon, 5 Sep 2022 11:23:19 GMT", "version": "v4" } ]
2022-09-09
[ [ "Grahn", "Jakob", "" ], [ "Bianchi", "Filippo Maria", "" ] ]
In this paper, we explore the possibility of detecting polar lows in C-band SAR images by means of deep learning. Specifically, we introduce a novel dataset consisting of Sentinel-1 images divided into two classes, representing the presence and absence of a maritime mesocyclone, respectively. The dataset is constructed...
0810.1018
Alexander Russell
Cristopher Moore and Alexander Russell
A simple constant-probability RP reduction from NP to Parity P
null
null
null
null
cs.CC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The proof of Toda's celebrated theorem that the polynomial hierarchy is contained in $\P^{# P}$ relies on the fact that, under mild technical conditions on the complexity class $C$, we have $\exists C \subset BP \cdot \oplus C$. More concretely, there is a randomized reduction which transforms nonempty sets and the e...
[ { "created": "Mon, 6 Oct 2008 17:23:06 GMT", "version": "v1" } ]
2008-10-07
[ [ "Moore", "Cristopher", "" ], [ "Russell", "Alexander", "" ] ]
The proof of Toda's celebrated theorem that the polynomial hierarchy is contained in $\P^{# P}$ relies on the fact that, under mild technical conditions on the complexity class $C$, we have $\exists C \subset BP \cdot \oplus C$. More concretely, there is a randomized reduction which transforms nonempty sets and the emp...
2408.03669
Jie Peng
Jie Peng, Runlin Lei, Zhewei Wei
Beyond Over-smoothing: Uncovering the Trainability Challenges in Deep Graph Neural Networks
CIKM2024
null
10.1145/3627673.3679776
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The drastic performance degradation of Graph Neural Networks (GNNs) as the depth of the graph propagation layers exceeds 8-10 is widely attributed to a phenomenon of Over-smoothing. Although recent research suggests that Over-smoothing may not be the dominant reason for such a performance degradation, they have not p...
[ { "created": "Wed, 7 Aug 2024 10:24:59 GMT", "version": "v1" } ]
2024-08-08
[ [ "Peng", "Jie", "" ], [ "Lei", "Runlin", "" ], [ "Wei", "Zhewei", "" ] ]
The drastic performance degradation of Graph Neural Networks (GNNs) as the depth of the graph propagation layers exceeds 8-10 is widely attributed to a phenomenon of Over-smoothing. Although recent research suggests that Over-smoothing may not be the dominant reason for such a performance degradation, they have not pro...
1805.09938
Francesco Leofante
Francesco Leofante, Nina Narodytska, Luca Pulina, Armando Tacchella
Automated Verification of Neural Networks: Advances, Challenges and Perspectives
null
null
null
null
cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Neural networks are one of the most investigated and widely used techniques in Machine Learning. In spite of their success, they still find limited application in safety- and security-related contexts, wherein assurance about networks' performances must be provided. In the recent past, automated reasoning techniques ...
[ { "created": "Fri, 25 May 2018 00:19:57 GMT", "version": "v1" } ]
2018-05-28
[ [ "Leofante", "Francesco", "" ], [ "Narodytska", "Nina", "" ], [ "Pulina", "Luca", "" ], [ "Tacchella", "Armando", "" ] ]
Neural networks are one of the most investigated and widely used techniques in Machine Learning. In spite of their success, they still find limited application in safety- and security-related contexts, wherein assurance about networks' performances must be provided. In the recent past, automated reasoning techniques ha...
2205.15561
Pei Liu
Pei Liu, Yanjie Zhao, Haipeng Cai, Mattia Fazzini, John Grundy, and Li Li
Automatically Detecting API-induced Compatibility Issues in Android Apps: A Comparative Analysis (Replicability Study)
null
null
10.1145/3533767.3534407
ISSTA '22 Proceedings of the 31st ACM SIGSOFT International Symposium on Software Testing and Analysis
cs.SE
http://creativecommons.org/licenses/by/4.0/
Fragmentation is a serious problem in the Android ecosystem. This problem is mainly caused by the fast evolution of the system itself and the various customizations independently maintained by different smartphone manufacturers. Many efforts have attempted to mitigate its impact via approaches to automatically pinpoi...
