id
stringlengths
9
10
submitter
stringlengths
1
64
authors
stringlengths
4
20.7k
title
stringlengths
4
246
comments
stringlengths
1
523
journal-ref
stringlengths
4
404
doi
stringlengths
11
153
report-no
stringlengths
2
254
categories
stringlengths
5
98
license
stringclasses
9 values
orig_abstract
stringlengths
14
3.35k
versions
listlengths
1
60
update_date
stringlengths
10
10
authors_parsed
listlengths
1
1.35k
abstract
stringlengths
11
3.34k
2201.13229
Xiwen Chen
Xiwen Chen, Hao Wang, Abolfazl Razi, Brendan Russo, Jason Pacheco, John Roberts, Jeffrey Wishart, Larry Head, Alonso Granados Baca
Network-level Safety Metrics for Overall Traffic Safety Assessment: A Case Study
null
null
null
null
cs.CV cs.AI cs.LG cs.SI
http://creativecommons.org/licenses/by/4.0/
Driving safety analysis has recently experienced unprecedented improvements thanks to technological advances in precise positioning sensors, artificial intelligence (AI)-based safety features, autonomous driving systems, connected vehicles, high-throughput computing, and edge computing servers. Particularly, deep lea...
[ { "created": "Thu, 27 Jan 2022 19:07:08 GMT", "version": "v1" }, { "created": "Mon, 13 Jun 2022 16:59:37 GMT", "version": "v2" } ]
2022-06-14
[ [ "Chen", "Xiwen", "" ], [ "Wang", "Hao", "" ], [ "Razi", "Abolfazl", "" ], [ "Russo", "Brendan", "" ], [ "Pacheco", "Jason", "" ], [ "Roberts", "John", "" ], [ "Wishart", "Jeffrey", "" ], [ "Head", ...
Driving safety analysis has recently experienced unprecedented improvements thanks to technological advances in precise positioning sensors, artificial intelligence (AI)-based safety features, autonomous driving systems, connected vehicles, high-throughput computing, and edge computing servers. Particularly, deep learn...
2004.03372
Ioannis Apostolopoulos
Ioannis D. Apostolopoulos, Peter P. Groumpos, Dimitris I. Apostolopoulos
State Space Advanced Fuzzy Cognitive Map approach for automatic and non Invasive diagnosis of Coronary Artery Disease
14 pages
Biomed. Phys. Eng. Express, 2021
10.1088/2057-1976/abfd83
null
cs.AI cs.SY eess.SY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Purpose: In this study, the recently emerged advances in Fuzzy Cognitive Maps (FCM) are investigated and employed, for achieving the automatic and non-invasive diagnosis of Coronary Artery Disease (CAD). Methods: A Computer-Aided Diagnostic model for the acceptable and non-invasive prediction of CAD using the State S...
[ { "created": "Fri, 3 Apr 2020 18:30:41 GMT", "version": "v1" }, { "created": "Fri, 30 Oct 2020 13:18:04 GMT", "version": "v2" } ]
2021-05-04
[ [ "Apostolopoulos", "Ioannis D.", "" ], [ "Groumpos", "Peter P.", "" ], [ "Apostolopoulos", "Dimitris I.", "" ] ]
Purpose: In this study, the recently emerged advances in Fuzzy Cognitive Maps (FCM) are investigated and employed, for achieving the automatic and non-invasive diagnosis of Coronary Artery Disease (CAD). Methods: A Computer-Aided Diagnostic model for the acceptable and non-invasive prediction of CAD using the State Spa...
2209.06467
Diab Abueidda
Junyan He and Diab Abueidda and Rashid Abu Al-Rub and Seid Koric and Iwona Jasiuk
A deep learning energy-based method for classical elastoplasticity
null
null
10.1016/j.ijplas.2023.103531
null
cs.CE cs.NA math.NA
http://creativecommons.org/licenses/by/4.0/
The deep energy method (DEM) has been used to solve the elastic deformation of structures with linear elasticity, hyperelasticity, and strain-gradient elasticity material models based on the principle of minimum potential energy. In this work, we extend DEM to elastoplasticity problems involving path dependence and i...
[ { "created": "Wed, 14 Sep 2022 07:46:26 GMT", "version": "v1" }, { "created": "Wed, 30 Nov 2022 11:39:00 GMT", "version": "v2" } ]
2023-01-26
[ [ "He", "Junyan", "" ], [ "Abueidda", "Diab", "" ], [ "Al-Rub", "Rashid Abu", "" ], [ "Koric", "Seid", "" ], [ "Jasiuk", "Iwona", "" ] ]
The deep energy method (DEM) has been used to solve the elastic deformation of structures with linear elasticity, hyperelasticity, and strain-gradient elasticity material models based on the principle of minimum potential energy. In this work, we extend DEM to elastoplasticity problems involving path dependence and irr...
1812.10775
Tolga Birdal
Yongheng Zhao and Tolga Birdal and Haowen Deng and Federico Tombari
3D Point Capsule Networks
As published in CVPR 2019 (camera ready version), with supplementary material
null
null
null
cs.CV cs.LG cs.NE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we propose 3D point-capsule networks, an auto-encoder designed to process sparse 3D point clouds while preserving spatial arrangements of the input data. 3D capsule networks arise as a direct consequence of our novel unified 3D auto-encoder formulation. Their dynamic routing scheme and the peculiar 2D ...
[ { "created": "Thu, 27 Dec 2018 17:16:48 GMT", "version": "v1" }, { "created": "Thu, 11 Jul 2019 23:39:55 GMT", "version": "v2" } ]
2019-07-15
[ [ "Zhao", "Yongheng", "" ], [ "Birdal", "Tolga", "" ], [ "Deng", "Haowen", "" ], [ "Tombari", "Federico", "" ] ]
In this paper, we propose 3D point-capsule networks, an auto-encoder designed to process sparse 3D point clouds while preserving spatial arrangements of the input data. 3D capsule networks arise as a direct consequence of our novel unified 3D auto-encoder formulation. Their dynamic routing scheme and the peculiar 2D la...
