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2309.03249
Surajit Ghosh
Surajit Ghosh, Archita Mallick, Anuva Chowdhury, Kounik De Sarkar
Graph Theory Applications in Advanced Geospatial Research
null
null
null
null
cs.LG cs.CE cs.CY physics.geo-ph
http://creativecommons.org/licenses/by/4.0/
Geospatial sciences include a wide range of applications, from environmental monitoring transportation to infrastructure planning, as well as location-based analysis and services. Graph theory algorithms in mathematics have emerged as indispensable tools in these domains due to their capability to model and analyse s...
[ { "created": "Wed, 6 Sep 2023 15:47:18 GMT", "version": "v1" }, { "created": "Mon, 9 Oct 2023 16:20:33 GMT", "version": "v2" } ]
2023-10-10
[ [ "Ghosh", "Surajit", "" ], [ "Mallick", "Archita", "" ], [ "Chowdhury", "Anuva", "" ], [ "De Sarkar", "Kounik", "" ] ]
Geospatial sciences include a wide range of applications, from environmental monitoring transportation to infrastructure planning, as well as location-based analysis and services. Graph theory algorithms in mathematics have emerged as indispensable tools in these domains due to their capability to model and analyse spa...
2302.06185
Jianyun Xu
Shihao Su, Jianyun Xu, Huanyu Wang, Zhenwei Miao, Xin Zhan, Dayang Hao, Xi Li
PUPS: Point Cloud Unified Panoptic Segmentation
accepted by AAAI2023
null
null
null
cs.CV
http://creativecommons.org/licenses/by-nc-nd/4.0/
Point cloud panoptic segmentation is a challenging task that seeks a holistic solution for both semantic and instance segmentation to predict groupings of coherent points. Previous approaches treat semantic and instance segmentation as surrogate tasks, and they either use clustering methods or bounding boxes to gathe...
[ { "created": "Mon, 13 Feb 2023 08:42:41 GMT", "version": "v1" }, { "created": "Tue, 28 Feb 2023 03:19:18 GMT", "version": "v2" } ]
2023-03-01
[ [ "Su", "Shihao", "" ], [ "Xu", "Jianyun", "" ], [ "Wang", "Huanyu", "" ], [ "Miao", "Zhenwei", "" ], [ "Zhan", "Xin", "" ], [ "Hao", "Dayang", "" ], [ "Li", "Xi", "" ] ]
Point cloud panoptic segmentation is a challenging task that seeks a holistic solution for both semantic and instance segmentation to predict groupings of coherent points. Previous approaches treat semantic and instance segmentation as surrogate tasks, and they either use clustering methods or bounding boxes to gather ...
2111.07608
Yufei Chen
Junhao Zhou, Yufei Chen, Chao Shen, Yang Zhang
Property Inference Attacks Against GANs
To Appear in NDSS 2022
null
null
null
cs.CR cs.AI cs.LG stat.ML
http://creativecommons.org/licenses/by/4.0/
While machine learning (ML) has made tremendous progress during the past decade, recent research has shown that ML models are vulnerable to various security and privacy attacks. So far, most of the attacks in this field focus on discriminative models, represented by classifiers. Meanwhile, little attention has been p...
[ { "created": "Mon, 15 Nov 2021 08:57:00 GMT", "version": "v1" } ]
2021-11-16
[ [ "Zhou", "Junhao", "" ], [ "Chen", "Yufei", "" ], [ "Shen", "Chao", "" ], [ "Zhang", "Yang", "" ] ]
While machine learning (ML) has made tremendous progress during the past decade, recent research has shown that ML models are vulnerable to various security and privacy attacks. So far, most of the attacks in this field focus on discriminative models, represented by classifiers. Meanwhile, little attention has been pai...
1905.06626
Frances Cooper
Frances Cooper and David Manlove
Two-sided profile-based optimality in the stable marriage problem
40 pages including appendix, 16 figures, 6 tables
null
null
null
cs.DS
http://creativecommons.org/licenses/by/4.0/
We study the problem of finding "fair" stable matchings in the Stable Marriage problem with Incomplete lists (SMI). In particular, we seek stable matchings that are optimal with respect to profile, which is a vector that indicates the number of agents who have their first-, second-, third-choice partner, etc. In a ra...
[ { "created": "Thu, 16 May 2019 09:53:23 GMT", "version": "v1" }, { "created": "Wed, 12 Feb 2020 15:49:09 GMT", "version": "v2" }, { "created": "Fri, 11 Sep 2020 07:03:23 GMT", "version": "v3" } ]
2020-09-14
[ [ "Cooper", "Frances", "" ], [ "Manlove", "David", "" ] ]
We study the problem of finding "fair" stable matchings in the Stable Marriage problem with Incomplete lists (SMI). In particular, we seek stable matchings that are optimal with respect to profile, which is a vector that indicates the number of agents who have their first-, second-, third-choice partner, etc. In a rank...
1912.07497
Michael Mirkin
Michael Mirkin, Yan Ji, Jonathan Pang, Ariah Klages-Mundt, Ittay Eyal and Ari Juels
BDoS: Blockchain Denial of Service
null
null
null
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Proof-of-work (PoW) cryptocurrency blockchains like Bitcoin secure vast amounts of money. Their operators, called miners, expend resources to generate blocks and receive monetary rewards for their effort. Blockchains are, in principle, attractive targets for Denial-of-Service (DoS) attacks: There is fierce competitio...
[ { "created": "Mon, 16 Dec 2019 16:55:14 GMT", "version": "v1" }, { "created": "Wed, 18 Dec 2019 21:23:34 GMT", "version": "v2" }, { "created": "Thu, 30 Jan 2020 14:05:32 GMT", "version": "v3" }, { "created": "Wed, 4 Nov 2020 21:48:52 GMT", "version": "v4" } ]
2020-11-06
[ [ "Mirkin", "Michael", "" ], [ "Ji", "Yan", "" ], [ "Pang", "Jonathan", "" ], [ "Klages-Mundt", "Ariah", "" ], [ "Eyal", "Ittay", "" ], [ "Juels", "Ari", "" ] ]
Proof-of-work (PoW) cryptocurrency blockchains like Bitcoin secure vast amounts of money. Their operators, called miners, expend resources to generate blocks and receive monetary rewards for their effort. Blockchains are, in principle, attractive targets for Denial-of-Service (DoS) attacks: There is fierce competition ...
1908.09788
Farid Ghareh Mohammadi
Farid Ghareh Mohammadi, M. Hadi Amini, and Hamid R. Arabnia
An Introduction to Advanced Machine Learning : Meta Learning Algorithms, Applications and Promises
17 pages, 9 figures. arXiv admin note: text overlap with arXiv:1902.08438 by other authors
null
null
null
cs.LG stat.ML
http://creativecommons.org/licenses/by/4.0/
In [1, 2], we have explored the theoretical aspects of feature extraction optimization processes for solving largescale problems and overcoming machine learning limitations. Majority of optimization algorithms that have been introduced in [1, 2] guarantee the optimal performance of supervised learning, given offline ...
[ { "created": "Mon, 26 Aug 2019 16:42:33 GMT", "version": "v1" } ]
2019-08-28
[ [ "Mohammadi", "Farid Ghareh", "" ], [ "Amini", "M. Hadi", "" ], [ "Arabnia", "Hamid R.", "" ] ]
In [1, 2], we have explored the theoretical aspects of feature extraction optimization processes for solving largescale problems and overcoming machine learning limitations. Majority of optimization algorithms that have been introduced in [1, 2] guarantee the optimal performance of supervised learning, given offline an...
1301.0775
Mohammad Nozari Zarmehri
Mohammad Nozari Zarmehri and Ana Aguiar
Supporting Sensing Application in Vehicular Networks
7 pages, 9 figures, 2 tables
ACM MobiCom Workshop on Challenged Networks, 2012
null
null
cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This research aims at using vehicular ad-hoc networks as infra-structure for an urban cyber-physical system in order to gather data about a city. In this scenario, all nodes are data sources and there is a gateway as ultimate destination for all packets. Because of the volatility of the network connections and uncert...
[ { "created": "Fri, 4 Jan 2013 17:25:01 GMT", "version": "v1" } ]
2013-01-07
[ [ "Zarmehri", "Mohammad Nozari", "" ], [ "Aguiar", "Ana", "" ] ]
This research aims at using vehicular ad-hoc networks as infra-structure for an urban cyber-physical system in order to gather data about a city. In this scenario, all nodes are data sources and there is a gateway as ultimate destination for all packets. Because of the volatility of the network connections and uncertai...
2111.11525
Geoffrey Driessel
Geoffrey van Driessel, Vincent Francois-Lavet
Component Transfer Learning for Deep RL Based on Abstract Representations
Workshop paper NeurIPS 2021
null
null
null
cs.LG cs.AI
http://creativecommons.org/licenses/by/4.0/
In this work we investigate a specific transfer learning approach for deep reinforcement learning in the context where the internal dynamics between two tasks are the same but the visual representations differ. We learn a low-dimensional encoding of the environment, meant to capture summarizing abstractions, from whi...
[ { "created": "Mon, 22 Nov 2021 20:48:38 GMT", "version": "v1" } ]
2021-11-24
[ [ "van Driessel", "Geoffrey", "" ], [ "Francois-Lavet", "Vincent", "" ] ]
In this work we investigate a specific transfer learning approach for deep reinforcement learning in the context where the internal dynamics between two tasks are the same but the visual representations differ. We learn a low-dimensional encoding of the environment, meant to capture summarizing abstractions, from which...
1910.11637
Daniele Giunchi
Daniele Giunchi, Stuart james, Donald Degraen, Anthony Steed
Mixing realities for sketch retrieval in Virtual Reality
10 pages
null
null
null
cs.HC cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Drawing tools for Virtual Reality (VR) enable users to model 3D designs from within the virtual environment itself. These tools employ sketching and sculpting techniques known from desktop-based interfaces and apply them to hand-based controller interaction. While these techniques allow for mid-air sketching of basic...
[ { "created": "Fri, 25 Oct 2019 11:52:25 GMT", "version": "v1" }, { "created": "Tue, 5 Nov 2019 09:58:24 GMT", "version": "v2" } ]
2019-11-06
[ [ "Giunchi", "Daniele", "" ], [ "james", "Stuart", "" ], [ "Degraen", "Donald", "" ], [ "Steed", "Anthony", "" ] ]
Drawing tools for Virtual Reality (VR) enable users to model 3D designs from within the virtual environment itself. These tools employ sketching and sculpting techniques known from desktop-based interfaces and apply them to hand-based controller interaction. While these techniques allow for mid-air sketching of basic s...
2011.01710
Guang Lin
Guang Lin, Jianhai Zhang, Yuxi Liu, Tianyang Gao, Wanzeng Kong, Xu Lei, Tao Qiu
BCGGAN: Ballistocardiogram artifact removal in simultaneous EEG-fMRI using generative adversarial network
null
Journal of Neuroscience Methods, Volume 371, 2022, 109498
10.1016/j.jneumeth.2022.109498
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Due to its advantages of high temporal and spatial resolution, the technology of simultaneous electroencephalogram-functional magnetic resonance imaging (EEG-fMRI) acquisition and analysis has attracted much attention, and has been widely used in various research fields of brain science. However, during the fMRI of t...
[ { "created": "Tue, 3 Nov 2020 13:54:01 GMT", "version": "v1" }, { "created": "Wed, 4 Nov 2020 01:39:34 GMT", "version": "v2" }, { "created": "Tue, 29 Aug 2023 06:39:04 GMT", "version": "v3" }, { "created": "Wed, 30 Aug 2023 05:08:47 GMT", "version": "v4" } ]
2023-09-01
[ [ "Lin", "Guang", "" ], [ "Zhang", "Jianhai", "" ], [ "Liu", "Yuxi", "" ], [ "Gao", "Tianyang", "" ], [ "Kong", "Wanzeng", "" ], [ "Lei", "Xu", "" ], [ "Qiu", "Tao", "" ] ]
Due to its advantages of high temporal and spatial resolution, the technology of simultaneous electroencephalogram-functional magnetic resonance imaging (EEG-fMRI) acquisition and analysis has attracted much attention, and has been widely used in various research fields of brain science. However, during the fMRI of the...
2405.02466
Heng Jin
Heng Jin and Chaoyu Zhang and Shanghao Shi and Wenjing Lou and Y. Thomas Hou
ProFLingo: A Fingerprinting-based Intellectual Property Protection Scheme for Large Language Models
This is the author's pre-print version of the work. It is posted here for your personal use. Not for redistribution
null
null
null
cs.CR cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Large language models (LLMs) have attracted significant attention in recent years. Due to their "Large" nature, training LLMs from scratch consumes immense computational resources. Since several major players in the artificial intelligence (AI) field have open-sourced their original LLMs, an increasing number of indi...
[ { "created": "Fri, 3 May 2024 20:00:40 GMT", "version": "v1" }, { "created": "Wed, 26 Jun 2024 16:22:43 GMT", "version": "v2" } ]
2024-06-27
[ [ "Jin", "Heng", "" ], [ "Zhang", "Chaoyu", "" ], [ "Shi", "Shanghao", "" ], [ "Lou", "Wenjing", "" ], [ "Hou", "Y. Thomas", "" ] ]
Large language models (LLMs) have attracted significant attention in recent years. Due to their "Large" nature, training LLMs from scratch consumes immense computational resources. Since several major players in the artificial intelligence (AI) field have open-sourced their original LLMs, an increasing number of indivi...
2112.15329
Sung Min Park
Sung Min Park, Kuo-An Wei, Kai Xiao, Jerry Li, Aleksander Madry
On Distinctive Properties of Universal Perturbations
null
null
null
null
cs.LG cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We identify properties of universal adversarial perturbations (UAPs) that distinguish them from standard adversarial perturbations. Specifically, we show that targeted UAPs generated by projected gradient descent exhibit two human-aligned properties: semantic locality and spatial invariance, which standard targeted a...
[ { "created": "Fri, 31 Dec 2021 07:35:04 GMT", "version": "v1" } ]
2022-01-03
[ [ "Park", "Sung Min", "" ], [ "Wei", "Kuo-An", "" ], [ "Xiao", "Kai", "" ], [ "Li", "Jerry", "" ], [ "Madry", "Aleksander", "" ] ]
We identify properties of universal adversarial perturbations (UAPs) that distinguish them from standard adversarial perturbations. Specifically, we show that targeted UAPs generated by projected gradient descent exhibit two human-aligned properties: semantic locality and spatial invariance, which standard targeted adv...