[ { "created": "Tue, 31 May 2022 06:39:39 GMT", "version": "v1" } ]
2022-06-01
[ [ "Liu", "Pei", "" ], [ "Zhao", "Yanjie", "" ], [ "Cai", "Haipeng", "" ], [ "Fazzini", "Mattia", "" ], [ "Grundy", "John", "" ], [ "Li", "Li", "" ] ]
Fragmentation is a serious problem in the Android ecosystem. This problem is mainly caused by the fast evolution of the system itself and the various customizations independently maintained by different smartphone manufacturers. Many efforts have attempted to mitigate its impact via approaches to automatically pinpoint...
2303.04150
Hui Bai
Hui Bai and Ran Cheng and Yaochu Jin
Evolutionary Reinforcement Learning: A Survey
null
INTELLIGENT COMPUTING, 21 Apr 2023
10.34133/icomputing.0025
null
cs.NE cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Reinforcement learning (RL) is a machine learning approach that trains agents to maximize cumulative rewards through interactions with environments. The integration of RL with deep learning has recently resulted in impressive achievements in a wide range of challenging tasks, including board games, arcade games, and ...
[ { "created": "Tue, 7 Mar 2023 01:38:42 GMT", "version": "v1" }, { "created": "Fri, 10 Mar 2023 07:21:10 GMT", "version": "v2" }, { "created": "Wed, 12 Apr 2023 01:56:52 GMT", "version": "v3" }, { "created": "Wed, 30 Aug 2023 01:47:53 GMT", "version": "v4" } ]
2023-08-31
[ [ "Bai", "Hui", "" ], [ "Cheng", "Ran", "" ], [ "Jin", "Yaochu", "" ] ]
Reinforcement learning (RL) is a machine learning approach that trains agents to maximize cumulative rewards through interactions with environments. The integration of RL with deep learning has recently resulted in impressive achievements in a wide range of challenging tasks, including board games, arcade games, and ro...
1902.10659
Kevin Carlberg
Philip A. Etter, Kevin T. Carlberg
Online adaptive basis refinement and compression for reduced-order models via vector-space sieving
null
null
10.1016/j.cma.2020.112931
null
cs.NA
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In many applications, projection-based reduced-order models (ROMs) have demonstrated the ability to provide rapid approximate solutions to high-fidelity full-order models (FOMs). However, there is no a priori assurance that these approximate solutions are accurate; their accuracy depends on the ability of the low-dim...
[ { "created": "Wed, 27 Feb 2019 17:47:51 GMT", "version": "v1" }, { "created": "Mon, 29 Apr 2019 22:14:16 GMT", "version": "v2" } ]
2020-04-22
[ [ "Etter", "Philip A.", "" ], [ "Carlberg", "Kevin T.", "" ] ]
In many applications, projection-based reduced-order models (ROMs) have demonstrated the ability to provide rapid approximate solutions to high-fidelity full-order models (FOMs). However, there is no a priori assurance that these approximate solutions are accurate; their accuracy depends on the ability of the low-dimen...
cs/0408022
Gerard Chang Jennhwa
Guey-Yun Chang, Gerard J. Chang and Gen-Huey Chen
Diagnosabilities of regular networks
26 pages
null
null
NCTS/TPE-Math Technical Report 2004-013
cs.NI
null
In this paper, we study diagnosabilities of multiprocessor systems under two diagnosis models: the PMC model and the comparison model. In each model, we further consider two different diagnosis strategies: the precise diagnosis strategy proposed by Preparata et al. and the pessimistic diagnosis strategy proposed by F...
[ { "created": "Mon, 9 Aug 2004 08:28:41 GMT", "version": "v1" } ]
2007-05-23
[ [ "Chang", "Guey-Yun", "" ], [ "Chang", "Gerard J.", "" ], [ "Chen", "Gen-Huey", "" ] ]
In this paper, we study diagnosabilities of multiprocessor systems under two diagnosis models: the PMC model and the comparison model. In each model, we further consider two different diagnosis strategies: the precise diagnosis strategy proposed by Preparata et al. and the pessimistic diagnosis strategy proposed by Fri...
2405.14766
Joshua Harris
Joshua Harris, Timothy Laurence, Leo Loman, Fan Grayson, Toby Nonnenmacher, Harry Long, Loes WalsGriffith, Amy Douglas, Holly Fountain, Stelios Georgiou, Jo Hardstaff, Kathryn Hopkins, Y-Ling Chi, Galena Kuyumdzhieva, Lesley Larkin, Samuel Collins, Hamish Mohammed, Thomas Finnie, Luke Hounsome and Steven Riley
Evaluating Large Language Models for Public Health Classification and Extraction Tasks
33 pages. Feedback and comments are highly appreciated
null
null
null
cs.CL cs.LG
http://creativecommons.org/licenses/by/4.0/
Advances in Large Language Models (LLMs) have led to significant interest in their potential to support human experts across a range of domains, including public health. In this work we present automated evaluations of LLMs for public health tasks involving the classification and extraction of free text. We combine s...