1503.03215
B Vidhya
B. Vidhya, Mary Joseph, D. Rajini Girinath, A. Malathi
Environment Based Secure Transfer of Data in Wireless Sensor Networks
12, VOL 4,NO 1, FEBRUARY 2015
null
null
null
cs.CR
http://creativecommons.org/licenses/by-nc-sa/3.0/
Most critical sensor readings (Top-k Monitoring) in environment monitoring system are important to many wireless sensor applications. In such applications, sensor nodes transmit the data continuously for a specific time period to the storage nodes. It is responsible for transferring the received results to the Author...
[ { "created": "Wed, 11 Mar 2015 08:31:26 GMT", "version": "v1" } ]
2015-03-12
[ [ "Vidhya", "B.", "" ], [ "Joseph", "Mary", "" ], [ "Girinath", "D. Rajini", "" ], [ "Malathi", "A.", "" ] ]
Most critical sensor readings (Top-k Monitoring) in environment monitoring system are important to many wireless sensor applications. In such applications, sensor nodes transmit the data continuously for a specific time period to the storage nodes. It is responsible for transferring the received results to the Authorit...
2402.01759
Abbas Edalat
Mary Ogbuka Kenneth, Foaad Khosmood and Abbas Edalat
Systematic Literature Review: Computational Approaches for Humour Style Classification
null
null
null
null
cs.CL cs.AI cs.LG
http://creativecommons.org/licenses/by/4.0/
Understanding various humour styles is essential for comprehending the multifaceted nature of humour and its impact on fields such as psychology and artificial intelligence. This understanding has revealed that humour, depending on the style employed, can either have therapeutic or detrimental effects on an individua...
[ { "created": "Tue, 30 Jan 2024 16:21:47 GMT", "version": "v1" } ]
2024-02-06
[ [ "Kenneth", "Mary Ogbuka", "" ], [ "Khosmood", "Foaad", "" ], [ "Edalat", "Abbas", "" ] ]
Understanding various humour styles is essential for comprehending the multifaceted nature of humour and its impact on fields such as psychology and artificial intelligence. This understanding has revealed that humour, depending on the style employed, can either have therapeutic or detrimental effects on an individual'...
1211.4116
Louis Theran
Franz J. Kir\'aly, Louis Theran, Ryota Tomioka
The Algebraic Combinatorial Approach for Low-Rank Matrix Completion
37 pages, with an appendix by Takeaki Uno
null
null
null
cs.LG cs.NA math.AG math.CO stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present a novel algebraic combinatorial view on low-rank matrix completion based on studying relations between a few entries with tools from algebraic geometry and matroid theory. The intrinsic locality of the approach allows for the treatment of single entries in a closed theoretical and practical framework. More...
[ { "created": "Sat, 17 Nov 2012 12:23:36 GMT", "version": "v1" }, { "created": "Mon, 26 Nov 2012 00:07:26 GMT", "version": "v2" }, { "created": "Wed, 17 Apr 2013 06:43:36 GMT", "version": "v3" }, { "created": "Tue, 19 Aug 2014 15:00:30 GMT", "version": "v4" } ]
2014-08-20
[ [ "Király", "Franz J.", "" ], [ "Theran", "Louis", "" ], [ "Tomioka", "Ryota", "" ] ]
We present a novel algebraic combinatorial view on low-rank matrix completion based on studying relations between a few entries with tools from algebraic geometry and matroid theory. The intrinsic locality of the approach allows for the treatment of single entries in a closed theoretical and practical framework. More s...
2212.01589
Idan Kligvasser
Idan Kligvasser, Tamar Rott Shaham, Noa Alkobi and Tomer Michaeli
BlendGAN: Learning and Blending the Internal Distributions of Single Images by Spatial Image-Identity Conditioning
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Training a generative model on a single image has drawn significant attention in recent years. Single image generative methods are designed to learn the internal patch distribution of a single natural image at multiple scales. These models can be used for drawing diverse samples that semantically resemble the trainin...
[ { "created": "Sat, 3 Dec 2022 10:38:27 GMT", "version": "v1" } ]
2022-12-06
[ [ "Kligvasser", "Idan", "" ], [ "Shaham", "Tamar Rott", "" ], [ "Alkobi", "Noa", "" ], [ "Michaeli", "Tomer", "" ] ]
Training a generative model on a single image has drawn significant attention in recent years. Single image generative methods are designed to learn the internal patch distribution of a single natural image at multiple scales. These models can be used for drawing diverse samples that semantically resemble the training ...
2302.12094
Kleyton da Costa Mr.
Cristian Munoz, Kleyton da Costa, Bernardo Modenesi, Adriano Koshiyama
Evaluating explainability for machine learning predictions using model-agnostic metrics
null
null
null
null
cs.LG cs.AI
http://creativecommons.org/licenses/by/4.0/
Rapid advancements in artificial intelligence (AI) technology have brought about a plethora of new challenges in terms of governance and regulation. AI systems are being integrated into various industries and sectors, creating a demand from decision-makers to possess a comprehensive and nuanced understanding of the c...
[ { "created": "Thu, 23 Feb 2023 15:28:36 GMT", "version": "v1" }, { "created": "Mon, 29 Jan 2024 18:56:08 GMT", "version": "v2" } ]
2024-01-30
[ [ "Munoz", "Cristian", "" ], [ "da Costa", "Kleyton", "" ], [ "Modenesi", "Bernardo", "" ], [ "Koshiyama", "Adriano", "" ] ]
Rapid advancements in artificial intelligence (AI) technology have brought about a plethora of new challenges in terms of governance and regulation. AI systems are being integrated into various industries and sectors, creating a demand from decision-makers to possess a comprehensive and nuanced understanding of the cap...