1708.00308
Igor Melnyk
Ramesh Nallapati, Igor Melnyk, Abhishek Kumar and Bowen Zhou
SenGen: Sentence Generating Neural Variational Topic Model
null
null
null
null
cs.CL cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present a new topic model that generates documents by sampling a topic for one whole sentence at a time, and generating the words in the sentence using an RNN decoder that is conditioned on the topic of the sentence. We argue that this novel formalism will help us not only visualize and model the topical discourse...
[ { "created": "Tue, 1 Aug 2017 13:31:24 GMT", "version": "v1" } ]
2017-08-03
[ [ "Nallapati", "Ramesh", "" ], [ "Melnyk", "Igor", "" ], [ "Kumar", "Abhishek", "" ], [ "Zhou", "Bowen", "" ] ]
We present a new topic model that generates documents by sampling a topic for one whole sentence at a time, and generating the words in the sentence using an RNN decoder that is conditioned on the topic of the sentence. We argue that this novel formalism will help us not only visualize and model the topical discourse s...
2207.11900
Jiang Li
Jiang Li, Xiaoping Wang, Guoqing Lv, Zhigang Zeng
GA2MIF: Graph and Attention Based Two-Stage Multi-Source Information Fusion for Conversational Emotion Detection
Accepted by IEEE Transactions on Affective Computing
null
10.1109/TAFFC.2023.3261279
null
cs.MM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Multimodal Emotion Recognition in Conversation (ERC) plays an influential role in the field of human-computer interaction and conversational robotics since it can motivate machines to provide empathetic services. Multimodal data modeling is an up-and-coming research area in recent years, which is inspired by human ca...
[ { "created": "Mon, 25 Jul 2022 04:22:41 GMT", "version": "v1" }, { "created": "Sat, 6 Aug 2022 21:53:02 GMT", "version": "v2" }, { "created": "Mon, 12 Sep 2022 13:11:17 GMT", "version": "v3" }, { "created": "Wed, 22 Mar 2023 02:51:19 GMT", "version": "v4" }, { "cr...
2023-11-23
[ [ "Li", "Jiang", "" ], [ "Wang", "Xiaoping", "" ], [ "Lv", "Guoqing", "" ], [ "Zeng", "Zhigang", "" ] ]
Multimodal Emotion Recognition in Conversation (ERC) plays an influential role in the field of human-computer interaction and conversational robotics since it can motivate machines to provide empathetic services. Multimodal data modeling is an up-and-coming research area in recent years, which is inspired by human capa...
2404.10454
Meriam Zribi
Meriam Zribi, Paolo Pagliuca, Francesca Pitolli
A Computer Vision-Based Quality Assessment Technique for the automatic control of consumables for analytical laboratories
31 pages, 13 figures, 10 tables
null
null
null
cs.CV cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The rapid growth of the Industry 4.0 paradigm is increasing the pressure to develop effective automated monitoring systems. Artificial Intelligence (AI) is a convenient tool to improve the efficiency of industrial processes while reducing errors and waste. In fact, it allows the use of real-time data to increase the ...
[ { "created": "Tue, 16 Apr 2024 10:50:16 GMT", "version": "v1" } ]
2024-04-17
[ [ "Zribi", "Meriam", "" ], [ "Pagliuca", "Paolo", "" ], [ "Pitolli", "Francesca", "" ] ]
The rapid growth of the Industry 4.0 paradigm is increasing the pressure to develop effective automated monitoring systems. Artificial Intelligence (AI) is a convenient tool to improve the efficiency of industrial processes while reducing errors and waste. In fact, it allows the use of real-time data to increase the ef...
1411.2577
Ilya Razenshteyn
Alexandr Andoni, Robert Krauthgamer, Ilya Razenshteyn
Sketching and Embedding are Equivalent for Norms
33 pages, an extended abstract appeared in the proceedings of the 47th ACM Symposium on Theory of Computing (STOC 2015); changes in v2: added quantitative bounds for the main results, preliminaries section with necessary definitions and facts has been added; v3: several clarifications, including a section on th...
null
null
null
cs.DS cs.CC math.FA
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
An outstanding open question posed by Guha and Indyk in 2006 asks to characterize metric spaces in which distances can be estimated using efficient sketches. Specifically, we say that a sketching algorithm is efficient if it achieves constant approximation using constant sketch size. A well-known result of Indyk (J. ...
[ { "created": "Mon, 10 Nov 2014 20:42:51 GMT", "version": "v1" }, { "created": "Mon, 20 Apr 2015 13:02:08 GMT", "version": "v2" }, { "created": "Wed, 15 Feb 2017 15:03:49 GMT", "version": "v3" } ]
2017-02-16
[ [ "Andoni", "Alexandr", "" ], [ "Krauthgamer", "Robert", "" ], [ "Razenshteyn", "Ilya", "" ] ]
An outstanding open question posed by Guha and Indyk in 2006 asks to characterize metric spaces in which distances can be estimated using efficient sketches. Specifically, we say that a sketching algorithm is efficient if it achieves constant approximation using constant sketch size. A well-known result of Indyk (J. AC...
1805.06298
Hidetoshi Furukawa
Hidetoshi Furukawa
SAVERS: SAR ATR with Verification Support Based on Convolutional Neural Network
Technical Report, 6 pages, 8 figures, 5 tables, Copyright(C)2018 IEICE. arXiv admin note: substantial text overlap with arXiv:1801.08558
IEICE Technical Report, vol.118, no.28, SANE2018-5, pp.23-28, May 2018
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We propose a new convolutional neural network (CNN) which performs coarse and fine segmentation for end-to-end synthetic aperture radar (SAR) automatic target recognition (ATR) system. In recent years, many CNNs for SAR ATR using deep learning have been proposed, but most of them classify target classes from fixed si...
[ { "created": "Mon, 14 May 2018 18:03:35 GMT", "version": "v1" } ]
2018-05-17
[ [ "Furukawa", "Hidetoshi", "" ] ]
We propose a new convolutional neural network (CNN) which performs coarse and fine segmentation for end-to-end synthetic aperture radar (SAR) automatic target recognition (ATR) system. In recent years, many CNNs for SAR ATR using deep learning have been proposed, but most of them classify target classes from fixed size...
2405.05398
Rafael Orozco
Rafael Orozco, Ali Siahkoohi, Mathias Louboutin, Felix J. Herrmann
ASPIRE: Iterative Amortized Posterior Inference for Bayesian Inverse Problems
null
null
null
null
cs.LG stat.ML
http://creativecommons.org/licenses/by/4.0/
Due to their uncertainty quantification, Bayesian solutions to inverse problems are the framework of choice in applications that are risk averse. These benefits come at the cost of computations that are in general, intractable. New advances in machine learning and variational inference (VI) have lowered the computati...
[ { "created": "Wed, 8 May 2024 20:03:12 GMT", "version": "v1" } ]
2024-05-10
[ [ "Orozco", "Rafael", "" ], [ "Siahkoohi", "Ali", "" ], [ "Louboutin", "Mathias", "" ], [ "Herrmann", "Felix J.", "" ] ]
Due to their uncertainty quantification, Bayesian solutions to inverse problems are the framework of choice in applications that are risk averse. These benefits come at the cost of computations that are in general, intractable. New advances in machine learning and variational inference (VI) have lowered the computation...
2012.13635
Samy Badreddine
Samy Badreddine and Artur d'Avila Garcez and Luciano Serafini and Michael Spranger
Logic Tensor Networks
68 pages, 28 figures, 6 tables
Artificial Intelligence, Volume 303, February 2022, 103649
10.1016/j.artint.2021.103649
null
cs.AI cs.LG
http://creativecommons.org/licenses/by/4.0/
Artificial Intelligence agents are required to learn from their surroundings and to reason about the knowledge that has been learned in order to make decisions. While state-of-the-art learning from data typically uses sub-symbolic distributed representations, reasoning is normally useful at a higher level of abstract...
[ { "created": "Fri, 25 Dec 2020 22:30:18 GMT", "version": "v1" }, { "created": "Thu, 14 Jan 2021 07:37:47 GMT", "version": "v2" }, { "created": "Sun, 17 Jan 2021 01:28:44 GMT", "version": "v3" }, { "created": "Thu, 23 Dec 2021 04:14:25 GMT", "version": "v4" } ]
2021-12-24
[ [ "Badreddine", "Samy", "" ], [ "Garcez", "Artur d'Avila", "" ], [ "Serafini", "Luciano", "" ], [ "Spranger", "Michael", "" ] ]
Artificial Intelligence agents are required to learn from their surroundings and to reason about the knowledge that has been learned in order to make decisions. While state-of-the-art learning from data typically uses sub-symbolic distributed representations, reasoning is normally useful at a higher level of abstractio...
2403.13289
Han-Hung Lee
Han-Hung Lee, Manolis Savva, Angel X. Chang
Text-to-3D Shape Generation
null
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Recent years have seen an explosion of work and interest in text-to-3D shape generation. Much of the progress is driven by advances in 3D representations, large-scale pretraining and representation learning for text and image data enabling generative AI models, and differentiable rendering. Computational systems that...
[ { "created": "Wed, 20 Mar 2024 04:03:44 GMT", "version": "v1" } ]
2024-03-21
[ [ "Lee", "Han-Hung", "" ], [ "Savva", "Manolis", "" ], [ "Chang", "Angel X.", "" ] ]
Recent years have seen an explosion of work and interest in text-to-3D shape generation. Much of the progress is driven by advances in 3D representations, large-scale pretraining and representation learning for text and image data enabling generative AI models, and differentiable rendering. Computational systems that c...
2005.13681
Elizabeth Salesky
Elizabeth Salesky and Alan W Black
Phone Features Improve Speech Translation
Accepted to ACL2020
null
null
null
cs.CL cs.SD eess.AS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
End-to-end models for speech translation (ST) more tightly couple speech recognition (ASR) and machine translation (MT) than a traditional cascade of separate ASR and MT models, with simpler model architectures and the potential for reduced error propagation. Their performance is often assumed to be superior, though ...
[ { "created": "Wed, 27 May 2020 22:05:10 GMT", "version": "v1" } ]
2020-05-29
[ [ "Salesky", "Elizabeth", "" ], [ "Black", "Alan W", "" ] ]
End-to-end models for speech translation (ST) more tightly couple speech recognition (ASR) and machine translation (MT) than a traditional cascade of separate ASR and MT models, with simpler model architectures and the potential for reduced error propagation. Their performance is often assumed to be superior, though in...
2005.10463
Haoneng Luo
Haoneng Luo, Shiliang Zhang, Ming Lei, Lei Xie
Simplified Self-Attention for Transformer-based End-to-End Speech Recognition
Accepted to SLT 2021
null
null
null
cs.SD cs.CL eess.AS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Transformer models have been introduced into end-to-end speech recognition with state-of-the-art performance on various tasks owing to their superiority in modeling long-term dependencies. However, such improvements are usually obtained through the use of very large neural networks. Transformer models mainly include ...
[ { "created": "Thu, 21 May 2020 04:55:59 GMT", "version": "v1" }, { "created": "Tue, 17 Nov 2020 09:58:44 GMT", "version": "v2" } ]
2020-11-18
[ [ "Luo", "Haoneng", "" ], [ "Zhang", "Shiliang", "" ], [ "Lei", "Ming", "" ], [ "Xie", "Lei", "" ] ]
Transformer models have been introduced into end-to-end speech recognition with state-of-the-art performance on various tasks owing to their superiority in modeling long-term dependencies. However, such improvements are usually obtained through the use of very large neural networks. Transformer models mainly include tw...
1104.1905
Carsten Lemmen
Carsten Lemmen and Detlef Gronenborn and Kai W. Wirtz
A simulation of the Neolithic transition in Western Eurasia
Accepted Author Manuscript version accepted for publication in Journal of Archaeological Science. A definitive version will be subsequently published in the Journal of Archaological Science
Journal of Archaeological Science Vol 38 (12), pp. 3459-3470, 2011
10.1016/j.jas.2011.08.008
null
cs.MA q-bio.PE
http://creativecommons.org/licenses/by-nc-sa/3.0/
Farming and herding were introduced to Europe from the Near East and Anatolia; there are, however, considerable arguments about the mechanisms of this transition. Were it people who moved and outplaced the indigenous hunter- gatherer groups or admixed with them? Or was it just material and information that moved-the ...
[ { "created": "Mon, 11 Apr 2011 11:15:04 GMT", "version": "v1" }, { "created": "Fri, 12 Aug 2011 08:14:41 GMT", "version": "v2" } ]
2011-11-08
[ [ "Lemmen", "Carsten", "" ], [ "Gronenborn", "Detlef", "" ], [ "Wirtz", "Kai W.", "" ] ]
Farming and herding were introduced to Europe from the Near East and Anatolia; there are, however, considerable arguments about the mechanisms of this transition. Were it people who moved and outplaced the indigenous hunter- gatherer groups or admixed with them? Or was it just material and information that moved-the Ne...
2304.13681
Eric Ming Chen
Eric Ming Chen, Sidhanth Holalkere, Ruyu Yan, Kai Zhang, Abe Davis
Ray Conditioning: Trading Photo-consistency for Photo-realism in Multi-view Image Generation
ICCV 2023 paper. Project page at https://ray-cond.github.io/
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Multi-view image generation attracts particular attention these days due to its promising 3D-related applications, e.g., image viewpoint editing. Most existing methods follow a paradigm where a 3D representation is first synthesized, and then rendered into 2D images to ensure photo-consistency across viewpoints. Howe...
[ { "created": "Wed, 26 Apr 2023 16:54:10 GMT", "version": "v1" }, { "created": "Mon, 4 Sep 2023 23:02:18 GMT", "version": "v2" } ]
2023-09-06
[ [ "Chen", "Eric Ming", "" ], [ "Holalkere", "Sidhanth", "" ], [ "Yan", "Ruyu", "" ], [ "Zhang", "Kai", "" ], [ "Davis", "Abe", "" ] ]
Multi-view image generation attracts particular attention these days due to its promising 3D-related applications, e.g., image viewpoint editing. Most existing methods follow a paradigm where a 3D representation is first synthesized, and then rendered into 2D images to ensure photo-consistency across viewpoints. Howeve...