[ { "created": "Thu, 23 May 2024 16:33:18 GMT", "version": "v1" } ]
2024-05-24
[ [ "Harris", "Joshua", "" ], [ "Laurence", "Timothy", "" ], [ "Loman", "Leo", "" ], [ "Grayson", "Fan", "" ], [ "Nonnenmacher", "Toby", "" ], [ "Long", "Harry", "" ], [ "WalsGriffith", "Loes", "" ], [ ...
Advances in Large Language Models (LLMs) have led to significant interest in their potential to support human experts across a range of domains, including public health. In this work we present automated evaluations of LLMs for public health tasks involving the classification and extraction of free text. We combine six...
2309.04581
Yi-Ling Qiao
Yi-Ling Qiao, Alexander Gao, Yiran Xu, Yue Feng, Jia-Bin Huang, Ming C. Lin
Dynamic Mesh-Aware Radiance Fields
ICCV 2023
null
null
null
cs.GR cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Embedding polygonal mesh assets within photorealistic Neural Radience Fields (NeRF) volumes, such that they can be rendered and their dynamics simulated in a physically consistent manner with the NeRF, is under-explored from the system perspective of integrating NeRF into the traditional graphics pipeline. This paper...
[ { "created": "Fri, 8 Sep 2023 20:18:18 GMT", "version": "v1" } ]
2023-09-12
[ [ "Qiao", "Yi-Ling", "" ], [ "Gao", "Alexander", "" ], [ "Xu", "Yiran", "" ], [ "Feng", "Yue", "" ], [ "Huang", "Jia-Bin", "" ], [ "Lin", "Ming C.", "" ] ]
Embedding polygonal mesh assets within photorealistic Neural Radience Fields (NeRF) volumes, such that they can be rendered and their dynamics simulated in a physically consistent manner with the NeRF, is under-explored from the system perspective of integrating NeRF into the traditional graphics pipeline. This paper d...
1907.00151
Yi Liao
Yi Liao, Yasheng Wang, Qun Liu, Xin Jiang
GPT-based Generation for Classical Chinese Poetry
null
null
null
null
cs.CL cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present a simple yet effective method for generating high quality classical Chinese poetry with Generative Pre-trained Language Model (GPT). The method adopts a simple GPT model, without using any human crafted rules or features, or designing any additional neural components. While the proposed model learns to gen...
[ { "created": "Sat, 29 Jun 2019 06:04:48 GMT", "version": "v1" }, { "created": "Tue, 2 Jul 2019 14:18:55 GMT", "version": "v2" }, { "created": "Wed, 3 Jul 2019 12:55:06 GMT", "version": "v3" }, { "created": "Fri, 12 Jul 2019 05:44:58 GMT", "version": "v4" }, { "cre...
2019-09-06
[ [ "Liao", "Yi", "" ], [ "Wang", "Yasheng", "" ], [ "Liu", "Qun", "" ], [ "Jiang", "Xin", "" ] ]
We present a simple yet effective method for generating high quality classical Chinese poetry with Generative Pre-trained Language Model (GPT). The method adopts a simple GPT model, without using any human crafted rules or features, or designing any additional neural components. While the proposed model learns to gener...
2006.11194
Yan Zhou
Yasmeen Alufaisan, Laura R. Marusich, Jonathan Z. Bakdash, Yan Zhou, Murat Kantarcioglu
Does Explainable Artificial Intelligence Improve Human Decision-Making?
null
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Explainable AI provides insight into the "why" for model predictions, offering potential for users to better understand and trust a model, and to recognize and correct AI predictions that are incorrect. Prior research on human and explainable AI interactions has focused on measures such as interpretability, trust, an...
[ { "created": "Fri, 19 Jun 2020 15:46:13 GMT", "version": "v1" } ]
2020-06-22
[ [ "Alufaisan", "Yasmeen", "" ], [ "Marusich", "Laura R.", "" ], [ "Bakdash", "Jonathan Z.", "" ], [ "Zhou", "Yan", "" ], [ "Kantarcioglu", "Murat", "" ] ]
Explainable AI provides insight into the "why" for model predictions, offering potential for users to better understand and trust a model, and to recognize and correct AI predictions that are incorrect. Prior research on human and explainable AI interactions has focused on measures such as interpretability, trust, and ...