1309.6200
Jonathan Scarlett
Jonathan Scarlett
On the Dispersions of the Gel'fand-Pinsker Channel and Dirty Paper Coding
(v2) Added dirty paper coding, changed title (v3) Generalized dirty paper coding to non-Gaussian state, submitted to IEEE Trans. Inf. Theory
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper studies second-order coding rates for memoryless channels with a state sequence known non-causally at the encoder. In the case of finite alphabets, an achievability result is obtained using constant-composition random coding, and by using a small fraction of the block to transmit the type of the state sequ...
[ { "created": "Tue, 24 Sep 2013 15:09:02 GMT", "version": "v1" }, { "created": "Mon, 14 Oct 2013 15:20:55 GMT", "version": "v2" }, { "created": "Tue, 12 Nov 2013 12:05:09 GMT", "version": "v3" } ]
2013-11-13
[ [ "Scarlett", "Jonathan", "" ] ]
This paper studies second-order coding rates for memoryless channels with a state sequence known non-causally at the encoder. In the case of finite alphabets, an achievability result is obtained using constant-composition random coding, and by using a small fraction of the block to transmit the type of the state sequen...
cs/0201001
Amir Shpilka
Amir Shpilka
Lower Bounds for Matrix Product
Published in the proceedings of the 42nd Annual Symposium on Foundations of Computer Science (FOCS) 2001
Published in the proceedings of the 42nd Annual Symposium on Foundations of Computer Science (FOCS) 2001
null
null
cs.CC
null
We prove lower bounds on the number of product gates in bilinear and quadratic circuits that compute the product of two $n \cross n$ matrices over finite fields. In particular we obtain the following results: 1. We show that the number of product gates in any bilinear (or quadratic) circuit that computes the produc...
[ { "created": "Wed, 2 Jan 2002 09:50:57 GMT", "version": "v1" } ]
2007-05-23
[ [ "Shpilka", "Amir", "" ] ]
We prove lower bounds on the number of product gates in bilinear and quadratic circuits that compute the product of two $n \cross n$ matrices over finite fields. In particular we obtain the following results: 1. We show that the number of product gates in any bilinear (or quadratic) circuit that computes the product of...
1802.09968
Chieh-Teng Chang
Chieh-Teng Chang, Chi-Chia Huang, Chih-Yuan Yang and Jane Yung-Jen Hsu
A Hybrid Word-Character Approach to Abstractive Summarization
null
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Automatic abstractive text summarization is an important and challenging research topic of natural language processing. Among many widely used languages, the Chinese language has a special property that a Chinese character contains rich information comparable to a word. Existing Chinese text summarization methods, ei...
[ { "created": "Tue, 27 Feb 2018 15:31:11 GMT", "version": "v1" }, { "created": "Sat, 8 Sep 2018 04:59:55 GMT", "version": "v2" } ]
2018-09-11
[ [ "Chang", "Chieh-Teng", "" ], [ "Huang", "Chi-Chia", "" ], [ "Yang", "Chih-Yuan", "" ], [ "Hsu", "Jane Yung-Jen", "" ] ]
Automatic abstractive text summarization is an important and challenging research topic of natural language processing. Among many widely used languages, the Chinese language has a special property that a Chinese character contains rich information comparable to a word. Existing Chinese text summarization methods, eith...
1708.06464
EPTCS
Markus Holzer (Institut f\"ur Informatik, Universit\"at Giessen), Martin Kutrib (Institut f\"ur Informatik, Universit\"at Giessen), Andreas Malcher (Institut f\"ur Informatik, Universit\"at Giessen), Matthias Wendlandt (Institut f\"ur Informatik, Universit\"at Giessen)
Input-Driven Double-Head Pushdown Automata
In Proceedings AFL 2017, arXiv:1708.06226
EPTCS 252, 2017, pp. 128-142
10.4204/EPTCS.252.14
null
cs.FL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We introduce and study input-driven deterministic and nondeterministic double-head pushdown automata. A double-head pushdown automaton is a slight generalization of an ordinary pushdown automaton working with two input heads that move in opposite directions on the common input tape. In every step one head is moved an...
[ { "created": "Tue, 22 Aug 2017 00:50:23 GMT", "version": "v1" } ]
2017-08-23
[ [ "Holzer", "Markus", "", "Institut für Informatik, Universität Giessen" ], [ "Kutrib", "Martin", "", "Institut für Informatik, Universität Giessen" ], [ "Malcher", "Andreas", "", "Institut für Informatik, Universität Giessen" ], [ "Wendlandt", "Ma...
We introduce and study input-driven deterministic and nondeterministic double-head pushdown automata. A double-head pushdown automaton is a slight generalization of an ordinary pushdown automaton working with two input heads that move in opposite directions on the common input tape. In every step one head is moved and ...
2001.07776
Jinzheng Cai
Jinzheng Cai, Adam P. Harrison, Youjing Zheng, Ke Yan, Yuankai Huo, Jing Xiao, Lin Yang, Le Lu
Lesion Harvester: Iteratively Mining Unlabeled Lesions and Hard-Negative Examples at Scale
13 pages, 13 figures, to appear in IEEE Transactions on Medical Imaging
IEEE Transactions on Medical Imaging, 2020
10.1109/TMI.2020.3022034
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Acquiring large-scale medical image data, necessary for training machine learning algorithms, is frequently intractable, due to prohibitive expert-driven annotation costs. Recent datasets extracted from hospital archives, e.g., DeepLesion, have begun to address this problem. However, these are often incompletely or n...