2206.07344
Pitchayagan Temniranrat
Kantip Kiratiratanapruk, Pitchayagan Temniranrat, Wasin Sinthupinyo, Sanparith Marukatat, and Sujin Patarapuwadol
Automatic Detection of Rice Disease in Images of Various Leaf Sizes
28 pages, 13 figures
null
null
null
cs.CV cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Fast, accurate and affordable rice disease detection method is required to assist rice farmers tackling equipment and expertise shortages problems. In this paper, we focused on the solution using computer vision technique to detect rice diseases from rice field photograph images. Dealing with images took in real-usag...
[ { "created": "Wed, 15 Jun 2022 07:56:41 GMT", "version": "v1" } ]
2022-06-16
[ [ "Kiratiratanapruk", "Kantip", "" ], [ "Temniranrat", "Pitchayagan", "" ], [ "Sinthupinyo", "Wasin", "" ], [ "Marukatat", "Sanparith", "" ], [ "Patarapuwadol", "Sujin", "" ] ]
Fast, accurate and affordable rice disease detection method is required to assist rice farmers tackling equipment and expertise shortages problems. In this paper, we focused on the solution using computer vision technique to detect rice diseases from rice field photograph images. Dealing with images took in real-usage ...
1708.02531
Yuming Shen
Yuming Shen, Li Liu, Ling Shao, Jingkuan Song
Deep Binaries: Encoding Semantic-Rich Cues for Efficient Textual-Visual Cross Retrieval
Accepted by ICCV 2017 as a conference paper
null
null
null
cs.CV cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Cross-modal hashing is usually regarded as an effective technique for large-scale textual-visual cross retrieval, where data from different modalities are mapped into a shared Hamming space for matching. Most of the traditional textual-visual binary encoding methods only consider holistic image representations and fa...
[ { "created": "Tue, 8 Aug 2017 15:46:16 GMT", "version": "v1" } ]
2017-08-09
[ [ "Shen", "Yuming", "" ], [ "Liu", "Li", "" ], [ "Shao", "Ling", "" ], [ "Song", "Jingkuan", "" ] ]
Cross-modal hashing is usually regarded as an effective technique for large-scale textual-visual cross retrieval, where data from different modalities are mapped into a shared Hamming space for matching. Most of the traditional textual-visual binary encoding methods only consider holistic image representations and fail...
1107.1676
Riccardo Albertoni
Monica De Martino, Riccardo Albertoni
A multilingual/multicultural semantic-based approach to improve Data Sharing in an SDI for Nature Conservation
null
International Journal of Spatial Data Infrastructures Research, 2011, Vol.6, 206-233
10.2902/1725-0463.2011.06.art10
null
cs.DL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The paper proposes an approach to transcend multicultural and multilingual barriers in the use and reuse of geographical data at the European level. The approach aims at sharing scientific terms in the field of nature conservation with the goal of assisting different user communities with metadata compilation and inf...
[ { "created": "Fri, 8 Jul 2011 16:50:38 GMT", "version": "v1" } ]
2011-07-11
[ [ "De Martino", "Monica", "" ], [ "Albertoni", "Riccardo", "" ] ]
The paper proposes an approach to transcend multicultural and multilingual barriers in the use and reuse of geographical data at the European level. The approach aims at sharing scientific terms in the field of nature conservation with the goal of assisting different user communities with metadata compilation and infor...
2112.04812
Jung-Su Ha
Jung-Su Ha, Danny Driess, Marc Toussaint
Deep Visual Constraints: Neural Implicit Models for Manipulation Planning from Visual Input
IEEE Robotics and Automation Letters (RA-L) 2022
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Manipulation planning is the problem of finding a sequence of robot configurations that involves interactions with objects in the scene, e.g., grasping and placing an object, or more general tool-use. To achieve such interactions, traditional approaches require hand-engineering of object representations and interacti...
[ { "created": "Thu, 9 Dec 2021 10:14:13 GMT", "version": "v1" }, { "created": "Sun, 30 Jan 2022 23:57:14 GMT", "version": "v2" }, { "created": "Thu, 28 Jul 2022 20:59:34 GMT", "version": "v3" } ]
2022-08-01
[ [ "Ha", "Jung-Su", "" ], [ "Driess", "Danny", "" ], [ "Toussaint", "Marc", "" ] ]
Manipulation planning is the problem of finding a sequence of robot configurations that involves interactions with objects in the scene, e.g., grasping and placing an object, or more general tool-use. To achieve such interactions, traditional approaches require hand-engineering of object representations and interaction...
1303.1829
Fernand Meyer
Fernand Meyer
Watersheds on edge or node weighted graphs "par l'exemple"
21 pages
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Watersheds have been defined both for node and edge weighted graphs. We show that they are identical: for each edge (resp.\ node) weighted graph exists a node (resp. edge) weighted graph with the same minima and catchment basin.
[ { "created": "Thu, 7 Mar 2013 21:15:29 GMT", "version": "v1" } ]
2013-03-11
[ [ "Meyer", "Fernand", "" ] ]
Watersheds have been defined both for node and edge weighted graphs. We show that they are identical: for each edge (resp.\ node) weighted graph exists a node (resp. edge) weighted graph with the same minima and catchment basin.
2311.17124
Corneliu Cofaru
Corneliu Cofaru and Johan Loeckx
A knowledge-driven AutoML architecture
null
null
null
null
cs.LG cs.AI cs.SE
http://creativecommons.org/licenses/by-sa/4.0/
This paper proposes a knowledge-driven AutoML architecture for pipeline and deep feature synthesis. The main goal is to render the AutoML process explainable and to leverage domain knowledge in the synthesis of pipelines and features. The architecture explores several novel ideas: first, the construction of pipelines...
[ { "created": "Tue, 28 Nov 2023 14:31:38 GMT", "version": "v1" } ]
2023-11-30
[ [ "Cofaru", "Corneliu", "" ], [ "Loeckx", "Johan", "" ] ]
This paper proposes a knowledge-driven AutoML architecture for pipeline and deep feature synthesis. The main goal is to render the AutoML process explainable and to leverage domain knowledge in the synthesis of pipelines and features. The architecture explores several novel ideas: first, the construction of pipelines a...
1208.3001
Zhili Chen Dr.
Zhili Chen, Liusheng Huang, Wei Yang, Peng Meng, and Haibo Miao
More than Word Frequencies: Authorship Attribution via Natural Frequency Zoned Word Distribution Analysis
27pages, 7figures, submited to Artificial Intelligence
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
With such increasing popularity and availability of digital text data, authorships of digital texts can not be taken for granted due to the ease of copying and parsing. This paper presents a new text style analysis called natural frequency zoned word distribution analysis (NFZ-WDA), and then a basic authorship attrib...
[ { "created": "Wed, 15 Aug 2012 00:53:39 GMT", "version": "v1" } ]
2012-08-16
[ [ "Chen", "Zhili", "" ], [ "Huang", "Liusheng", "" ], [ "Yang", "Wei", "" ], [ "Meng", "Peng", "" ], [ "Miao", "Haibo", "" ] ]
With such increasing popularity and availability of digital text data, authorships of digital texts can not be taken for granted due to the ease of copying and parsing. This paper presents a new text style analysis called natural frequency zoned word distribution analysis (NFZ-WDA), and then a basic authorship attribut...
2103.00657
Eric Pryzant
E. Pryzant, Q. Deng, B. Mei, E. Shrestha
Achieving Competitive Play Through Bottom-Up Approach in Semantic Segmentation
null
null
null
null
cs.CV
http://creativecommons.org/licenses/by-nc-nd/4.0/
With the renaissance of neural networks, object detection has slowly shifted from a bottom-up recognition problem to a top-down approach. Best in class algorithms enumerate a near-complete list of objects and classify each into object/not object. In this paper, we show that strong performance can still be achieved us...
[ { "created": "Sun, 28 Feb 2021 23:14:13 GMT", "version": "v1" } ]
2021-03-02
[ [ "Pryzant", "E.", "" ], [ "Deng", "Q.", "" ], [ "Mei", "B.", "" ], [ "Shrestha", "E.", "" ] ]
With the renaissance of neural networks, object detection has slowly shifted from a bottom-up recognition problem to a top-down approach. Best in class algorithms enumerate a near-complete list of objects and classify each into object/not object. In this paper, we show that strong performance can still be achieved usin...
1311.4703
Tuvi Etzion
Michal Horovitz and Tuvi Etzion
Constructions of Snake-in-the-Box Codes for Rank Modulation
IEEE Transactions on Information Theory
null
null
null
cs.IT math.CO math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Snake-in-the-box code is a Gray code which is capable of detecting a single error. Gray codes are important in the context of the rank modulation scheme which was suggested recently for representing information in flash memories. For a Gray code in this scheme the codewords are permutations, two consecutive codewords...
[ { "created": "Tue, 19 Nov 2013 11:37:16 GMT", "version": "v1" }, { "created": "Wed, 26 Feb 2014 13:32:24 GMT", "version": "v2" }, { "created": "Sun, 13 Jul 2014 13:44:15 GMT", "version": "v3" }, { "created": "Sun, 14 Sep 2014 17:40:56 GMT", "version": "v4" } ]
2014-09-16
[ [ "Horovitz", "Michal", "" ], [ "Etzion", "Tuvi", "" ] ]
Snake-in-the-box code is a Gray code which is capable of detecting a single error. Gray codes are important in the context of the rank modulation scheme which was suggested recently for representing information in flash memories. For a Gray code in this scheme the codewords are permutations, two consecutive codewords a...
2111.05392
Minyoung Kim
Minyoung Kim, Timothy Hospedales
Gaussian Process Meta Few-shot Classifier Learning via Linear Discriminant Laplace Approximation
Rev1
null
null
null
cs.LG
http://creativecommons.org/licenses/by/4.0/
The meta learning few-shot classification is an emerging problem in machine learning that received enormous attention recently, where the goal is to learn a model that can quickly adapt to a new task with only a few labeled data. We consider the Bayesian Gaussian process (GP) approach, in which we meta-learn the GP p...
[ { "created": "Tue, 9 Nov 2021 20:00:16 GMT", "version": "v1" }, { "created": "Mon, 13 Dec 2021 10:30:59 GMT", "version": "v2" } ]
2021-12-14
[ [ "Kim", "Minyoung", "" ], [ "Hospedales", "Timothy", "" ] ]
The meta learning few-shot classification is an emerging problem in machine learning that received enormous attention recently, where the goal is to learn a model that can quickly adapt to a new task with only a few labeled data. We consider the Bayesian Gaussian process (GP) approach, in which we meta-learn the GP pri...
2107.09388
Parthasaarathy Sudarsanam
Parthasaarathy Sudarsanam, Archontis Politis, Konstantinos Drossos
Assessment of Self-Attention on Learned Features For Sound Event Localization and Detection
null
null
null
null
cs.SD eess.AS
http://creativecommons.org/licenses/by/4.0/
Joint sound event localization and detection (SELD) is an emerging audio signal processing task adding spatial dimensions to acoustic scene analysis and sound event detection. A popular approach to modeling SELD jointly is using convolutional recurrent neural network (CRNN) models, where CNNs learn high-level feature...
[ { "created": "Tue, 20 Jul 2021 10:12:39 GMT", "version": "v1" }, { "created": "Mon, 27 Sep 2021 09:32:34 GMT", "version": "v2" } ]
2021-09-28
[ [ "Sudarsanam", "Parthasaarathy", "" ], [ "Politis", "Archontis", "" ], [ "Drossos", "Konstantinos", "" ] ]
Joint sound event localization and detection (SELD) is an emerging audio signal processing task adding spatial dimensions to acoustic scene analysis and sound event detection. A popular approach to modeling SELD jointly is using convolutional recurrent neural network (CRNN) models, where CNNs learn high-level features ...
2405.03151
Xinye Sha
Xinye Sha
Time Series Stock Price Forecasting Based on Genetic Algorithm (GA)-Long Short-Term Memory Network (LSTM) Optimization
null
null
null
null
cs.CE cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, a time series algorithm based on Genetic Algorithm (GA) and Long Short-Term Memory Network (LSTM) optimization is used to forecast stock prices effectively, taking into account the trend of the big data era. The data are first analyzed by descriptive statistics, and then the model is built and trained ...
[ { "created": "Mon, 6 May 2024 04:04:27 GMT", "version": "v1" } ]
2024-05-07
[ [ "Sha", "Xinye", "" ] ]
In this paper, a time series algorithm based on Genetic Algorithm (GA) and Long Short-Term Memory Network (LSTM) optimization is used to forecast stock prices effectively, taking into account the trend of the big data era. The data are first analyzed by descriptive statistics, and then the model is built and trained an...
1605.02156
Massimo Cairo
Massimo Cairo and Romeo Rizzi
The Complexity of Simulation and Matrix Multiplication
Submitted. Changed in v2: This is a major rewrite of the paper. The introduction has been expanded considerably, some notation has been simplified, proofs of general results on reachability games have been moved to the appendix, more intuitive arguments for proofs have been provided, moving the formal arguments...
null
null
null
cs.CC cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Computing the simulation preorder of a given Kripke structure (i.e., a directed graph with $n$ labeled vertices) has crucial applications in model checking of temporal logic. It amounts to solving a specific two-players reachability game, called simulation game. We offer the first conditional lower bounds for this pr...
[ { "created": "Sat, 7 May 2016 08:18:31 GMT", "version": "v1" }, { "created": "Tue, 30 Aug 2016 15:51:14 GMT", "version": "v2" } ]
2016-08-31
[ [ "Cairo", "Massimo", "" ], [ "Rizzi", "Romeo", "" ] ]
Computing the simulation preorder of a given Kripke structure (i.e., a directed graph with $n$ labeled vertices) has crucial applications in model checking of temporal logic. It amounts to solving a specific two-players reachability game, called simulation game. We offer the first conditional lower bounds for this prob...