2310.06112
Shaopeng Fu
Shaopeng Fu, Di Wang
Theoretical Analysis of Robust Overfitting for Wide DNNs: An NTK Approach
In Twelfth International Conference on Learning Representations (ICLR 2024)
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Adversarial training (AT) is a canonical method for enhancing the robustness of deep neural networks (DNNs). However, recent studies empirically demonstrated that it suffers from robust overfitting, i.e., a long time AT can be detrimental to the robustness of DNNs. This paper presents a theoretical explanation of rob...
[ { "created": "Mon, 9 Oct 2023 19:40:25 GMT", "version": "v1" }, { "created": "Sun, 4 Feb 2024 16:31:50 GMT", "version": "v2" } ]
2024-02-06
[ [ "Fu", "Shaopeng", "" ], [ "Wang", "Di", "" ] ]
Adversarial training (AT) is a canonical method for enhancing the robustness of deep neural networks (DNNs). However, recent studies empirically demonstrated that it suffers from robust overfitting, i.e., a long time AT can be detrimental to the robustness of DNNs. This paper presents a theoretical explanation of robus...
2202.03947
Robert Penicka
Robert Penicka and Davide Scaramuzza
Minimum-Time Quadrotor Waypoint Flight in Cluttered Environments
Accepted in IEEE Robotics and Automation Letters
null
null
null
cs.RO
http://creativecommons.org/licenses/by/4.0/
We tackle the problem of planning a minimum-time trajectory for a quadrotor over a sequence of specified waypoints in the presence of obstacles while exploiting the full quadrotor dynamics. This problem is crucial for autonomous search and rescue and drone racing scenarios but was, so far, unaddressed by the robotics...
[ { "created": "Tue, 8 Feb 2022 15:54:19 GMT", "version": "v1" } ]
2022-02-09
[ [ "Penicka", "Robert", "" ], [ "Scaramuzza", "Davide", "" ] ]
We tackle the problem of planning a minimum-time trajectory for a quadrotor over a sequence of specified waypoints in the presence of obstacles while exploiting the full quadrotor dynamics. This problem is crucial for autonomous search and rescue and drone racing scenarios but was, so far, unaddressed by the robotics c...
2406.19296
Adnan Aijaz
Freddy Tuxworth, Adnan Aijaz
Vehicle-to-Grid Technology meets Packetized Energy Management: A Co-Simulation Study
Accepted for publication in the International Conference on Power Systems and Electrical Technology (PSET) 2024
null
null
null
cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The global energy landscape is experiencing a significant transformation driven by increased awareness of climate change and rapid technological advancements in renewable energy and electric vehicles (EVs). Packetized energy management (PEM) schemes are gaining attention as a potential solution for power management f...
[ { "created": "Thu, 27 Jun 2024 16:10:55 GMT", "version": "v1" } ]
2024-06-28
[ [ "Tuxworth", "Freddy", "" ], [ "Aijaz", "Adnan", "" ] ]
The global energy landscape is experiencing a significant transformation driven by increased awareness of climate change and rapid technological advancements in renewable energy and electric vehicles (EVs). Packetized energy management (PEM) schemes are gaining attention as a potential solution for power management for...
2103.12012
Sangeeta Yadav
Sangeeta Yadav, Asif Khan
SP Async:Single Source Shortest Path in Asynchronous Mode on MPI
null
null
null
null
cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Finding single source shortest path is a very ubiquitous problem. But with the increasing size of large datasets in important application like social network data-mining, network topology determination-efficient parallelization of these techniques is needed to match the need of really large graphs. We present a new I...
[ { "created": "Mon, 22 Mar 2021 17:02:06 GMT", "version": "v1" } ]
2021-03-23
[ [ "Yadav", "Sangeeta", "" ], [ "Khan", "Asif", "" ] ]
Finding single source shortest path is a very ubiquitous problem. But with the increasing size of large datasets in important application like social network data-mining, network topology determination-efficient parallelization of these techniques is needed to match the need of really large graphs. We present a new Int...