[ { "created": "Tue, 21 Jan 2020 21:09:49 GMT", "version": "v1" }, { "created": "Tue, 28 Jan 2020 05:09:07 GMT", "version": "v2" }, { "created": "Mon, 23 Nov 2020 17:50:20 GMT", "version": "v3" } ]
2020-11-24
[ [ "Cai", "Jinzheng", "" ], [ "Harrison", "Adam P.", "" ], [ "Zheng", "Youjing", "" ], [ "Yan", "Ke", "" ], [ "Huo", "Yuankai", "" ], [ "Xiao", "Jing", "" ], [ "Yang", "Lin", "" ], [ "Lu", "Le", ...
Acquiring large-scale medical image data, necessary for training machine learning algorithms, is frequently intractable, due to prohibitive expert-driven annotation costs. Recent datasets extracted from hospital archives, e.g., DeepLesion, have begun to address this problem. However, these are often incompletely or noi...
2402.16899
Shuyu Yin
Shuyu Yin, Qixuan Zhou, Fei Wen, Tao Luo
A priori Estimates for Deep Residual Network in Continuous-time Reinforcement Learning
null
null
null
null
cs.LG cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Deep reinforcement learning excels in numerous large-scale practical applications. However, existing performance analyses ignores the unique characteristics of continuous-time control problems, is unable to directly estimate the generalization error of the Bellman optimal loss and require a boundedness assumption. Ou...
[ { "created": "Sat, 24 Feb 2024 06:31:43 GMT", "version": "v1" }, { "created": "Wed, 6 Mar 2024 06:59:46 GMT", "version": "v2" }, { "created": "Thu, 7 Mar 2024 05:33:40 GMT", "version": "v3" } ]
2024-03-08
[ [ "Yin", "Shuyu", "" ], [ "Zhou", "Qixuan", "" ], [ "Wen", "Fei", "" ], [ "Luo", "Tao", "" ] ]
Deep reinforcement learning excels in numerous large-scale practical applications. However, existing performance analyses ignores the unique characteristics of continuous-time control problems, is unable to directly estimate the generalization error of the Bellman optimal loss and require a boundedness assumption. Our ...
2012.00242
Weixuan Sun
Weixuan Sun, Jing Zhang, Nick Barnes
3D Guided Weakly Supervised Semantic Segmentation
null
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Pixel-wise clean annotation is necessary for fully-supervised semantic segmentation, which is laborious and expensive to obtain. In this paper, we propose a weakly supervised 2D semantic segmentation model by incorporating sparse bounding box labels with available 3D information, which is much easier to obtain with a...
[ { "created": "Tue, 1 Dec 2020 03:34:15 GMT", "version": "v1" } ]
2020-12-02
[ [ "Sun", "Weixuan", "" ], [ "Zhang", "Jing", "" ], [ "Barnes", "Nick", "" ] ]
Pixel-wise clean annotation is necessary for fully-supervised semantic segmentation, which is laborious and expensive to obtain. In this paper, we propose a weakly supervised 2D semantic segmentation model by incorporating sparse bounding box labels with available 3D information, which is much easier to obtain with adv...
1512.03770
Arsany Basta
Wolfgang Kellerer, Arsany Basta, Andreas Blenk
Flexibility of Networks: a new measure for network design space analysis?
null
null
null
null
cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Flexibility is often claimed as a competitive advantage when proposing new network designs. However, most proposals provide only qualitative arguments for their improved support of flexibility. Quantitative arguments vary a lot among different proposals. A general understanding for flexibility is not yet clearly defi...
[ { "created": "Fri, 11 Dec 2015 19:40:39 GMT", "version": "v1" }, { "created": "Wed, 16 Dec 2015 13:54:23 GMT", "version": "v2" } ]
2015-12-17
[ [ "Kellerer", "Wolfgang", "" ], [ "Basta", "Arsany", "" ], [ "Blenk", "Andreas", "" ] ]
Flexibility is often claimed as a competitive advantage when proposing new network designs. However, most proposals provide only qualitative arguments for their improved support of flexibility. Quantitative arguments vary a lot among different proposals. A general understanding for flexibility is not yet clearly define...
1403.4357
Yunquan Dong
Yunquan Dong, Pingyi Fan, Khaled Ben Letaief
High Speed Railway Wireless Communications: Efficiency v.s. Fairness
16 pages, 6 figures
IEEE Trans. Veh. Technol., vol. 62, no. 2, 2014, pp: 925-930
10.1109/TVT.2013.2281401
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
High speed railways (HSRs) have been deployed widely all over the world in recent years. Different from traditional cellular communication, its high mobility makes it essential to implement power allocation along the time. In the HSR case, the transmission rate depends greatly on the distance between the base station...
[ { "created": "Tue, 18 Mar 2014 06:32:44 GMT", "version": "v1" } ]
2014-03-19
[ [ "Dong", "Yunquan", "" ], [ "Fan", "Pingyi", "" ], [ "Letaief", "Khaled Ben", "" ] ]
High speed railways (HSRs) have been deployed widely all over the world in recent years. Different from traditional cellular communication, its high mobility makes it essential to implement power allocation along the time. In the HSR case, the transmission rate depends greatly on the distance between the base station (...
2106.08024
Max Maass
Max Maass and Marc-Pascal Clement and Matthias Hollick
Snail Mail Beats Email Any Day: On Effective Operator Security Notifications in the Internet
Accepted at The 16th International Conference on Availability, Reliability and Security (ARES '21). Code and data: https://doi.org/10.5281/zenodo.4817463
null
10.1145/3465481.3465743
null
cs.CR cs.CY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In the era of large-scale internet scanning, misconfigured websites are a frequent cause of data leaks and security incidents. Previous research has investigated sending automated email notifications to operators of insecure or compromised websites, but has often met with limited success due to challenges in address ...