2109.09057
Yohan Jo
Yohan Jo, Haneul Yoo, JinYeong Bak, Alice Oh, Chris Reed, Eduard Hovy
Knowledge-Enhanced Evidence Retrieval for Counterargument Generation
To appear in Findings of EMNLP 2021
null
null
null
cs.CL
http://creativecommons.org/licenses/by-nc-nd/4.0/
Finding counterevidence to statements is key to many tasks, including counterargument generation. We build a system that, given a statement, retrieves counterevidence from diverse sources on the Web. At the core of this system is a natural language inference (NLI) model that determines whether a candidate sentence is...
[ { "created": "Sun, 19 Sep 2021 04:31:21 GMT", "version": "v1" } ]
2021-09-21
[ [ "Jo", "Yohan", "" ], [ "Yoo", "Haneul", "" ], [ "Bak", "JinYeong", "" ], [ "Oh", "Alice", "" ], [ "Reed", "Chris", "" ], [ "Hovy", "Eduard", "" ] ]
Finding counterevidence to statements is key to many tasks, including counterargument generation. We build a system that, given a statement, retrieves counterevidence from diverse sources on the Web. At the core of this system is a natural language inference (NLI) model that determines whether a candidate sentence is v...
1009.4898
Sanat Sarangi
Sanat Sarangi and Subrat Kar
Location Estimation with Reactive Routing in Resource Constrained Sensor Networks
6 pages, 6 figures
International Conference on Sensors and Related Networks (SENNET'09), VIT University, Vellore, India, Dec. 08-10, 2009, pp.563-567
null
null
cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Routing algorithms for wireless sensor networks can be broadly divided into two classes - proactive and reactive. Proactive routing is suitable for a network with a fixed topology. On the other hand, reactive routing is more suitable for a set of mobile nodes where routes are created on demand and there is not much t...
[ { "created": "Fri, 24 Sep 2010 17:30:56 GMT", "version": "v1" }, { "created": "Wed, 1 Aug 2012 14:28:01 GMT", "version": "v2" } ]
2012-08-02
[ [ "Sarangi", "Sanat", "" ], [ "Kar", "Subrat", "" ] ]
Routing algorithms for wireless sensor networks can be broadly divided into two classes - proactive and reactive. Proactive routing is suitable for a network with a fixed topology. On the other hand, reactive routing is more suitable for a set of mobile nodes where routes are created on demand and there is not much tim...
1011.2644
Anna Rimoldi
Anna Rimoldi and Massimiliano Sala and Enrico Bertolazzi
Do AES encryptions act randomly?
15 pages
null
null
null
cs.IT cs.CR math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The Advanced Encryption Standard (AES) is widely recognized as the most important block cipher in common use nowadays. This high assurance in AES is given by its resistance to ten years of extensive cryptanalysis, that has shown no weakness, not even any deviation from the statistical behaviour expected from a random...
[ { "created": "Thu, 11 Nov 2010 13:17:15 GMT", "version": "v1" } ]
2010-11-12
[ [ "Rimoldi", "Anna", "" ], [ "Sala", "Massimiliano", "" ], [ "Bertolazzi", "Enrico", "" ] ]
The Advanced Encryption Standard (AES) is widely recognized as the most important block cipher in common use nowadays. This high assurance in AES is given by its resistance to ten years of extensive cryptanalysis, that has shown no weakness, not even any deviation from the statistical behaviour expected from a random p...
1901.00754
Stanislav Zivny
Silvia Butti and Stanislav Zivny
Sparsification of Binary CSPs
Full version of a STACS'19 paper
SIAM Journal on Discrete Mathematics 34(1) (2020) 825-842
10.1137/19M1242446
null
cs.DS cs.DM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A cut $\varepsilon$-sparsifier of a weighted graph $G$ is a re-weighted subgraph of $G$ of (quasi)linear size that preserves the size of all cuts up to a multiplicative factor of $\varepsilon$. Since their introduction by Bencz\'ur and Karger [STOC'96], cut sparsifiers have proved extremely influential and found vari...
[ { "created": "Thu, 3 Jan 2019 14:15:10 GMT", "version": "v1" }, { "created": "Fri, 13 Dec 2019 16:19:38 GMT", "version": "v2" } ]
2020-03-25
[ [ "Butti", "Silvia", "" ], [ "Zivny", "Stanislav", "" ] ]
A cut $\varepsilon$-sparsifier of a weighted graph $G$ is a re-weighted subgraph of $G$ of (quasi)linear size that preserves the size of all cuts up to a multiplicative factor of $\varepsilon$. Since their introduction by Bencz\'ur and Karger [STOC'96], cut sparsifiers have proved extremely influential and found variou...
2007.01189
Avinash Madasu
Avinash Madasu and Vijjini Anvesh Rao
Sequential Domain Adaptation through Elastic Weight Consolidation for Sentiment Analysis
Accepted at 25th International Conference on Pattern Recognition, January 2021, Milan, Italy
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Elastic Weight Consolidation (EWC) is a technique used in overcoming catastrophic forgetting between successive tasks trained on a neural network. We use this phenomenon of information sharing between tasks for domain adaptation. Training data for tasks such as sentiment analysis (SA) may not be fairly represented ac...
[ { "created": "Thu, 2 Jul 2020 15:21:56 GMT", "version": "v1" }, { "created": "Sat, 4 Jul 2020 11:06:07 GMT", "version": "v2" }, { "created": "Sun, 19 Jul 2020 08:50:19 GMT", "version": "v3" } ]
2020-07-21
[ [ "Madasu", "Avinash", "" ], [ "Rao", "Vijjini Anvesh", "" ] ]
Elastic Weight Consolidation (EWC) is a technique used in overcoming catastrophic forgetting between successive tasks trained on a neural network. We use this phenomenon of information sharing between tasks for domain adaptation. Training data for tasks such as sentiment analysis (SA) may not be fairly represented acro...
2302.07399
Turgay Pamuklu
Anne Catherine Nguyen, Turgay Pamuklu, Aisha Syed, W. Sean Kennedy, Melike Erol-Kantarci
To Risk or Not to Risk: Learning with Risk Quantification for IoT Task Offloading in UAVs
Accepted for ICC2023
null
null
null
cs.NI cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A deep reinforcement learning technique is presented for task offloading decision-making algorithms for a multi-access edge computing (MEC) assisted unmanned aerial vehicle (UAV) network in a smart farm Internet of Things (IoT) environment. The task offloading technique uses financial concepts such as cost functions ...
[ { "created": "Tue, 14 Feb 2023 23:50:37 GMT", "version": "v1" } ]
2023-02-16
[ [ "Nguyen", "Anne Catherine", "" ], [ "Pamuklu", "Turgay", "" ], [ "Syed", "Aisha", "" ], [ "Kennedy", "W. Sean", "" ], [ "Erol-Kantarci", "Melike", "" ] ]
A deep reinforcement learning technique is presented for task offloading decision-making algorithms for a multi-access edge computing (MEC) assisted unmanned aerial vehicle (UAV) network in a smart farm Internet of Things (IoT) environment. The task offloading technique uses financial concepts such as cost functions an...
2312.05975
Ravidu Suien Rammuni Silva
Ravidu Suien Rammuni Silva, Jordan J. Bird
FM-G-CAM: A Holistic Approach for Explainable AI in Computer Vision
null
null
null
null
cs.CV cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Explainability is an aspect of modern AI that is vital for impact and usability in the real world. The main objective of this paper is to emphasise the need to understand the predictions of Computer Vision models, specifically Convolutional Neural Network (CNN) based models. Existing methods of explaining CNN predict...
[ { "created": "Sun, 10 Dec 2023 19:33:40 GMT", "version": "v1" }, { "created": "Sat, 13 Apr 2024 10:45:47 GMT", "version": "v2" } ]
2024-04-16
[ [ "Silva", "Ravidu Suien Rammuni", "" ], [ "Bird", "Jordan J.", "" ] ]
Explainability is an aspect of modern AI that is vital for impact and usability in the real world. The main objective of this paper is to emphasise the need to understand the predictions of Computer Vision models, specifically Convolutional Neural Network (CNN) based models. Existing methods of explaining CNN predictio...
2010.02415
Alexander Tong
Alexander Tong, Frederik Wenkel, Kincaid MacDonald, Smita Krishnaswamy, Guy Wolf
Data-Driven Learning of Geometric Scattering Networks
6 pages, 2 figures, 3 tables, Presented at IEEE MLSP 2021
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We propose a new graph neural network (GNN) module, based on relaxations of recently proposed geometric scattering transforms, which consist of a cascade of graph wavelet filters. Our learnable geometric scattering (LEGS) module enables adaptive tuning of the wavelets to encourage band-pass features to emerge in lear...
[ { "created": "Tue, 6 Oct 2020 01:20:27 GMT", "version": "v1" }, { "created": "Mon, 22 Feb 2021 13:03:54 GMT", "version": "v2" }, { "created": "Mon, 28 Mar 2022 16:17:03 GMT", "version": "v3" } ]
2022-03-29
[ [ "Tong", "Alexander", "" ], [ "Wenkel", "Frederik", "" ], [ "MacDonald", "Kincaid", "" ], [ "Krishnaswamy", "Smita", "" ], [ "Wolf", "Guy", "" ] ]
We propose a new graph neural network (GNN) module, based on relaxations of recently proposed geometric scattering transforms, which consist of a cascade of graph wavelet filters. Our learnable geometric scattering (LEGS) module enables adaptive tuning of the wavelets to encourage band-pass features to emerge in learne...
2310.18724
Naman Goel
Elliott Ash, Naman Goel, Nianyun Li, Claudia Marangon, Peiyao Sun
WCLD: Curated Large Dataset of Criminal Cases from Wisconsin Circuit Courts
(Forthcoming) Proceedings of the 37th Conference on Neural Information Processing Systems (NeurIPS 2023) Track on Datasets and Benchmarks
null
null
null
cs.LG cs.AI
http://creativecommons.org/licenses/by/4.0/
Machine learning based decision-support tools in criminal justice systems are subjects of intense discussions and academic research. There are important open questions about the utility and fairness of such tools. Academic researchers often rely on a few small datasets that are not sufficient to empirically study var...
[ { "created": "Sat, 28 Oct 2023 15:04:29 GMT", "version": "v1" } ]
2023-10-31
[ [ "Ash", "Elliott", "" ], [ "Goel", "Naman", "" ], [ "Li", "Nianyun", "" ], [ "Marangon", "Claudia", "" ], [ "Sun", "Peiyao", "" ] ]
Machine learning based decision-support tools in criminal justice systems are subjects of intense discussions and academic research. There are important open questions about the utility and fairness of such tools. Academic researchers often rely on a few small datasets that are not sufficient to empirically study vario...
1501.06140
Moti Medina
Guy Even and Moti Medina and Boaz Patt-Shamir
Better Online Deterministic Packet Routing on Grids
null
null
null
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We consider the following fundamental routing problem. An adversary inputs packets arbitrarily at sources, each packet with an arbitrary destination. Traffic is constrained by link capacities and buffer sizes, and packets may be dropped at any time. The goal of the routing algorithm is to maximize throughput, i.e., r...
[ { "created": "Sun, 25 Jan 2015 11:22:58 GMT", "version": "v1" } ]
2015-01-27
[ [ "Even", "Guy", "" ], [ "Medina", "Moti", "" ], [ "Patt-Shamir", "Boaz", "" ] ]
We consider the following fundamental routing problem. An adversary inputs packets arbitrarily at sources, each packet with an arbitrary destination. Traffic is constrained by link capacities and buffer sizes, and packets may be dropped at any time. The goal of the routing algorithm is to maximize throughput, i.e., rou...
1712.07487
Sebastian Sudholt
Sebastian Sudholt and Gernot Fink
Attribute CNNs for Word Spotting in Handwritten Documents
under review at IJDAR
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Word spotting has become a field of strong research interest in document image analysis over the last years. Recently, AttributeSVMs were proposed which predict a binary attribute representation. At their time, this influential method defined the state-of-the-art in segmentation-based word spotting. In this work, we ...
[ { "created": "Wed, 20 Dec 2017 14:11:27 GMT", "version": "v1" } ]
2017-12-21
[ [ "Sudholt", "Sebastian", "" ], [ "Fink", "Gernot", "" ] ]
Word spotting has become a field of strong research interest in document image analysis over the last years. Recently, AttributeSVMs were proposed which predict a binary attribute representation. At their time, this influential method defined the state-of-the-art in segmentation-based word spotting. In this work, we pr...
2106.02566
Tristan Gomez
Tristan Gomez, Suiyi Ling, Thomas Fr\'eour, Harold Mouch\`ere
BR-NPA: A Non-Parametric High-Resolution Attention Model to improve the Interpretability of Attention
null
null
null
null
cs.CV cs.LG
http://creativecommons.org/licenses/by-nc-sa/4.0/
The prevalence of employing attention mechanisms has brought along concerns on the interpretability of attention distributions. Although it provides insights about how a model is operating, utilizing attention as the explanation of model predictions is still highly dubious. The community is still seeking more interpr...
[ { "created": "Fri, 4 Jun 2021 15:57:37 GMT", "version": "v1" }, { "created": "Mon, 7 Jun 2021 10:25:01 GMT", "version": "v2" }, { "created": "Mon, 31 Jan 2022 14:50:41 GMT", "version": "v3" }, { "created": "Thu, 19 May 2022 07:19:38 GMT", "version": "v4" }, { "cre...
2022-09-16
[ [ "Gomez", "Tristan", "" ], [ "Ling", "Suiyi", "" ], [ "Fréour", "Thomas", "" ], [ "Mouchère", "Harold", "" ] ]
The prevalence of employing attention mechanisms has brought along concerns on the interpretability of attention distributions. Although it provides insights about how a model is operating, utilizing attention as the explanation of model predictions is still highly dubious. The community is still seeking more interpret...
2301.01379
Sanjeevan Ahilan
Sanjeevan Ahilan
A Succinct Summary of Reinforcement Learning
null
null
null
null
cs.AI cs.LG
http://creativecommons.org/licenses/by/4.0/
This document is a concise summary of many key results in single-agent reinforcement learning (RL). The intended audience are those who already have some familiarity with RL and are looking to review, reference and/or remind themselves of important ideas in the field.
[ { "created": "Tue, 3 Jan 2023 22:17:55 GMT", "version": "v1" } ]
2023-01-05
[ [ "Ahilan", "Sanjeevan", "" ] ]
This document is a concise summary of many key results in single-agent reinforcement learning (RL). The intended audience are those who already have some familiarity with RL and are looking to review, reference and/or remind themselves of important ideas in the field.