2008.06281
Priyadarshi Mukherjee
Priyadarshi Mukherjee, Souhir Lajnef, Ioannis Krikidis
MIMO SWIPT Systems with Power Amplifier Nonlinearities and Memory Effects
5 pages, 6 figures. To appear in IEEE Wireless Communications Letters
null
null
null
cs.IT eess.SP math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this letter, we study the impact of nonlinear high power amplifier (HPA) on simultaneous wireless information and power transfer (SWIPT), for a point-to-point multiple-input multiple-output communication system. We derive the rate-energy (RE) region by taking into account the HPA nonlinearities and its associated ...
[ { "created": "Fri, 14 Aug 2020 10:21:35 GMT", "version": "v1" } ]
2020-08-17
[ [ "Mukherjee", "Priyadarshi", "" ], [ "Lajnef", "Souhir", "" ], [ "Krikidis", "Ioannis", "" ] ]
In this letter, we study the impact of nonlinear high power amplifier (HPA) on simultaneous wireless information and power transfer (SWIPT), for a point-to-point multiple-input multiple-output communication system. We derive the rate-energy (RE) region by taking into account the HPA nonlinearities and its associated me...
1801.08052
Daniel Kaltenthaler
Daniel Kaltenthaler and Johannes-Y. Lohrer
The Historic Development of the Zooarchaeological Database OssoBook and the xBook Framework for Scientific Databases
null
null
null
null
cs.DB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this technical report, we describe the historic development of the zooarchaeological database OssoBook and the resulting framework xBook, a generic infrastructure for distributed, relational data management that is mainly designed for the needs of scientific data. We describe the concepts of the architecture and i...
[ { "created": "Wed, 24 Jan 2018 16:07:39 GMT", "version": "v1" } ]
2018-02-12
[ [ "Kaltenthaler", "Daniel", "" ], [ "Lohrer", "Johannes-Y.", "" ] ]
In this technical report, we describe the historic development of the zooarchaeological database OssoBook and the resulting framework xBook, a generic infrastructure for distributed, relational data management that is mainly designed for the needs of scientific data. We describe the concepts of the architecture and its...
2101.04667
Emmanouil Vasileios Vlatakis Gkaragkounis
Angeliki Giannou, Emmanouil-Vasileios Vlatakis-Gkaragkounis, Panayotis Mertikopoulos
Survival of the strictest: Stable and unstable equilibria under regularized learning with partial information
null
null
null
null
cs.GT cs.LG cs.MA math.OC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we examine the Nash equilibrium convergence properties of no-regret learning in general N-player games. For concreteness, we focus on the archetypal follow the regularized leader (FTRL) family of algorithms, and we consider the full spectrum of uncertainty that the players may encounter - from noisy, o...
[ { "created": "Tue, 12 Jan 2021 18:55:11 GMT", "version": "v1" }, { "created": "Thu, 4 Feb 2021 14:45:34 GMT", "version": "v2" } ]
2021-02-05
[ [ "Giannou", "Angeliki", "" ], [ "Vlatakis-Gkaragkounis", "Emmanouil-Vasileios", "" ], [ "Mertikopoulos", "Panayotis", "" ] ]
In this paper, we examine the Nash equilibrium convergence properties of no-regret learning in general N-player games. For concreteness, we focus on the archetypal follow the regularized leader (FTRL) family of algorithms, and we consider the full spectrum of uncertainty that the players may encounter - from noisy, ora...
1910.07772
Florian Wirthm\"uller
Florian Wirthm\"uller, Julian Schlechtriemen, Jochen Hipp and Manfred Reichert
Teaching Vehicles to Anticipate: A Systematic Study on Probabilistic Behavior Prediction Using Large Data Sets
the paper has been accepted for publication in IEEE Transcations on Intelligent Transportation Systems (T-ITS) 16 pages 13 figures 12 tables
null
10.1109/TITS.2020.3002070
null
cs.LG cs.RO stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
By observing their environment as well as other traffic participants, humans are enabled to drive road vehicles safely. Vehicle passengers, however, perceive a notable difference between non-experienced and experienced drivers. In particular, they may get the impression that the latter ones anticipate what will happe...