[ { "created": "Tue, 15 Jun 2021 10:17:59 GMT", "version": "v1" } ]
2021-06-16
[ [ "Maass", "Max", "" ], [ "Clement", "Marc-Pascal", "" ], [ "Hollick", "Matthias", "" ] ]
In the era of large-scale internet scanning, misconfigured websites are a frequent cause of data leaks and security incidents. Previous research has investigated sending automated email notifications to operators of insecure or compromised websites, but has often met with limited success due to challenges in address da...
1303.4199
Manjesh Kumar Hanawal
Manjesh Kumar Hanawal and Eitan Altman
Network Non-Neutrality through Preferential Signaling
10 pages, 4 figures, Accepted at WiOpt 2013
null
null
null
cs.GT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
One of the central issues in the debate on network neutrality has been whether one should allow or prevent preferential treatment by an internet service provider (ISP) of traffic according to its origin. This raised the question of whether to allow an ISP to have exclusive agreement with a content provider (CP). In t...
[ { "created": "Mon, 18 Mar 2013 10:24:07 GMT", "version": "v1" } ]
2013-03-19
[ [ "Hanawal", "Manjesh Kumar", "" ], [ "Altman", "Eitan", "" ] ]
One of the central issues in the debate on network neutrality has been whether one should allow or prevent preferential treatment by an internet service provider (ISP) of traffic according to its origin. This raised the question of whether to allow an ISP to have exclusive agreement with a content provider (CP). In thi...
1705.08091
Andros Tjandra
Andros Tjandra, Sakriani Sakti, Satoshi Nakamura
Local Monotonic Attention Mechanism for End-to-End Speech and Language Processing
Accepted at IJCNLP 2017 --- (V2: added more experiments on G2P & MT)
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recently, encoder-decoder neural networks have shown impressive performance on many sequence-related tasks. The architecture commonly uses an attentional mechanism which allows the model to learn alignments between the source and the target sequence. Most attentional mechanisms used today is based on a global attenti...
[ { "created": "Tue, 23 May 2017 06:32:36 GMT", "version": "v1" }, { "created": "Fri, 3 Nov 2017 15:34:00 GMT", "version": "v2" } ]
2017-11-06
[ [ "Tjandra", "Andros", "" ], [ "Sakti", "Sakriani", "" ], [ "Nakamura", "Satoshi", "" ] ]
Recently, encoder-decoder neural networks have shown impressive performance on many sequence-related tasks. The architecture commonly uses an attentional mechanism which allows the model to learn alignments between the source and the target sequence. Most attentional mechanisms used today is based on a global attention...
2107.00133
Andrew Adamatzky
Alexander E. Beasley, Phil Ayres, Martin Tegelaar, Michail-Antisthenis Tsompanas, Andrew Adamatzky
On electrical gates on fungal colony
null
null
null
null
cs.ET
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Mycelium networks are promising substrates for designing unconventional computing devices providing rich topologies and geometries where signals propagate and interact. Fulfilling our long-term objectives of prototyping electrical analog computers from living mycelium networks, including networks hybridised with nano...
[ { "created": "Wed, 30 Jun 2021 22:39:10 GMT", "version": "v1" } ]
2021-07-02
[ [ "Beasley", "Alexander E.", "" ], [ "Ayres", "Phil", "" ], [ "Tegelaar", "Martin", "" ], [ "Tsompanas", "Michail-Antisthenis", "" ], [ "Adamatzky", "Andrew", "" ] ]
Mycelium networks are promising substrates for designing unconventional computing devices providing rich topologies and geometries where signals propagate and interact. Fulfilling our long-term objectives of prototyping electrical analog computers from living mycelium networks, including networks hybridised with nanopa...
1908.05453
Stav Klein
Reut Tsarfaty, Amit Seker, Shoval Sadde, Stav Klein
What's Wrong with Hebrew NLP? And How to Make it Right
null
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
For languages with simple morphology, such as English, automatic annotation pipelines such as spaCy or Stanford's CoreNLP successfully serve projects in academia and the industry. For many morphologically-rich languages (MRLs), similar pipelines show sub-optimal performance that limits their applicability for text an...
[ { "created": "Thu, 15 Aug 2019 08:09:52 GMT", "version": "v1" } ]
2019-08-16
[ [ "Tsarfaty", "Reut", "" ], [ "Seker", "Amit", "" ], [ "Sadde", "Shoval", "" ], [ "Klein", "Stav", "" ] ]
For languages with simple morphology, such as English, automatic annotation pipelines such as spaCy or Stanford's CoreNLP successfully serve projects in academia and the industry. For many morphologically-rich languages (MRLs), similar pipelines show sub-optimal performance that limits their applicability for text anal...
2007.09438
Dongyun Lin
Dongyun Lin, Yanpeng Cao, Wenbing Zhu, and Yiqun Li
Few-Shot Defect Segmentation Leveraging Abundant Normal Training Samples Through Normal Background Regularization and Crop-and-Paste Operation
Will be appeared in ICME2021 Oral Presentation
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In industrial product quality assessment, it is essential to determine whether a product is defect-free and further analyze the severity of anomality. To this end, accurate defect segmentation on images of products provides an important functionality. In industrial inspection tasks, it is common to capture abundant d...
[ { "created": "Sat, 18 Jul 2020 14:15:42 GMT", "version": "v1" }, { "created": "Tue, 6 Apr 2021 07:14:39 GMT", "version": "v2" } ]
2021-04-07
[ [ "Lin", "Dongyun", "" ], [ "Cao", "Yanpeng", "" ], [ "Zhu", "Wenbing", "" ], [ "Li", "Yiqun", "" ] ]
In industrial product quality assessment, it is essential to determine whether a product is defect-free and further analyze the severity of anomality. To this end, accurate defect segmentation on images of products provides an important functionality. In industrial inspection tasks, it is common to capture abundant def...