2004.07623
Ankur Mali
Ankur Mali, Alexander Ororbia, Daniel Kifer, Clyde Lee Giles
Recognizing Long Grammatical Sequences Using Recurrent Networks Augmented With An External Differentiable Stack
14 pages, 10 tables
null
null
null
cs.CL cs.LG
http://creativecommons.org/licenses/by/4.0/
Recurrent neural networks (RNNs) are a widely used deep architecture for sequence modeling, generation, and prediction. Despite success in applications such as machine translation and voice recognition, these stateful models have several critical shortcomings. Specifically, RNNs generalize poorly over very long seque...
[ { "created": "Sat, 4 Apr 2020 14:19:15 GMT", "version": "v1" }, { "created": "Wed, 22 Apr 2020 15:36:26 GMT", "version": "v2" } ]
2020-04-23
[ [ "Mali", "Ankur", "" ], [ "Ororbia", "Alexander", "" ], [ "Kifer", "Daniel", "" ], [ "Giles", "Clyde Lee", "" ] ]
Recurrent neural networks (RNNs) are a widely used deep architecture for sequence modeling, generation, and prediction. Despite success in applications such as machine translation and voice recognition, these stateful models have several critical shortcomings. Specifically, RNNs generalize poorly over very long sequenc...
1210.2462
EPTCS
Alex Kruckman (Berkeley University), Sasha Rubin (TU Vienna and IST Austria), John Sheridan, Ben Zax
A Myhill-Nerode theorem for automata with advice
In Proceedings GandALF 2012, arXiv:1210.2028
EPTCS 96, 2012, pp. 238-246
10.4204/EPTCS.96.18
null
cs.FL cs.LO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
An automaton with advice is a finite state automaton which has access to an additional fixed infinite string called an advice tape. We refine the Myhill-Nerode theorem to characterize the languages of finite strings that are accepted by automata with advice. We do the same for tree automata with advice.
[ { "created": "Tue, 9 Oct 2012 00:55:28 GMT", "version": "v1" } ]
2012-10-10
[ [ "Kruckman", "Alex", "", "Berkeley University" ], [ "Rubin", "Sasha", "", "TU Vienna and IST\n Austria" ], [ "Sheridan", "John", "" ], [ "Zax", "Ben", "" ] ]
An automaton with advice is a finite state automaton which has access to an additional fixed infinite string called an advice tape. We refine the Myhill-Nerode theorem to characterize the languages of finite strings that are accepted by automata with advice. We do the same for tree automata with advice.
1906.01502
Telmo Pires
Telmo Pires, Eva Schlinger and Dan Garrette
How multilingual is Multilingual BERT?
null
null
null
null
cs.CL cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we show that Multilingual BERT (M-BERT), released by Devlin et al. (2018) as a single language model pre-trained from monolingual corpora in 104 languages, is surprisingly good at zero-shot cross-lingual model transfer, in which task-specific annotations in one language are used to fine-tune the model ...
[ { "created": "Tue, 4 Jun 2019 15:12:47 GMT", "version": "v1" } ]
2019-06-05
[ [ "Pires", "Telmo", "" ], [ "Schlinger", "Eva", "" ], [ "Garrette", "Dan", "" ] ]
In this paper, we show that Multilingual BERT (M-BERT), released by Devlin et al. (2018) as a single language model pre-trained from monolingual corpora in 104 languages, is surprisingly good at zero-shot cross-lingual model transfer, in which task-specific annotations in one language are used to fine-tune the model fo...
2010.13676
Radu P Horaud
Zhiqi Kang, Mostafa Sadeghi and Radu Horaud
Face Frontalization Based on Robustly Fitting a Deformable Shape Model to 3D Landmarks
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Face frontalization consists of synthesizing a frontally-viewed face from an arbitrarily-viewed one. The main contribution of this paper is a robust face alignment method that enables pixel-to-pixel warping. The method simultaneously estimates the rigid transformation (scale, rotation, and translation) and the non-ri...
[ { "created": "Mon, 26 Oct 2020 15:52:50 GMT", "version": "v1" }, { "created": "Wed, 10 Mar 2021 10:45:41 GMT", "version": "v2" } ]
2021-03-11
[ [ "Kang", "Zhiqi", "" ], [ "Sadeghi", "Mostafa", "" ], [ "Horaud", "Radu", "" ] ]
Face frontalization consists of synthesizing a frontally-viewed face from an arbitrarily-viewed one. The main contribution of this paper is a robust face alignment method that enables pixel-to-pixel warping. The method simultaneously estimates the rigid transformation (scale, rotation, and translation) and the non-rigi...
2303.17580
Yongliang Shen
Yongliang Shen, Kaitao Song, Xu Tan, Dongsheng Li, Weiming Lu, Yueting Zhuang
HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in Hugging Face
null
null
null
null
cs.CL cs.AI cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Solving complicated AI tasks with different domains and modalities is a key step toward artificial general intelligence. While there are numerous AI models available for various domains and modalities, they cannot handle complicated AI tasks autonomously. Considering large language models (LLMs) have exhibited except...
[ { "created": "Thu, 30 Mar 2023 17:48:28 GMT", "version": "v1" }, { "created": "Sun, 2 Apr 2023 17:24:47 GMT", "version": "v2" }, { "created": "Thu, 25 May 2023 15:50:20 GMT", "version": "v3" }, { "created": "Sun, 3 Dec 2023 18:17:21 GMT", "version": "v4" } ]
2023-12-05
[ [ "Shen", "Yongliang", "" ], [ "Song", "Kaitao", "" ], [ "Tan", "Xu", "" ], [ "Li", "Dongsheng", "" ], [ "Lu", "Weiming", "" ], [ "Zhuang", "Yueting", "" ] ]
Solving complicated AI tasks with different domains and modalities is a key step toward artificial general intelligence. While there are numerous AI models available for various domains and modalities, they cannot handle complicated AI tasks autonomously. Considering large language models (LLMs) have exhibited exceptio...
1606.07502
Biljana Risteska Stojkoska Dr
Biljana Stojkoska, Ilinka Ivanoska and Danco Davcev
Wireless Sensor Networks Localization Methods: Multidimensional Scaling vs. Semidefinite Programming Approach
12 pages
ICT Innovations 2009, Ohrid, Macedonia, pp.145-155, Print ISBN 978-3-642-10780-1, Online ISBN 978-3-642-10781-8
10.1007/978-3-642-10781-8_16
null
cs.DC cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
With the recent development of technology, wireless sensor networks are becoming an important part of many applications such as health and medical applications, military applications, agriculture monitoring, home and office applications, environmental monitoring, etc. Knowing the location of a sensor is important, bu...
[ { "created": "Thu, 23 Jun 2016 22:46:52 GMT", "version": "v1" } ]
2016-06-27
[ [ "Stojkoska", "Biljana", "" ], [ "Ivanoska", "Ilinka", "" ], [ "Davcev", "Danco", "" ] ]
With the recent development of technology, wireless sensor networks are becoming an important part of many applications such as health and medical applications, military applications, agriculture monitoring, home and office applications, environmental monitoring, etc. Knowing the location of a sensor is important, but ...
2306.15597
Ruilong Zhang
Christoph Damerius, Peter Kling, Minming Li, Chenyang Xu, Ruilong Zhang
Scheduling with a Limited Testing Budget
To appear in ESA 2023
null
null
null
cs.DS
http://creativecommons.org/licenses/by-nc-nd/4.0/
Scheduling with testing falls under the umbrella of the research on optimization with explorable uncertainty. In this model, each job has an upper limit on its processing time that can be decreased to a lower limit (possibly unknown) by some preliminary action (testing). Recently, D{\"{u}}rr et al. \cite{DBLP:journal...
[ { "created": "Tue, 27 Jun 2023 16:34:15 GMT", "version": "v1" } ]
2023-06-28
[ [ "Damerius", "Christoph", "" ], [ "Kling", "Peter", "" ], [ "Li", "Minming", "" ], [ "Xu", "Chenyang", "" ], [ "Zhang", "Ruilong", "" ] ]
Scheduling with testing falls under the umbrella of the research on optimization with explorable uncertainty. In this model, each job has an upper limit on its processing time that can be decreased to a lower limit (possibly unknown) by some preliminary action (testing). Recently, D{\"{u}}rr et al. \cite{DBLP:journals/...
2204.02341
Jonathan Grizou
Jonathan Grizou
IFTT-PIN: Demonstrating the Self-Calibration Paradigm on a PIN-Entry Task
null
null
null
null
cs.HC cs.AI cs.LG
http://creativecommons.org/licenses/by-nc-sa/4.0/
We demonstrate IFTT-PIN, a self-calibrating version of the PIN-entry method introduced in Roth et al. (2004) [1]. In [1], digits are split into two sets and assigned a color respectively. To communicate their digit, users press the button with the same color that is assigned to their digit, which can be identified by...
[ { "created": "Tue, 5 Apr 2022 16:56:40 GMT", "version": "v1" } ]
2022-04-06
[ [ "Grizou", "Jonathan", "" ] ]
We demonstrate IFTT-PIN, a self-calibrating version of the PIN-entry method introduced in Roth et al. (2004) [1]. In [1], digits are split into two sets and assigned a color respectively. To communicate their digit, users press the button with the same color that is assigned to their digit, which can be identified by e...
2101.09601
Renaud-Alexandre Pitaval
Renaud-Alexandre Pitaval
A note on simplified SINR expressions for OFDM with insufficient CP
null
null
null
null
cs.IT math.IT
http://creativecommons.org/licenses/by/4.0/
This note provides derivation details of simplified OFDM transmission equation and resulting signal-to-interference plus noise ratio (SINR) for the case of an insufficient CP. Each channel component after demodulation is expressed as a single sum which can be interpreted a weighted Fourier transform of the channel im...
[ { "created": "Sat, 23 Jan 2021 22:52:41 GMT", "version": "v1" } ]
2021-01-26
[ [ "Pitaval", "Renaud-Alexandre", "" ] ]
This note provides derivation details of simplified OFDM transmission equation and resulting signal-to-interference plus noise ratio (SINR) for the case of an insufficient CP. Each channel component after demodulation is expressed as a single sum which can be interpreted a weighted Fourier transform of the channel impu...
1106.4569
D. V. Pynadath
D. V. Pynadath, M. Tambe
The Communicative Multiagent Team Decision Problem: Analyzing Teamwork Theories and Models
null
Journal Of Artificial Intelligence Research, Volume 16, pages 389-423, 2002
10.1613/jair.1024
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Despite the significant progress in multiagent teamwork, existing research does not address the optimality of its prescriptions nor the complexity of the teamwork problem. Without a characterization of the optimality-complexity tradeoffs, it is impossible to determine whether the assumptions and approximations made b...
[ { "created": "Wed, 22 Jun 2011 20:55:38 GMT", "version": "v1" } ]
2011-06-24
[ [ "Pynadath", "D. V.", "" ], [ "Tambe", "M.", "" ] ]
Despite the significant progress in multiagent teamwork, existing research does not address the optimality of its prescriptions nor the complexity of the teamwork problem. Without a characterization of the optimality-complexity tradeoffs, it is impossible to determine whether the assumptions and approximations made by ...
2104.05072
Furkan K{\i}nl{\i}
Furkan K{\i}nl{\i}, Bar{\i}\c{s} \"Ozcan, Furkan K{\i}ra\c{c}
Instagram Filter Removal on Fashionable Images
10 pages, 7 figures, Accepted to New Trends in Image Restoration and Enhancement workshop and challenges on image and video processing in conjunction with CVPR 2021
null
null
null
cs.CV
http://creativecommons.org/licenses/by-nc-sa/4.0/
Social media images are generally transformed by filtering to obtain aesthetically more pleasing appearances. However, CNNs generally fail to interpret both the image and its filtered version as the same in the visual analysis of social media images. We introduce Instagram Filter Removal Network (IFRNet) to mitigate ...
[ { "created": "Sun, 11 Apr 2021 18:44:43 GMT", "version": "v1" } ]
2021-04-13
[ [ "Kınlı", "Furkan", "" ], [ "Özcan", "Barış", "" ], [ "Kıraç", "Furkan", "" ] ]
Social media images are generally transformed by filtering to obtain aesthetically more pleasing appearances. However, CNNs generally fail to interpret both the image and its filtered version as the same in the visual analysis of social media images. We introduce Instagram Filter Removal Network (IFRNet) to mitigate th...
2207.00526
Matthew Earnshaw
Matthew Earnshaw, Pawe{\l} Soboci\'nski
Regular Monoidal Languages
Full version of a paper accepted for MFCS 2022
null
null
null
cs.FL math.CT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We introduce regular languages of morphisms in free monoidal categories, with their associated grammars and automata. These subsume the classical theory of regular languages of words and trees, but also open up a much wider class of languages over string diagrams. We use the algebra of monoidal and cartesian restrict...
[ { "created": "Fri, 1 Jul 2022 16:18:52 GMT", "version": "v1" } ]
2022-07-04
[ [ "Earnshaw", "Matthew", "" ], [ "Sobociński", "Paweł", "" ] ]
We introduce regular languages of morphisms in free monoidal categories, with their associated grammars and automata. These subsume the classical theory of regular languages of words and trees, but also open up a much wider class of languages over string diagrams. We use the algebra of monoidal and cartesian restrictio...
1812.05815
Anna Bosman
Kevin Louis de Jong and Anna Sergeevna Bosman
Unsupervised Change Detection in Satellite Images Using Convolutional Neural Networks
Paper accepted to IJCNN 2019
null
null
null
cs.NE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper proposes an efficient unsupervised method for detecting relevant changes between two temporally different images of the same scene. A convolutional neural network (CNN) for semantic segmentation is implemented to extract compressed image features, as well as to classify the detected changes into the correc...
[ { "created": "Fri, 14 Dec 2018 08:15:15 GMT", "version": "v1" }, { "created": "Thu, 21 Mar 2019 10:37:16 GMT", "version": "v2" } ]
2019-03-22
[ [ "de Jong", "Kevin Louis", "" ], [ "Bosman", "Anna Sergeevna", "" ] ]
This paper proposes an efficient unsupervised method for detecting relevant changes between two temporally different images of the same scene. A convolutional neural network (CNN) for semantic segmentation is implemented to extract compressed image features, as well as to classify the detected changes into the correct ...