[ { "created": "Thu, 17 Oct 2019 08:42:40 GMT", "version": "v1" }, { "created": "Tue, 21 Jan 2020 13:46:33 GMT", "version": "v2" }, { "created": "Thu, 9 Apr 2020 15:14:48 GMT", "version": "v3" }, { "created": "Wed, 10 Jun 2020 15:43:01 GMT", "version": "v4" } ]
2020-06-11
[ [ "Wirthmüller", "Florian", "" ], [ "Schlechtriemen", "Julian", "" ], [ "Hipp", "Jochen", "" ], [ "Reichert", "Manfred", "" ] ]
By observing their environment as well as other traffic participants, humans are enabled to drive road vehicles safely. Vehicle passengers, however, perceive a notable difference between non-experienced and experienced drivers. In particular, they may get the impression that the latter ones anticipate what will happen ...
1308.5269
Hamed Mesri
Hamed Yousefi Mesri
A comparative analysis of methods for estimating axon diameter using DWI
The work needs more details. The complete work will be submitted later
null
null
null
cs.NE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The importance of studying the brain microstructure is described and the existing and state of the art non-invasive methods for the investigation of the brain microstructure using Diffusion Weighted Magnetic Resonance Imaging (DWI) is studied. In the next step, Cramer-Rao Lower Bound (CRLB) analysis is described and ...
[ { "created": "Sat, 24 Aug 2013 00:57:26 GMT", "version": "v1" }, { "created": "Tue, 12 Nov 2013 02:48:33 GMT", "version": "v2" } ]
2013-11-13
[ [ "Mesri", "Hamed Yousefi", "" ] ]
The importance of studying the brain microstructure is described and the existing and state of the art non-invasive methods for the investigation of the brain microstructure using Diffusion Weighted Magnetic Resonance Imaging (DWI) is studied. In the next step, Cramer-Rao Lower Bound (CRLB) analysis is described and ut...
2008.10518
Ajinkya Jain
Ajinkya Jain and Rudolf Lioutikov and Caleb Chuck and Scott Niekum
ScrewNet: Category-Independent Articulation Model Estimation From Depth Images Using Screw Theory
Presented at ICRA'21. Project webpage: https://pearl-utexas.github.io/ScrewNet/
null
null
null
cs.RO cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Robots in human environments will need to interact with a wide variety of articulated objects such as cabinets, drawers, and dishwashers while assisting humans in performing day-to-day tasks. Existing methods either require objects to be textured or need to know the articulation model category a priori for estimating...
[ { "created": "Mon, 24 Aug 2020 15:41:23 GMT", "version": "v1" }, { "created": "Tue, 2 Mar 2021 21:01:42 GMT", "version": "v2" }, { "created": "Mon, 19 Jul 2021 22:55:24 GMT", "version": "v3" } ]
2021-07-21
[ [ "Jain", "Ajinkya", "" ], [ "Lioutikov", "Rudolf", "" ], [ "Chuck", "Caleb", "" ], [ "Niekum", "Scott", "" ] ]
Robots in human environments will need to interact with a wide variety of articulated objects such as cabinets, drawers, and dishwashers while assisting humans in performing day-to-day tasks. Existing methods either require objects to be textured or need to know the articulation model category a priori for estimating t...
2310.10909
Zihan Qiu
Zihan Qiu, Zhen Liu, Shuicheng Yan, Shanghang Zhang, Jie Fu
Heterogenous Memory Augmented Neural Networks
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
It has been shown that semi-parametric methods, which combine standard neural networks with non-parametric components such as external memory modules and data retrieval, are particularly helpful in data scarcity and out-of-distribution (OOD) scenarios. However, existing semi-parametric methods mostly depend on indepe...
[ { "created": "Tue, 17 Oct 2023 01:05:28 GMT", "version": "v1" } ]
2023-10-18
[ [ "Qiu", "Zihan", "" ], [ "Liu", "Zhen", "" ], [ "Yan", "Shuicheng", "" ], [ "Zhang", "Shanghang", "" ], [ "Fu", "Jie", "" ] ]
It has been shown that semi-parametric methods, which combine standard neural networks with non-parametric components such as external memory modules and data retrieval, are particularly helpful in data scarcity and out-of-distribution (OOD) scenarios. However, existing semi-parametric methods mostly depend on independ...
1509.03706
Pradeep Kr. Banerjee
Pradeep Kr. Banerjee, Virgil Griffith
Synergy, Redundancy and Common Information
16 pages, 3 figures
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We consider the problem of decomposing the total mutual information conveyed by a pair of predictor random variables about a target random variable into redundant, unique and synergistic contributions. We focus on the relationship between "redundant information" and the more familiar information-theoretic notions of ...