1308.2443
Tiancheng Li
Tiancheng Li, Shudong Sun, Tariq P. Sattar and Juan M. Corchado
Fighting Sample Degeneracy and Impoverishment in Particle Filters: A Review of Intelligent Approaches
Expert Systems with Applications, 2014
Expert Systems with Applications, Volume 41, Issue 8, Pages 3944-3954 (15 June 2014)
10.1016/j.eswa.2013.12.031
null
cs.AI stat.CO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
During the last two decades there has been a growing interest in Particle Filtering (PF). However, PF suffers from two long-standing problems that are referred to as sample degeneracy and impoverishment. We are investigating methods that are particularly efficient at Particle Distribution Optimization (PDO) to fight ...
[ { "created": "Mon, 12 Aug 2013 01:38:17 GMT", "version": "v1" }, { "created": "Thu, 9 Jan 2014 02:32:06 GMT", "version": "v2" } ]
2017-07-31
[ [ "Li", "Tiancheng", "" ], [ "Sun", "Shudong", "" ], [ "Sattar", "Tariq P.", "" ], [ "Corchado", "Juan M.", "" ] ]
During the last two decades there has been a growing interest in Particle Filtering (PF). However, PF suffers from two long-standing problems that are referred to as sample degeneracy and impoverishment. We are investigating methods that are particularly efficient at Particle Distribution Optimization (PDO) to fight sa...
2110.00338
Ni Zhang
Ni Zhang and Junwei Han and Nian Liu and Ling Shao
Summarize and Search: Learning Consensus-aware Dynamic Convolution for Co-Saliency Detection
Accepted for ICCV 2021
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Humans perform co-saliency detection by first summarizing the consensus knowledge in the whole group and then searching corresponding objects in each image. Previous methods usually lack robustness, scalability, or stability for the first process and simply fuse consensus features with image features for the second p...
[ { "created": "Fri, 1 Oct 2021 12:06:42 GMT", "version": "v1" } ]
2021-10-04
[ [ "Zhang", "Ni", "" ], [ "Han", "Junwei", "" ], [ "Liu", "Nian", "" ], [ "Shao", "Ling", "" ] ]
Humans perform co-saliency detection by first summarizing the consensus knowledge in the whole group and then searching corresponding objects in each image. Previous methods usually lack robustness, scalability, or stability for the first process and simply fuse consensus features with image features for the second pro...
2306.03598
Jiazheng Li
Jiazheng Li, Zhaoyue Sun, Bin Liang, Lin Gui, Yulan He
CUE: An Uncertainty Interpretation Framework for Text Classifiers Built on Pre-Trained Language Models
Accepted to UAI 2023
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
Text classifiers built on Pre-trained Language Models (PLMs) have achieved remarkable progress in various tasks including sentiment analysis, natural language inference, and question-answering. However, the occurrence of uncertain predictions by these classifiers poses a challenge to their reliability when deployed i...
[ { "created": "Tue, 6 Jun 2023 11:37:46 GMT", "version": "v1" } ]
2023-06-07
[ [ "Li", "Jiazheng", "" ], [ "Sun", "Zhaoyue", "" ], [ "Liang", "Bin", "" ], [ "Gui", "Lin", "" ], [ "He", "Yulan", "" ] ]
Text classifiers built on Pre-trained Language Models (PLMs) have achieved remarkable progress in various tasks including sentiment analysis, natural language inference, and question-answering. However, the occurrence of uncertain predictions by these classifiers poses a challenge to their reliability when deployed in ...
2308.04602
Abby Stevens
Abby Stevens, Jonathan Ozik, Kyle Chard, Jaline Gerardin, Justin M. Wozniak
NSF RESUME HPC Workshop: High-Performance Computing and Large-Scale Data Management in Service of Epidemiological Modeling
null
null
null
null
cs.CY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The NSF-funded Robust Epidemic Surveillance and Modeling (RESUME) project successfully convened a workshop entitled "High-performance computing and large-scale data management in service of epidemiological modeling" at the University of Chicago on May 1-2, 2023. This was part of a series of workshops designed to fost...
[ { "created": "Tue, 8 Aug 2023 22:01:33 GMT", "version": "v1" } ]
2023-08-10
[ [ "Stevens", "Abby", "" ], [ "Ozik", "Jonathan", "" ], [ "Chard", "Kyle", "" ], [ "Gerardin", "Jaline", "" ], [ "Wozniak", "Justin M.", "" ] ]
The NSF-funded Robust Epidemic Surveillance and Modeling (RESUME) project successfully convened a workshop entitled "High-performance computing and large-scale data management in service of epidemiological modeling" at the University of Chicago on May 1-2, 2023. This was part of a series of workshops designed to foster...
1909.09938
Saurabh Bagchi
Jinkyu Koo, Michael Roth and Saurabh Bagchi
HAWKEYE: Adversarial Example Detector for Deep Neural Networks
null
null
null
null
cs.LG cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Adversarial examples (AEs) are images that can mislead deep neural network (DNN) classifiers via introducing slight perturbations into original images. Recent work has shown that detecting AEs can be more effective against AEs than preventing them from being generated. However, the state-of-the-art AE detection still...
[ { "created": "Sun, 22 Sep 2019 04:19:33 GMT", "version": "v1" } ]
2019-09-24
[ [ "Koo", "Jinkyu", "" ], [ "Roth", "Michael", "" ], [ "Bagchi", "Saurabh", "" ] ]
Adversarial examples (AEs) are images that can mislead deep neural network (DNN) classifiers via introducing slight perturbations into original images. Recent work has shown that detecting AEs can be more effective against AEs than preventing them from being generated. However, the state-of-the-art AE detection still s...