1509.06767
Jason McEwen
Jason D. McEwen, Claudio Durastanti, Yves Wiaux
Localisation of directional scale-discretised wavelets on the sphere
28 pages, 8 figures, minor changes to match version accepted for publication by ACHA
null
10.1016/j.acha.2016.03.009
null
cs.IT astro-ph.IM math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Scale-discretised wavelets yield a directional wavelet framework on the sphere where a signal can be probed not only in scale and position but also in orientation. Furthermore, a signal can be synthesised from its wavelet coefficients exactly, in theory and practice (to machine precision). Scale-discretised wavelets ...
[ { "created": "Tue, 22 Sep 2015 20:27:17 GMT", "version": "v1" }, { "created": "Tue, 5 Apr 2016 16:08:12 GMT", "version": "v2" } ]
2017-08-17
[ [ "McEwen", "Jason D.", "" ], [ "Durastanti", "Claudio", "" ], [ "Wiaux", "Yves", "" ] ]
Scale-discretised wavelets yield a directional wavelet framework on the sphere where a signal can be probed not only in scale and position but also in orientation. Furthermore, a signal can be synthesised from its wavelet coefficients exactly, in theory and practice (to machine precision). Scale-discretised wavelets ar...
2305.02728
Alex Iacob
Alex Iacob, Pedro P. B. Gusm\~ao, Nicholas D. Lane
Can Fair Federated Learning reduce the need for Personalisation?
In 3rd Workshop on Machine Learning and Systems (EuroMLSys 2023), 9 pages
null
10.1145/3578356.3592592
null
cs.LG cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Federated Learning (FL) enables training ML models on edge clients without sharing data. However, the federated model's performance on local data varies, disincentivising the participation of clients who benefit little from FL. Fair FL reduces accuracy disparity by focusing on clients with higher losses while persona...
[ { "created": "Thu, 4 May 2023 11:03:33 GMT", "version": "v1" } ]
2023-05-05
[ [ "Iacob", "Alex", "" ], [ "Gusmão", "Pedro P. B.", "" ], [ "Lane", "Nicholas D.", "" ] ]
Federated Learning (FL) enables training ML models on edge clients without sharing data. However, the federated model's performance on local data varies, disincentivising the participation of clients who benefit little from FL. Fair FL reduces accuracy disparity by focusing on clients with higher losses while personali...
2404.19311
Yazhou Yao
Wang Zhang, Tingting Li, Yuntian Zhang, Gensheng Pei, Xiruo Jiang, Yazhou Yao
A Light-weight Transformer-based Self-supervised Matching Network for Heterogeneous Images
accepted by Information Fusion
null
null
null
cs.CV cs.MM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Matching visible and near-infrared (NIR) images remains a significant challenge in remote sensing image fusion. The nonlinear radiometric differences between heterogeneous remote sensing images make the image matching task even more difficult. Deep learning has gained substantial attention in computer vision tasks in...
[ { "created": "Tue, 30 Apr 2024 07:30:33 GMT", "version": "v1" } ]
2024-05-01
[ [ "Zhang", "Wang", "" ], [ "Li", "Tingting", "" ], [ "Zhang", "Yuntian", "" ], [ "Pei", "Gensheng", "" ], [ "Jiang", "Xiruo", "" ], [ "Yao", "Yazhou", "" ] ]
Matching visible and near-infrared (NIR) images remains a significant challenge in remote sensing image fusion. The nonlinear radiometric differences between heterogeneous remote sensing images make the image matching task even more difficult. Deep learning has gained substantial attention in computer vision tasks in r...
2305.14288
Chenxi Whitehouse
Chenxi Whitehouse, Monojit Choudhury, Alham Fikri Aji
LLM-powered Data Augmentation for Enhanced Cross-lingual Performance
EMNLP 2023 Main Conference
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
This paper explores the potential of leveraging Large Language Models (LLMs) for data augmentation in multilingual commonsense reasoning datasets where the available training data is extremely limited. To achieve this, we utilise several LLMs, namely Dolly-v2, StableVicuna, ChatGPT, and GPT-4, to augment three datase...
[ { "created": "Tue, 23 May 2023 17:33:27 GMT", "version": "v1" }, { "created": "Sun, 22 Oct 2023 22:57:00 GMT", "version": "v2" } ]
2023-10-24
[ [ "Whitehouse", "Chenxi", "" ], [ "Choudhury", "Monojit", "" ], [ "Aji", "Alham Fikri", "" ] ]
This paper explores the potential of leveraging Large Language Models (LLMs) for data augmentation in multilingual commonsense reasoning datasets where the available training data is extremely limited. To achieve this, we utilise several LLMs, namely Dolly-v2, StableVicuna, ChatGPT, and GPT-4, to augment three datasets...
2011.00574
Omid Taheri
Omid Taheri, Hassan Salarieh, Aria Alasty
Human Leg Motion Tracking by Fusing IMUs and RGB Camera Data Using Extended Kalman Filter
This paper results from O. Taheri's MSc Thesis (2017) at the Sharif University of Technology
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Human motion capture is frequently used to study rehabilitation and clinical problems, as well as to provide realistic animation for the entertainment industry. IMU-based systems, as well as Marker-based motion tracking systems, are the most popular methods to track movement due to their low cost of implementation an...
[ { "created": "Sun, 1 Nov 2020 17:54:53 GMT", "version": "v1" }, { "created": "Mon, 7 Dec 2020 22:20:27 GMT", "version": "v2" } ]
2020-12-09
[ [ "Taheri", "Omid", "" ], [ "Salarieh", "Hassan", "" ], [ "Alasty", "Aria", "" ] ]
Human motion capture is frequently used to study rehabilitation and clinical problems, as well as to provide realistic animation for the entertainment industry. IMU-based systems, as well as Marker-based motion tracking systems, are the most popular methods to track movement due to their low cost of implementation and ...
2305.17710
Wentao Chao
Wentao Chao, Fuqing Duan, Xuechun Wang, Yingqian Wang, Guanghui Wang
OccCasNet: Occlusion-aware Cascade Cost Volume for Light Field Depth Estimation
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Light field (LF) depth estimation is a crucial task with numerous practical applications. However, mainstream methods based on the multi-view stereo (MVS) are resource-intensive and time-consuming as they need to construct a finer cost volume. To address this issue and achieve a better trade-off between accuracy and ...
[ { "created": "Sun, 28 May 2023 12:31:27 GMT", "version": "v1" } ]
2023-05-30
[ [ "Chao", "Wentao", "" ], [ "Duan", "Fuqing", "" ], [ "Wang", "Xuechun", "" ], [ "Wang", "Yingqian", "" ], [ "Wang", "Guanghui", "" ] ]
Light field (LF) depth estimation is a crucial task with numerous practical applications. However, mainstream methods based on the multi-view stereo (MVS) are resource-intensive and time-consuming as they need to construct a finer cost volume. To address this issue and achieve a better trade-off between accuracy and ef...
2304.10596
Akhil K
Akhil Kuniyil, Avinash Kshitij, and Kasturi Mandal
Enhancing Artificial intelligence Policies with Fusion and Forecasting: Insights from Indian Patents Using Network Analysis
null
null
null
null
cs.AI
http://creativecommons.org/licenses/by-nc-sa/4.0/
This paper presents a study of the interconnectivity and interdependence of various Artificial intelligence (AI) technologies through the use of centrality measures, clustering coefficients, and degree of fusion measures. By analyzing the technologies through different time windows and quantifying their importance, w...
[ { "created": "Thu, 20 Apr 2023 18:37:11 GMT", "version": "v1" } ]
2023-04-24
[ [ "Kuniyil", "Akhil", "" ], [ "Kshitij", "Avinash", "" ], [ "Mandal", "Kasturi", "" ] ]
This paper presents a study of the interconnectivity and interdependence of various Artificial intelligence (AI) technologies through the use of centrality measures, clustering coefficients, and degree of fusion measures. By analyzing the technologies through different time windows and quantifying their importance, we ...
2107.13600
Michael Jones
Sai Saketh Rambhatla, Michael Jones, Rama Chellappa
To Boost or not to Boost: On the Limits of Boosted Neural Networks
null
null
null
null
cs.LG
http://creativecommons.org/licenses/by/4.0/
Boosting is a method for finding a highly accurate hypothesis by linearly combining many ``weak" hypotheses, each of which may be only moderately accurate. Thus, boosting is a method for learning an ensemble of classifiers. While boosting has been shown to be very effective for decision trees, its impact on neural ne...
[ { "created": "Wed, 28 Jul 2021 19:10:03 GMT", "version": "v1" } ]
2021-07-30
[ [ "Rambhatla", "Sai Saketh", "" ], [ "Jones", "Michael", "" ], [ "Chellappa", "Rama", "" ] ]
Boosting is a method for finding a highly accurate hypothesis by linearly combining many ``weak" hypotheses, each of which may be only moderately accurate. Thus, boosting is a method for learning an ensemble of classifiers. While boosting has been shown to be very effective for decision trees, its impact on neural netw...
1602.08721
Oren Kalinsky
Oren Kalinsky, Yoav Etsion, Benny Kimelfeld
Flexible Caching in Trie Joins
null
null
null
null
cs.DB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Traditional algorithms for multiway join computation are based on rewriting the order of joins and combining results of intermediate subqueries. Recently, several approaches have been proposed for algorithms that are "worst-case optimal" wherein all relations are scanned simultaneously. An example is Veldhuizen's Lea...
[ { "created": "Sun, 28 Feb 2016 14:26:08 GMT", "version": "v1" } ]
2016-03-01
[ [ "Kalinsky", "Oren", "" ], [ "Etsion", "Yoav", "" ], [ "Kimelfeld", "Benny", "" ] ]
Traditional algorithms for multiway join computation are based on rewriting the order of joins and combining results of intermediate subqueries. Recently, several approaches have been proposed for algorithms that are "worst-case optimal" wherein all relations are scanned simultaneously. An example is Veldhuizen's Leapf...
2303.03642
Xinhang Lu
Haris Aziz, Xinhang Lu, Mashbat Suzuki, Jeremy Vollen, Toby Walsh
Best-of-Both-Worlds Fairness in Committee Voting
Appears in the 19th Conference on Web and Internet Economics (WINE), 2023
null
null
null
cs.GT econ.TH
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The best-of-both-worlds paradigm advocates an approach that achieves desirable properties both ex-ante and ex-post. We launch a best-of-both-worlds fairness perspective for the important social choice setting of approval-based committee voting. To this end, we initiate work on ex-ante proportional representation prop...
[ { "created": "Tue, 7 Mar 2023 04:19:47 GMT", "version": "v1" }, { "created": "Fri, 7 Jul 2023 06:46:16 GMT", "version": "v2" }, { "created": "Mon, 25 Dec 2023 13:23:33 GMT", "version": "v3" } ]
2023-12-27
[ [ "Aziz", "Haris", "" ], [ "Lu", "Xinhang", "" ], [ "Suzuki", "Mashbat", "" ], [ "Vollen", "Jeremy", "" ], [ "Walsh", "Toby", "" ] ]
The best-of-both-worlds paradigm advocates an approach that achieves desirable properties both ex-ante and ex-post. We launch a best-of-both-worlds fairness perspective for the important social choice setting of approval-based committee voting. To this end, we initiate work on ex-ante proportional representation proper...
2308.08495
Ciaran Eising
Ciar\'an Hogan, Ganesh Sistu, Ciar\'an Eising
Self-Supervised Online Camera Calibration for Automated Driving and Parking Applications
null
Proceedings of the Irish Machine Vision and Image Processing Conference 2023
null
null
cs.CV cs.RO
http://creativecommons.org/licenses/by/4.0/
Camera-based perception systems play a central role in modern autonomous vehicles. These camera based perception algorithms require an accurate calibration to map the real world distances to image pixels. In practice, calibration is a laborious procedure requiring specialised data collection and careful tuning. This ...
[ { "created": "Wed, 16 Aug 2023 16:49:50 GMT", "version": "v1" } ]
2023-08-17
[ [ "Hogan", "Ciarán", "" ], [ "Sistu", "Ganesh", "" ], [ "Eising", "Ciarán", "" ] ]
Camera-based perception systems play a central role in modern autonomous vehicles. These camera based perception algorithms require an accurate calibration to map the real world distances to image pixels. In practice, calibration is a laborious procedure requiring specialised data collection and careful tuning. This pr...
1311.6677
Alexandr Klimchik
Alexandr Klimchik (IRCCyN), Yier Wu (IRCCyN), St\'ephane Caro (IRCCyN), Beno\^it Furet (IRCCyN), Anatol Pashkevich (IRCCyN)
Advanced robot calibration using partial pose measurements
null
18th International Conference on Methods and Models in Automation and Robotics (MMAR 2013), Mi{\ke}dzyzdroje : Poland (2013)
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The paper focuses on the calibration of serial industrial robots using partial pose measurements. In contrast to other works, the developed advanced robot calibration technique is suitable for geometrical and elastostatic calibration. The main attention is paid to the model parameters identification accuracy. To redu...
[ { "created": "Tue, 26 Nov 2013 14:02:58 GMT", "version": "v1" } ]
2013-11-27
[ [ "Klimchik", "Alexandr", "", "IRCCyN" ], [ "Wu", "Yier", "", "IRCCyN" ], [ "Caro", "Stéphane", "", "IRCCyN" ], [ "Furet", "Benoît", "", "IRCCyN" ], [ "Pashkevich", "Anatol", "", "IRCCyN" ] ]
The paper focuses on the calibration of serial industrial robots using partial pose measurements. In contrast to other works, the developed advanced robot calibration technique is suitable for geometrical and elastostatic calibration. The main attention is paid to the model parameters identification accuracy. To reduce...
2405.14394
Zhengxiang Shi
Zhengyan Shi, Adam X. Yang, Bin Wu, Laurence Aitchison, Emine Yilmaz, Aldo Lipani
Instruction Tuning With Loss Over Instructions
Code is available at https://github.com/ZhengxiangShi/InstructionModelling
null
null
null
cs.CL cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Instruction tuning plays a crucial role in shaping the outputs of language models (LMs) to desired styles. In this work, we propose a simple yet effective method, Instruction Modelling (IM), which trains LMs by applying a loss function to the instruction and prompt part rather than solely to the output part. Through ...