[ { "created": "Sat, 12 Sep 2015 05:28:43 GMT", "version": "v1" } ]
2015-09-15
[ [ "Banerjee", "Pradeep Kr.", "" ], [ "Griffith", "Virgil", "" ] ]
We consider the problem of decomposing the total mutual information conveyed by a pair of predictor random variables about a target random variable into redundant, unique and synergistic contributions. We focus on the relationship between "redundant information" and the more familiar information-theoretic notions of "c...
1805.04217
Yuan Fu
Yuan Fu, Hu Wang, and Meng-Zhu Yang
An Adaptive Population Size Differential Evolution with Novel Mutation Strategy for Constrained Optimization
null
null
null
null
cs.NE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Differential evolution (DE) has competitive performance on constrained optimization problems (COPs), which targets at searching for global optimal solution without violating the constraints. Generally, researchers pay more attention on avoiding violating the constraints than better objective function value. To achiev...
[ { "created": "Fri, 11 May 2018 01:28:35 GMT", "version": "v1" } ]
2018-05-14
[ [ "Fu", "Yuan", "" ], [ "Wang", "Hu", "" ], [ "Yang", "Meng-Zhu", "" ] ]
Differential evolution (DE) has competitive performance on constrained optimization problems (COPs), which targets at searching for global optimal solution without violating the constraints. Generally, researchers pay more attention on avoiding violating the constraints than better objective function value. To achieve ...
2307.11228
Enayat Ullah
Enayat Ullah, Raman Arora
From Adaptive Query Release to Machine Unlearning
Accepted to ICML 2023
null
null
null
cs.LG stat.ML
http://creativecommons.org/licenses/by/4.0/
We formalize the problem of machine unlearning as design of efficient unlearning algorithms corresponding to learning algorithms which perform a selection of adaptive queries from structured query classes. We give efficient unlearning algorithms for linear and prefix-sum query classes. As applications, we show that u...
[ { "created": "Thu, 20 Jul 2023 20:46:39 GMT", "version": "v1" } ]
2023-07-24
[ [ "Ullah", "Enayat", "" ], [ "Arora", "Raman", "" ] ]
We formalize the problem of machine unlearning as design of efficient unlearning algorithms corresponding to learning algorithms which perform a selection of adaptive queries from structured query classes. We give efficient unlearning algorithms for linear and prefix-sum query classes. As applications, we show that unl...
1905.06480
Rafael S. Gon\c{c}alves
Rafael S. Gon\c{c}alves, Martin J. O'Connor, Marcos Mart\'inez-Romero, Attila L. Egyedi, Debra Willrett, John Graybeal and Mark A. Musen
The CEDAR Workbench: An Ontology-Assisted Environment for Authoring Metadata that Describe Scientific Experiments
null
null
10.1007/978-3-319-68204-4_10
null
cs.DB cs.DL
http://creativecommons.org/licenses/by/4.0/
The Center for Expanded Data Annotation and Retrieval (CEDAR) aims to revolutionize the way that metadata describing scientific experiments are authored. The software we have developed--the CEDAR Workbench--is a suite of Web-based tools and REST APIs that allows users to construct metadata templates, to fill in templ...
[ { "created": "Thu, 16 May 2019 00:19:49 GMT", "version": "v1" } ]
2019-05-17
[ [ "Gonçalves", "Rafael S.", "" ], [ "O'Connor", "Martin J.", "" ], [ "Martínez-Romero", "Marcos", "" ], [ "Egyedi", "Attila L.", "" ], [ "Willrett", "Debra", "" ], [ "Graybeal", "John", "" ], [ "Musen", "Mark A."...
The Center for Expanded Data Annotation and Retrieval (CEDAR) aims to revolutionize the way that metadata describing scientific experiments are authored. The software we have developed--the CEDAR Workbench--is a suite of Web-based tools and REST APIs that allows users to construct metadata templates, to fill in templat...
2111.08956
Cong Luong Nguyen
Nguyen Thi Thanh Van, Huy T. Nguyen, Nguyen Cong Luong, Ngo Manh Tien, Dusit Niyato, and Dong In Kim
Intelligence Reflecting Surface-Aided Integrated Data and Energy Networking Coexisting D2D Communications
null
null
null
null
cs.NI
http://creativecommons.org/publicdomain/zero/1.0/
In this paper, we consider an integrated data and energy network and D2D communication coexistence (DED2D) system. The DED2D system allows a base station (BS) to transfer data to information-demanded users (IUs) and energy to energy-demanded users (EUs), i.e., using a time-fraction-based information and energy transf...