2404.06279
Ehsan Pajouheshgar
Ehsan Pajouheshgar, Yitao Xu, Sabine S\"usstrunk
NoiseNCA: Noisy Seed Improves Spatio-Temporal Continuity of Neural Cellular Automata
9 pages, 12 figures
Artificial Life (ALife) 2024
null
null
cs.CV cs.AI cs.GR cs.MA
http://creativecommons.org/licenses/by-nc-sa/4.0/
Neural Cellular Automata (NCA) is a class of Cellular Automata where the update rule is parameterized by a neural network that can be trained using gradient descent. In this paper, we focus on NCA models used for texture synthesis, where the update rule is inspired by partial differential equations (PDEs) describing ...
[ { "created": "Tue, 9 Apr 2024 13:02:33 GMT", "version": "v1" }, { "created": "Wed, 24 Apr 2024 14:15:27 GMT", "version": "v2" }, { "created": "Fri, 14 Jun 2024 11:48:51 GMT", "version": "v3" } ]
2024-06-17
[ [ "Pajouheshgar", "Ehsan", "" ], [ "Xu", "Yitao", "" ], [ "Süsstrunk", "Sabine", "" ] ]
Neural Cellular Automata (NCA) is a class of Cellular Automata where the update rule is parameterized by a neural network that can be trained using gradient descent. In this paper, we focus on NCA models used for texture synthesis, where the update rule is inspired by partial differential equations (PDEs) describing re...
cs/0512081
Mihai Patrascu
Erik D. Demaine, Friedhelm Meyer auf der Heide, Rasmus Pagh and Mihai Patrascu
De Dictionariis Dynamicis Pauco Spatio Utentibus
14 pages. Full version of a paper accepted to LATIN'06
null
null
null
cs.DS
null
We develop dynamic dictionaries on the word RAM that use asymptotically optimal space, up to constant factors, subject to insertions and deletions, and subject to supporting perfect-hashing queries and/or membership queries, each operation in constant time with high probability. When supporting only membership querie...
[ { "created": "Tue, 20 Dec 2005 23:01:41 GMT", "version": "v1" } ]
2007-05-23
[ [ "Demaine", "Erik D.", "" ], [ "der Heide", "Friedhelm Meyer auf", "" ], [ "Pagh", "Rasmus", "" ], [ "Patrascu", "Mihai", "" ] ]
We develop dynamic dictionaries on the word RAM that use asymptotically optimal space, up to constant factors, subject to insertions and deletions, and subject to supporting perfect-hashing queries and/or membership queries, each operation in constant time with high probability. When supporting only membership queries,...
1910.06764
Emilio Parisotto
Emilio Parisotto, H. Francis Song, Jack W. Rae, Razvan Pascanu, Caglar Gulcehre, Siddhant M. Jayakumar, Max Jaderberg, Raphael Lopez Kaufman, Aidan Clark, Seb Noury, Matthew M. Botvinick, Nicolas Heess, Raia Hadsell
Stabilizing Transformers for Reinforcement Learning
null
null
null
null
cs.LG cs.AI stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Owing to their ability to both effectively integrate information over long time horizons and scale to massive amounts of data, self-attention architectures have recently shown breakthrough success in natural language processing (NLP), achieving state-of-the-art results in domains such as language modeling and machine...
[ { "created": "Sun, 13 Oct 2019 20:02:15 GMT", "version": "v1" } ]
2019-10-16
[ [ "Parisotto", "Emilio", "" ], [ "Song", "H. Francis", "" ], [ "Rae", "Jack W.", "" ], [ "Pascanu", "Razvan", "" ], [ "Gulcehre", "Caglar", "" ], [ "Jayakumar", "Siddhant M.", "" ], [ "Jaderberg", "Max", "" ...
Owing to their ability to both effectively integrate information over long time horizons and scale to massive amounts of data, self-attention architectures have recently shown breakthrough success in natural language processing (NLP), achieving state-of-the-art results in domains such as language modeling and machine t...
2408.06303
Mina Huh
Mina Huh, Fangyuan Xu, Yi-Hao Peng, Chongyan Chen, Hansika Murugu, Danna Gurari, Eunsol Choi, Amy Pavel
Long-Form Answers to Visual Questions from Blind and Low Vision People
COLM 2024
null
null
null
cs.CL cs.CV
http://creativecommons.org/licenses/by/4.0/
Vision language models can now generate long-form answers to questions about images - long-form visual question answers (LFVQA). We contribute VizWiz-LF, a dataset of long-form answers to visual questions posed by blind and low vision (BLV) users. VizWiz-LF contains 4.2k long-form answers to 600 visual questions, col...
[ { "created": "Mon, 12 Aug 2024 17:15:02 GMT", "version": "v1" } ]
2024-08-13
[ [ "Huh", "Mina", "" ], [ "Xu", "Fangyuan", "" ], [ "Peng", "Yi-Hao", "" ], [ "Chen", "Chongyan", "" ], [ "Murugu", "Hansika", "" ], [ "Gurari", "Danna", "" ], [ "Choi", "Eunsol", "" ], [ "Pavel", ...
Vision language models can now generate long-form answers to questions about images - long-form visual question answers (LFVQA). We contribute VizWiz-LF, a dataset of long-form answers to visual questions posed by blind and low vision (BLV) users. VizWiz-LF contains 4.2k long-form answers to 600 visual questions, colle...