[ { "created": "Thu, 23 May 2024 10:12:03 GMT", "version": "v1" } ]
2024-05-24
[ [ "Shi", "Zhengyan", "" ], [ "Yang", "Adam X.", "" ], [ "Wu", "Bin", "" ], [ "Aitchison", "Laurence", "" ], [ "Yilmaz", "Emine", "" ], [ "Lipani", "Aldo", "" ] ]
Instruction tuning plays a crucial role in shaping the outputs of language models (LMs) to desired styles. In this work, we propose a simple yet effective method, Instruction Modelling (IM), which trains LMs by applying a loss function to the instruction and prompt part rather than solely to the output part. Through ex...
1705.02397
Nikhil Mande
Arkadev Chattopadhyay and Nikhil S. Mande
Weights at the Bottom Matter When the Top is Heavy
null
null
null
null
cs.CC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Proving super-polynomial lower bounds against depth-2 threshold circuits of the form THR of THR is a well-known open problem that represents a frontier of our understanding in boolean circuit complexity. By contrast, exponential lower bounds on the size of THR of MAJ circuits were shown by Razborov and Sherstov (SIAM...
[ { "created": "Fri, 5 May 2017 21:08:31 GMT", "version": "v1" } ]
2017-05-09
[ [ "Chattopadhyay", "Arkadev", "" ], [ "Mande", "Nikhil S.", "" ] ]
Proving super-polynomial lower bounds against depth-2 threshold circuits of the form THR of THR is a well-known open problem that represents a frontier of our understanding in boolean circuit complexity. By contrast, exponential lower bounds on the size of THR of MAJ circuits were shown by Razborov and Sherstov (SIAM J...
1603.08293
Feiping Nie
Feiping Nie and Heng Huang
Non-Greedy L21-Norm Maximization for Principal Component Analysis
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Principal Component Analysis (PCA) is one of the most important unsupervised methods to handle high-dimensional data. However, due to the high computational complexity of its eigen decomposition solution, it hard to apply PCA to the large-scale data with high dimensionality. Meanwhile, the squared L2-norm based objec...
[ { "created": "Mon, 28 Mar 2016 03:37:26 GMT", "version": "v1" } ]
2016-03-29
[ [ "Nie", "Feiping", "" ], [ "Huang", "Heng", "" ] ]
Principal Component Analysis (PCA) is one of the most important unsupervised methods to handle high-dimensional data. However, due to the high computational complexity of its eigen decomposition solution, it hard to apply PCA to the large-scale data with high dimensionality. Meanwhile, the squared L2-norm based objecti...
1705.06264
Stanislav Filippov
Stanislav Filippov, Arsenii Moiseev and Andronenko Andrey
Deep Diagnostics: Applying Convolutional Neural Networks for Vessels Defects Detection
Complaint to the article due to low research quality
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Coronary angiography is considered to be a safe tool for the evaluation of coronary artery disease and perform in approximately 12 million patients each year worldwide. [1] In most cases, angiograms are manually analyzed by a cardiologist. Actually, there are no clinical practice algorithms which could improve and au...
[ { "created": "Wed, 17 May 2017 17:17:07 GMT", "version": "v1" }, { "created": "Tue, 6 Jun 2017 16:56:23 GMT", "version": "v2" } ]
2017-06-07
[ [ "Filippov", "Stanislav", "" ], [ "Moiseev", "Arsenii", "" ], [ "Andrey", "Andronenko", "" ] ]
Coronary angiography is considered to be a safe tool for the evaluation of coronary artery disease and perform in approximately 12 million patients each year worldwide. [1] In most cases, angiograms are manually analyzed by a cardiologist. Actually, there are no clinical practice algorithms which could improve and auto...
1509.08979
Diego Calvanese
Diego Calvanese, Giuseppe De Giacomo, Maurizio Lenzerini, Moshe Y. Vardi
Fixpoint Node Selection Query Languages for Trees
null
null
null
null
cs.DB cs.LO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The study of node selection query languages for (finite) trees has been a major topic in the recent research on query languages for Web documents. On one hand, there has been an extensive study of XPath and its various extensions. On the other hand, query languages based on classical logics, such as first-order logic...
[ { "created": "Wed, 30 Sep 2015 00:12:55 GMT", "version": "v1" }, { "created": "Mon, 12 Nov 2018 17:48:36 GMT", "version": "v2" }, { "created": "Wed, 14 Nov 2018 05:31:19 GMT", "version": "v3" } ]
2018-11-15
[ [ "Calvanese", "Diego", "" ], [ "De Giacomo", "Giuseppe", "" ], [ "Lenzerini", "Maurizio", "" ], [ "Vardi", "Moshe Y.", "" ] ]
The study of node selection query languages for (finite) trees has been a major topic in the recent research on query languages for Web documents. On one hand, there has been an extensive study of XPath and its various extensions. On the other hand, query languages based on classical logics, such as first-order logic (...
1906.07809
Parisa Kordjamshidi
Parisa Kordjamshidi, Dan Roth, Kristian Kersting
Declarative Learning-Based Programming as an Interface to AI Systems
null
null
null
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Data-driven approaches are becoming more common as problem-solving techniques in many areas of research and industry. In most cases, machine learning models are the key component of these solutions, but a solution involves multiple such models, along with significant levels of reasoning with the models' output and in...
[ { "created": "Tue, 18 Jun 2019 20:57:51 GMT", "version": "v1" } ]
2019-06-20
[ [ "Kordjamshidi", "Parisa", "" ], [ "Roth", "Dan", "" ], [ "Kersting", "Kristian", "" ] ]
Data-driven approaches are becoming more common as problem-solving techniques in many areas of research and industry. In most cases, machine learning models are the key component of these solutions, but a solution involves multiple such models, along with significant levels of reasoning with the models' output and inpu...
2105.06004
Debarnab Mitra
Debarnab Mitra, Lev Tauz and Lara Dolecek
Communication-Efficient LDPC Code Design for Data Availability Oracle in Side Blockchains
7 pages, 2 figures, 2 tables, To appear in Information Theory Workshop (ITW) 2021
null
null
null
cs.IT cs.CR math.IT
http://creativecommons.org/licenses/by/4.0/
A popular method of improving the throughput of blockchain systems is by running smaller side blockchains that push the hashes of their blocks onto a trusted blockchain. Side blockchains are vulnerable to stalling attacks where a side blockchain node pushes the hash of a block to the trusted blockchain but makes the ...
[ { "created": "Wed, 12 May 2021 23:57:42 GMT", "version": "v1" }, { "created": "Thu, 26 Aug 2021 03:34:26 GMT", "version": "v2" } ]
2021-08-27
[ [ "Mitra", "Debarnab", "" ], [ "Tauz", "Lev", "" ], [ "Dolecek", "Lara", "" ] ]
A popular method of improving the throughput of blockchain systems is by running smaller side blockchains that push the hashes of their blocks onto a trusted blockchain. Side blockchains are vulnerable to stalling attacks where a side blockchain node pushes the hash of a block to the trusted blockchain but makes the bl...
2402.11843
Yan Hong
Yan Hong, Jianfu Zhang
WildFake: A Large-scale Challenging Dataset for AI-Generated Images Detection
null
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
The extraordinary ability of generative models enabled the generation of images with such high quality that human beings cannot distinguish Artificial Intelligence (AI) generated images from real-life photographs. The development of generation techniques opened up new opportunities but concurrently introduced potenti...
[ { "created": "Mon, 19 Feb 2024 05:13:39 GMT", "version": "v1" } ]
2024-02-20
[ [ "Hong", "Yan", "" ], [ "Zhang", "Jianfu", "" ] ]
The extraordinary ability of generative models enabled the generation of images with such high quality that human beings cannot distinguish Artificial Intelligence (AI) generated images from real-life photographs. The development of generation techniques opened up new opportunities but concurrently introduced potential...
2212.03550
Aleksandr Grekov
Aleksandr N. Grekov (1) (2), Aleksei A. Kabanov (2), Sergei Yu. Alekseev (1), ((1) Institute of Natural and Technical Systems, (2) Sevastopol State University)
Support Vector Machine for Determining Euler Angles in an Inertial Navigation System
7 pages, 5 figures, 5 formulas
Monitoring systems of environment 4(46),2021: 134-142
10.33075/2220-5861-2021-4-134-142
null
cs.RO cs.AI cs.SY eess.SP eess.SY physics.ins-det
http://creativecommons.org/licenses/by/4.0/
The paper discusses the improvement of the accuracy of an inertial navigation system created on the basis of MEMS sensors using machine learning (ML) methods. As input data for the classifier, we used infor-mation obtained from a developed laboratory setup with MEMS sensors on a sealed platform with the ability to ad...
[ { "created": "Wed, 7 Dec 2022 10:01:11 GMT", "version": "v1" } ]
2022-12-08
[ [ "Grekov", "Aleksandr N.", "" ], [ "Kabanov", "Aleksei A.", "" ], [ "Alekseev", "Sergei Yu.", "" ] ]
The paper discusses the improvement of the accuracy of an inertial navigation system created on the basis of MEMS sensors using machine learning (ML) methods. As input data for the classifier, we used infor-mation obtained from a developed laboratory setup with MEMS sensors on a sealed platform with the ability to adju...
1206.4632
Julia Vogt
Julia Vogt (University of Basel), Volker Roth (University of Basel)
A Complete Analysis of the l_1,p Group-Lasso
ICML2012
null
null
null
cs.LG math.OC stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The Group-Lasso is a well-known tool for joint regularization in machine learning methods. While the l_{1,2} and the l_{1,\infty} version have been studied in detail and efficient algorithms exist, there are still open questions regarding other l_{1,p} variants. We characterize conditions for solutions of the l_{1,p}...
[ { "created": "Mon, 18 Jun 2012 15:12:01 GMT", "version": "v1" } ]
2012-06-22
[ [ "Vogt", "Julia", "", "University of Basel" ], [ "Roth", "Volker", "", "University of Basel" ] ]
The Group-Lasso is a well-known tool for joint regularization in machine learning methods. While the l_{1,2} and the l_{1,\infty} version have been studied in detail and efficient algorithms exist, there are still open questions regarding other l_{1,p} variants. We characterize conditions for solutions of the l_{1,p} G...
2206.12896
Kirk Pruhs
Marilena Leichter, Benjamin Moseley, Kirk Pruhs
On the Impossibility of Decomposing Binary Matroids
null
null
null
null
cs.DS math.CO
http://creativecommons.org/licenses/by/4.0/
We show that there exist $k$-colorable matroids that are not $(b,c)$-decomposable when $b$ and $c$ are constants. A matroid is $(b,c)$-decomposable, if its ground set of elements can be partitioned into sets $X_1, X_2, \ldots, X_l$ with the following two properties. Each set $X_i$ has size at most $ck$. Moreover, for...
[ { "created": "Sun, 26 Jun 2022 15:06:20 GMT", "version": "v1" }, { "created": "Wed, 29 Jun 2022 14:15:36 GMT", "version": "v2" } ]
2022-06-30
[ [ "Leichter", "Marilena", "" ], [ "Moseley", "Benjamin", "" ], [ "Pruhs", "Kirk", "" ] ]
We show that there exist $k$-colorable matroids that are not $(b,c)$-decomposable when $b$ and $c$ are constants. A matroid is $(b,c)$-decomposable, if its ground set of elements can be partitioned into sets $X_1, X_2, \ldots, X_l$ with the following two properties. Each set $X_i$ has size at most $ck$. Moreover, for a...
2312.10418
Lyudong Jin
Lyudong Jin, Ming Tang, Meng Zhang, Hao Wang
Fractional Deep Reinforcement Learning for Age-Minimal Mobile Edge Computing
null
null
null
null
cs.LG cs.NI eess.SP
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Mobile edge computing (MEC) is a promising paradigm for real-time applications with intensive computational needs (e.g., autonomous driving), as it can reduce the processing delay. In this work, we focus on the timeliness of computational-intensive updates, measured by Age-ofInformation (AoI), and study how to jointl...
[ { "created": "Sat, 16 Dec 2023 11:13:40 GMT", "version": "v1" }, { "created": "Tue, 19 Dec 2023 13:11:49 GMT", "version": "v2" } ]
2023-12-20
[ [ "Jin", "Lyudong", "" ], [ "Tang", "Ming", "" ], [ "Zhang", "Meng", "" ], [ "Wang", "Hao", "" ] ]
Mobile edge computing (MEC) is a promising paradigm for real-time applications with intensive computational needs (e.g., autonomous driving), as it can reduce the processing delay. In this work, we focus on the timeliness of computational-intensive updates, measured by Age-ofInformation (AoI), and study how to jointly ...
2406.15282
Aadityan Ganesh
Matheus V. X. Ferreira, Aadityan Ganesh, Jack Hourigan, Hannah Huh, S. Matthew Weinberg, Catherine Yu
Computing Optimal Manipulations in Cryptographic Self-Selection Proof-of-Stake Protocols
Appeared in the 25th ACM Conference on Economics and Computation (EC '24)
null
10.1145/3670865.3673602
null
cs.GT cs.CR econ.TH
http://creativecommons.org/licenses/by/4.0/
Cryptographic Self-Selection is a paradigm employed by modern Proof-of-Stake consensus protocols to select a block-proposing "leader." Algorand [Chen and Micali, 2019] proposes a canonical protocol, and Ferreira et al. [2022] establish bounds $f(\alpha,\beta)$ on the maximum fraction of rounds a strategic player can ...
[ { "created": "Fri, 21 Jun 2024 16:20:39 GMT", "version": "v1" } ]
2024-06-24
[ [ "Ferreira", "Matheus V. X.", "" ], [ "Ganesh", "Aadityan", "" ], [ "Hourigan", "Jack", "" ], [ "Huh", "Hannah", "" ], [ "Weinberg", "S. Matthew", "" ], [ "Yu", "Catherine", "" ] ]
Cryptographic Self-Selection is a paradigm employed by modern Proof-of-Stake consensus protocols to select a block-proposing "leader." Algorand [Chen and Micali, 2019] proposes a canonical protocol, and Ferreira et al. [2022] establish bounds $f(\alpha,\beta)$ on the maximum fraction of rounds a strategic player can le...