[ { "created": "Wed, 17 Nov 2021 08:01:41 GMT", "version": "v1" } ]
2021-11-18
[ [ "Van", "Nguyen Thi Thanh", "" ], [ "Nguyen", "Huy T.", "" ], [ "Luong", "Nguyen Cong", "" ], [ "Tien", "Ngo Manh", "" ], [ "Niyato", "Dusit", "" ], [ "Kim", "Dong In", "" ] ]
In this paper, we consider an integrated data and energy network and D2D communication coexistence (DED2D) system. The DED2D system allows a base station (BS) to transfer data to information-demanded users (IUs) and energy to energy-demanded users (EUs), i.e., using a time-fraction-based information and energy transfer...
2406.10481
Shuyu Dong
Shuyu Dong, Mich\`ele Sebag, Kento Uemura, Akito Fujii, Shuang Chang, Yusuke Koyanagi, Koji Maruhashi
DCDILP: a distributed learning method for large-scale causal structure learning
null
null
null
null
cs.LG math.OC stat.ME
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper presents a novel approach to causal discovery through a divide-and-conquer framework. By decomposing the problem into smaller subproblems defined on Markov blankets, the proposed DCDILP method first explores in parallel the local causal graphs of these subproblems. However, this local discovery phase encou...
[ { "created": "Sat, 15 Jun 2024 03:17:48 GMT", "version": "v1" } ]
2024-06-18
[ [ "Dong", "Shuyu", "" ], [ "Sebag", "Michèle", "" ], [ "Uemura", "Kento", "" ], [ "Fujii", "Akito", "" ], [ "Chang", "Shuang", "" ], [ "Koyanagi", "Yusuke", "" ], [ "Maruhashi", "Koji", "" ] ]
This paper presents a novel approach to causal discovery through a divide-and-conquer framework. By decomposing the problem into smaller subproblems defined on Markov blankets, the proposed DCDILP method first explores in parallel the local causal graphs of these subproblems. However, this local discovery phase encount...
1912.01639
Sariel Har-Peled
Timothy M. Chan and Sariel Har-Peled and Mitchell Jones
Optimal Algorithms for Geometric Centers and Depth
This paper is a merge of two conference papers that were published sixteen years apart. The first paper appeared in SODA 2004, and the second paper (which can be viewed as an applications paper of the first paper) appeared in SoCG 2020
null
null
null
cs.CG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
$\renewcommand{\Re}{\mathbb{R}}$ We develop a general randomized technique for solving "implic it" linear programming problems, where the collection of constraints are defined implicitly by an underlying ground set of elements. In many cases, the structure of the implicitly defined constraints can be exploited in ord...
[ { "created": "Tue, 3 Dec 2019 19:24:58 GMT", "version": "v1" }, { "created": "Tue, 25 May 2021 18:28:34 GMT", "version": "v2" }, { "created": "Thu, 23 Dec 2021 18:03:56 GMT", "version": "v3" } ]
2021-12-24
[ [ "Chan", "Timothy M.", "" ], [ "Har-Peled", "Sariel", "" ], [ "Jones", "Mitchell", "" ] ]
$\renewcommand{\Re}{\mathbb{R}}$ We develop a general randomized technique for solving "implic it" linear programming problems, where the collection of constraints are defined implicitly by an underlying ground set of elements. In many cases, the structure of the implicitly defined constraints can be exploited in order...
1707.00408
Zhedong Zheng
Zhedong Zheng, Liang Zheng, Yi Yang
Pedestrian Alignment Network for Large-scale Person Re-identification
null
null
10.1109/TCSVT.2018.2873599
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Person re-identification (person re-ID) is mostly viewed as an image retrieval problem. This task aims to search a query person in a large image pool. In practice, person re-ID usually adopts automatic detectors to obtain cropped pedestrian images. However, this process suffers from two types of detector errors: exce...
[ { "created": "Mon, 3 Jul 2017 05:48:54 GMT", "version": "v1" } ]
2019-06-24
[ [ "Zheng", "Zhedong", "" ], [ "Zheng", "Liang", "" ], [ "Yang", "Yi", "" ] ]
Person re-identification (person re-ID) is mostly viewed as an image retrieval problem. This task aims to search a query person in a large image pool. In practice, person re-ID usually adopts automatic detectors to obtain cropped pedestrian images. However, this process suffers from two types of detector errors: excess...