1207.1534
Gol Kim
Gol Kim, Yunchol Jong, Sifeng Liu
Generalized Hybrid Grey Relation Method for Multiple Attribute Mixed Type Decision Making
null
null
null
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The multiple attribute mixed type decision making is performed by four methods, that is, the relative approach degree of grey TOPSIS method, the relative approach degree of grey incidence, the relative membership degree of grey incidence and the grey relation relative approach degree method using the maximum entropy ...
[ { "created": "Fri, 6 Jul 2012 06:44:08 GMT", "version": "v1" } ]
2012-07-12
[ [ "Kim", "Gol", "" ], [ "Jong", "Yunchol", "" ], [ "Liu", "Sifeng", "" ] ]
The multiple attribute mixed type decision making is performed by four methods, that is, the relative approach degree of grey TOPSIS method, the relative approach degree of grey incidence, the relative membership degree of grey incidence and the grey relation relative approach degree method using the maximum entropy es...
2010.14580
Joao Ramos
Joao Ramos, Yanran Ding, Young-woo Sim, Kevin Murphy, and Daniel Block
HOPPY: An open-source and low-cost kit for dynamic robotics education
null
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This letter introduces HOPPY, an open-source, low-cost, robust, and modular kit for robotics education. The robot dynamically hops around a rotating gantry with a fixed base. The kit lowers the entry barrier for studying dynamic robots and legged locomotion in real systems. The kit bridges the theoretical content of ...
[ { "created": "Tue, 27 Oct 2020 19:43:45 GMT", "version": "v1" } ]
2020-10-29
[ [ "Ramos", "Joao", "" ], [ "Ding", "Yanran", "" ], [ "Sim", "Young-woo", "" ], [ "Murphy", "Kevin", "" ], [ "Block", "Daniel", "" ] ]
This letter introduces HOPPY, an open-source, low-cost, robust, and modular kit for robotics education. The robot dynamically hops around a rotating gantry with a fixed base. The kit lowers the entry barrier for studying dynamic robots and legged locomotion in real systems. The kit bridges the theoretical content of fu...
1506.07097
Andrej Gajduk
Andrej Gajduk, Vladimir Zdraveski, Lasko Basnarkov, Mirko Todorovski, Ljupco Kocarev
A Strategy for Power System Stability Improvement via Controlled Charge/Discharge of Plug-in Electric Vehicles
18 pages, 7 figures, subbmited for review in Elsevier's International Journal of Electrical Power & Energy Systems
null
null
null
cs.SY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Plug-in electrical vehicles (PEV) are capable of both grid-to-vehicle (G2V) and vehicle-to-grid (V2G) power transfer. The advantages of developing V2G include an additional revenue stream for cleaner vehicles, increased stability and reliability of the electric grid, lower electric system costs, and eventually, inexp...
[ { "created": "Mon, 22 Jun 2015 13:09:24 GMT", "version": "v1" } ]
2015-06-24
[ [ "Gajduk", "Andrej", "" ], [ "Zdraveski", "Vladimir", "" ], [ "Basnarkov", "Lasko", "" ], [ "Todorovski", "Mirko", "" ], [ "Kocarev", "Ljupco", "" ] ]
Plug-in electrical vehicles (PEV) are capable of both grid-to-vehicle (G2V) and vehicle-to-grid (V2G) power transfer. The advantages of developing V2G include an additional revenue stream for cleaner vehicles, increased stability and reliability of the electric grid, lower electric system costs, and eventually, inexpen...
1611.00260
Vanessa Volz M.Sc.
Vanessa Volz, G\"unter Rudolph, Boris Naujoks
Surrogate-Assisted Partial Order-based Evolutionary Optimisation
null
null
null
null
cs.NE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we propose a novel approach (SAPEO) to support the survival selection process in multi-objective evolutionary algorithms with surrogate models - it dynamically chooses individuals to evaluate exactly based on the model uncertainty and the distinctness of the population. We introduce variants that diffe...
[ { "created": "Tue, 1 Nov 2016 15:00:52 GMT", "version": "v1" } ]
2016-11-02
[ [ "Volz", "Vanessa", "" ], [ "Rudolph", "Günter", "" ], [ "Naujoks", "Boris", "" ] ]
In this paper, we propose a novel approach (SAPEO) to support the survival selection process in multi-objective evolutionary algorithms with surrogate models - it dynamically chooses individuals to evaluate exactly based on the model uncertainty and the distinctness of the population. We introduce variants that differ ...
2210.03580
Lei Wang
Lei Wang, Rong Tong, Cheung Chi Leung, Sunil Sivadas, Chongjia Ni, Bin Ma
Cloud-based Automatic Speech Recognition Systems for Southeast Asian Languages
Published by the 2017 IEEE International Conference on Orange Technologies (ICOT 2017)
null
10.1109/ICOT.2017.8336109
null
cs.CL eess.AS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper provides an overall introduction of our Automatic Speech Recognition (ASR) systems for Southeast Asian languages. As not much existing work has been carried out on such regional languages, a few difficulties should be addressed before building the systems: limitation on speech and text resources, lack of l...
[ { "created": "Fri, 7 Oct 2022 14:28:40 GMT", "version": "v1" } ]
2022-10-10
[ [ "Wang", "Lei", "" ], [ "Tong", "Rong", "" ], [ "Leung", "Cheung Chi", "" ], [ "Sivadas", "Sunil", "" ], [ "Ni", "Chongjia", "" ], [ "Ma", "Bin", "" ] ]
This paper provides an overall introduction of our Automatic Speech Recognition (ASR) systems for Southeast Asian languages. As not much existing work has been carried out on such regional languages, a few difficulties should be addressed before building the systems: limitation on speech and text resources, lack of lin...
2203.16414
Simon Dahan
Simon Dahan, Abdulah Fawaz, Logan Z. J. Williams, Chunhui Yang, Timothy S. Coalson, Matthew F. Glasser, A. David Edwards, Daniel Rueckert, Emma C. Robinson
Surface Vision Transformers: Attention-Based Modelling applied to Cortical Analysis
22 pages, 6 figures, Accepted to MIDL 2022, OpenReview link https://openreview.net/forum?id=mpp843Bsf-
Proceedings of Machine Learning Research. 172 (2022) 282-303
null
null
cs.CV eess.IV q-bio.NC
http://creativecommons.org/licenses/by/4.0/
The extension of convolutional neural networks (CNNs) to non-Euclidean geometries has led to multiple frameworks for studying manifolds. Many of those methods have shown design limitations resulting in poor modelling of long-range associations, as the generalisation of convolutions to irregular surfaces is non-trivia...
[ { "created": "Wed, 30 Mar 2022 15:56:11 GMT", "version": "v1" } ]
2024-06-06
[ [ "Dahan", "Simon", "" ], [ "Fawaz", "Abdulah", "" ], [ "Williams", "Logan Z. J.", "" ], [ "Yang", "Chunhui", "" ], [ "Coalson", "Timothy S.", "" ], [ "Glasser", "Matthew F.", "" ], [ "Edwards", "A. David", "...
The extension of convolutional neural networks (CNNs) to non-Euclidean geometries has led to multiple frameworks for studying manifolds. Many of those methods have shown design limitations resulting in poor modelling of long-range associations, as the generalisation of convolutions to irregular surfaces is non-trivial....
1810.10180
Luke Metz
Luke Metz, Niru Maheswaranathan, Jeremy Nixon, C. Daniel Freeman, Jascha Sohl-Dickstein
Understanding and correcting pathologies in the training of learned optimizers
null
null
null
null
cs.NE stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Deep learning has shown that learned functions can dramatically outperform hand-designed functions on perceptual tasks. Analogously, this suggests that learned optimizers may similarly outperform current hand-designed optimizers, especially for specific problems. However, learned optimizers are notoriously difficult ...
[ { "created": "Wed, 24 Oct 2018 04:04:25 GMT", "version": "v1" }, { "created": "Fri, 26 Oct 2018 17:41:54 GMT", "version": "v2" }, { "created": "Thu, 28 Feb 2019 00:12:30 GMT", "version": "v3" }, { "created": "Wed, 3 Apr 2019 23:14:02 GMT", "version": "v4" }, { "cr...
2019-06-11
[ [ "Metz", "Luke", "" ], [ "Maheswaranathan", "Niru", "" ], [ "Nixon", "Jeremy", "" ], [ "Freeman", "C. Daniel", "" ], [ "Sohl-Dickstein", "Jascha", "" ] ]
Deep learning has shown that learned functions can dramatically outperform hand-designed functions on perceptual tasks. Analogously, this suggests that learned optimizers may similarly outperform current hand-designed optimizers, especially for specific problems. However, learned optimizers are notoriously difficult to...
2302.09973
Simon Kirchgasser
Simon Kirchgasser, Christof Kauba, Georg Wimmer and Andreas Uhl
Advanced Image Quality Assessment for Hand- and Fingervein Biometrics
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Natural Scene Statistics commonly used in non-reference image quality measures and a deep learning based quality assessment approach are proposed as biometric quality indicators for vasculature images. While NIQE and BRISQUE if trained on common images with usual distortions do not work well for assessing vasculature...
[ { "created": "Mon, 20 Feb 2023 13:35:28 GMT", "version": "v1" }, { "created": "Tue, 21 Feb 2023 10:55:57 GMT", "version": "v2" } ]
2023-02-22
[ [ "Kirchgasser", "Simon", "" ], [ "Kauba", "Christof", "" ], [ "Wimmer", "Georg", "" ], [ "Uhl", "Andreas", "" ] ]
Natural Scene Statistics commonly used in non-reference image quality measures and a deep learning based quality assessment approach are proposed as biometric quality indicators for vasculature images. While NIQE and BRISQUE if trained on common images with usual distortions do not work well for assessing vasculature p...
2006.11337
Tianlang Chen
Tianlang Chen, Wei Xiong, Haitian Zheng, Jiebo Luo
Image Sentiment Transfer
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this work, we introduce an important but still unexplored research task -- image sentiment transfer. Compared with other related tasks that have been well-studied, such as image-to-image translation and image style transfer, transferring the sentiment of an image is more challenging. Given an input image, the rule...
[ { "created": "Fri, 19 Jun 2020 19:28:08 GMT", "version": "v1" } ]
2020-06-23
[ [ "Chen", "Tianlang", "" ], [ "Xiong", "Wei", "" ], [ "Zheng", "Haitian", "" ], [ "Luo", "Jiebo", "" ] ]
In this work, we introduce an important but still unexplored research task -- image sentiment transfer. Compared with other related tasks that have been well-studied, such as image-to-image translation and image style transfer, transferring the sentiment of an image is more challenging. Given an input image, the rule t...
2402.01201
Wenhao Jiang
Wenhao Jiang, Duo Li, Menghan Hu, Guangtao Zhai, Xiaokang Yang, Xiao-Ping Zhang
Few-Shot Class-Incremental Learning with Prior Knowledge
null
null
null
null
cs.LG cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
To tackle the issues of catastrophic forgetting and overfitting in few-shot class-incremental learning (FSCIL), previous work has primarily concentrated on preserving the memory of old knowledge during the incremental phase. The role of pre-trained model in shaping the effectiveness of incremental learning is frequen...
[ { "created": "Fri, 2 Feb 2024 08:05:35 GMT", "version": "v1" } ]
2024-02-05
[ [ "Jiang", "Wenhao", "" ], [ "Li", "Duo", "" ], [ "Hu", "Menghan", "" ], [ "Zhai", "Guangtao", "" ], [ "Yang", "Xiaokang", "" ], [ "Zhang", "Xiao-Ping", "" ] ]
To tackle the issues of catastrophic forgetting and overfitting in few-shot class-incremental learning (FSCIL), previous work has primarily concentrated on preserving the memory of old knowledge during the incremental phase. The role of pre-trained model in shaping the effectiveness of incremental learning is frequentl...
2206.12733
Christos Koutras
Christos Koutras, Rihan Hai, Kyriakos Psarakis, Marios Fragkoulis, Asterios Katsifodimos
SiMa: Effective and Efficient Matching Across Data Silos Using Graph Neural Networks
null
null
null
null
cs.DB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
How can we leverage existing column relationships within silos, to predict similar ones across silos? Can we do this efficiently and effectively? Existing matching approaches do not exploit prior knowledge, relying on prohibitively expensive similarity computations. In this paper we present the first technique for ma...
[ { "created": "Sat, 25 Jun 2022 21:18:08 GMT", "version": "v1" }, { "created": "Sun, 3 Mar 2024 07:27:07 GMT", "version": "v2" } ]
2024-03-05
[ [ "Koutras", "Christos", "" ], [ "Hai", "Rihan", "" ], [ "Psarakis", "Kyriakos", "" ], [ "Fragkoulis", "Marios", "" ], [ "Katsifodimos", "Asterios", "" ] ]
How can we leverage existing column relationships within silos, to predict similar ones across silos? Can we do this efficiently and effectively? Existing matching approaches do not exploit prior knowledge, relying on prohibitively expensive similarity computations. In this paper we present the first technique for matc...
2406.15613
Parikshit Solunke
Parikshit Solunke, Vitoria Guardieiro, Joao Rulff, Peter Xenopoulos, Gromit Yeuk-Yin Chan, Brian Barr, Luis Gustavo Nonato, Claudio Silva
MOUNTAINEER: Topology-Driven Visual Analytics for Comparing Local Explanations
Author version of article accepted to IEEE Transactions on Visualization and Computer Graphics
null
null
null
cs.LG cs.GR math.AT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
With the increasing use of black-box Machine Learning (ML) techniques in critical applications, there is a growing demand for methods that can provide transparency and accountability for model predictions. As a result, a large number of local explainability methods for black-box models have been developed and popular...
[ { "created": "Fri, 21 Jun 2024 19:28:50 GMT", "version": "v1" } ]
2024-06-25
[ [ "Solunke", "Parikshit", "" ], [ "Guardieiro", "Vitoria", "" ], [ "Rulff", "Joao", "" ], [ "Xenopoulos", "Peter", "" ], [ "Chan", "Gromit Yeuk-Yin", "" ], [ "Barr", "Brian", "" ], [ "Nonato", "Luis Gustavo", ...
With the increasing use of black-box Machine Learning (ML) techniques in critical applications, there is a growing demand for methods that can provide transparency and accountability for model predictions. As a result, a large number of local explainability methods for black-box models have been developed and populariz...