2202.03391
Martin Genzel
Jonathan Sauder and Martin Genzel and Peter Jung
Gradient-Based Learning of Discrete Structured Measurement Operators for Signal Recovery
The current version of the manuscript has been accepted to IEEE Journal on Selected Areas in Information Theory
IEEE J. Sel. Area. Inf. Theory 3:3 (2022) 481-492
10.1109/JSAIT.2022.3221644
null
cs.LG eess.SP
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Countless signal processing applications include the reconstruction of signals from few indirect linear measurements. The design of effective measurement operators is typically constrained by the underlying hardware and physics, posing a challenging and often even discrete optimization task. While the potential of gr...
[ { "created": "Mon, 7 Feb 2022 18:27:08 GMT", "version": "v1" }, { "created": "Thu, 10 Nov 2022 09:12:11 GMT", "version": "v2" } ]
2023-05-23
[ [ "Sauder", "Jonathan", "" ], [ "Genzel", "Martin", "" ], [ "Jung", "Peter", "" ] ]
Countless signal processing applications include the reconstruction of signals from few indirect linear measurements. The design of effective measurement operators is typically constrained by the underlying hardware and physics, posing a challenging and often even discrete optimization task. While the potential of grad...
2012.12309
Liang Ma
Liang Ma
Influence Maximization Under Generic Threshold-based Non-submodular Model
null
null
null
null
cs.SI cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
As a widely observable social effect, influence diffusion refers to a process where innovations, trends, awareness, etc. spread across the network via the social impact among individuals. Motivated by such social effect, the concept of influence maximization is coined, where the goal is to select a bounded number of ...
[ { "created": "Fri, 18 Dec 2020 16:14:49 GMT", "version": "v1" } ]
2020-12-24
[ [ "Ma", "Liang", "" ] ]
As a widely observable social effect, influence diffusion refers to a process where innovations, trends, awareness, etc. spread across the network via the social impact among individuals. Motivated by such social effect, the concept of influence maximization is coined, where the goal is to select a bounded number of th...
2006.16302
Alexander Jones
Alexander Jones and Rashmi Jha
A Compact Gated-Synapse Model for Neuromorphic Circuits
Submitted to IEEE Transactions on Computer-Aided Design for Integrated Circuits and Systems for review. "This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible."
null
null
null
cs.NE cs.ET
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This work reports a compact behavioral model for gated-synaptic memory. The model is developed in Verilog-A for easy integration into computer-aided design of neuromorphic circuits using emerging memory. The model encompasses various forms of gated synapses within a single framework and is not restricted to only a si...
[ { "created": "Mon, 29 Jun 2020 18:22:11 GMT", "version": "v1" } ]
2020-07-01
[ [ "Jones", "Alexander", "" ], [ "Jha", "Rashmi", "" ] ]
This work reports a compact behavioral model for gated-synaptic memory. The model is developed in Verilog-A for easy integration into computer-aided design of neuromorphic circuits using emerging memory. The model encompasses various forms of gated synapses within a single framework and is not restricted to only a sing...
2406.11164
Farhad Nazari
Farhad Nazari, Arian Shajari, Darius Nahavandi, Navid Mohajer
Optimum signal duration for Human Activity Recognition based on Deep Convolutional Neural Networks
This paper is accepted for publication in the proceedings of the 18th Annual IEEE International Systems Conference (SysCon 2024) \c{opyright} 2024 IEEE. Personal use of this material is permitted
null
null
null
cs.HC
http://creativecommons.org/licenses/by-nc-nd/4.0/
Human Activity Recognition (HAR) stands as a pivotal technique within pattern recognition, dedicated to deciphering human movements and actions utilizing one or multiple sensory inputs. Its significance extends across diverse applications, encompassing monitoring, security protocols, and the development of human-in-t...
[ { "created": "Mon, 17 Jun 2024 03:08:48 GMT", "version": "v1" } ]
2024-06-18
[ [ "Nazari", "Farhad", "" ], [ "Shajari", "Arian", "" ], [ "Nahavandi", "Darius", "" ], [ "Mohajer", "Navid", "" ] ]
Human Activity Recognition (HAR) stands as a pivotal technique within pattern recognition, dedicated to deciphering human movements and actions utilizing one or multiple sensory inputs. Its significance extends across diverse applications, encompassing monitoring, security protocols, and the development of human-in-the...
1904.11560
Morteza Hoseinzadeh
Morteza Hoseinzadeh
A Survey on Tiering and Caching in High-Performance Storage Systems
Ph.D. Research Exam Report
null
null
null
cs.AR cs.OS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Although every individual invented storage technology made a big step towards perfection, none of them is spotless. Different data store essentials such as performance, availability, and recovery requirements have not met together in a single economically affordable medium, yet. One of the most influential factors is...
[ { "created": "Thu, 25 Apr 2019 19:57:31 GMT", "version": "v1" } ]
2019-04-29
[ [ "Hoseinzadeh", "Morteza", "" ] ]
Although every individual invented storage technology made a big step towards perfection, none of them is spotless. Different data store essentials such as performance, availability, and recovery requirements have not met together in a single economically affordable medium, yet. One of the most influential factors is p...
2001.11844
Diep Do Ngoc
Do Ngoc Diep
Statistical Tests and Confidential Intervals as Thresholds for Quantum Neural Networks
LaTeX2e, no figure
null
null
null
cs.ET cs.LG quant-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Some basic quantum neural networks were analyzed and constructed in the recent work of the author \cite{dndiep3}, published in International Journal of Theoretical Physics (2020). In particular the Least Quare Problem (LSP) and the Linear Regression Problem (LRP) was discussed. In this second paper we continue to ana...
[ { "created": "Thu, 30 Jan 2020 05:41:04 GMT", "version": "v1" } ]
2020-02-03
[ [ "Diep", "Do Ngoc", "" ] ]
Some basic quantum neural networks were analyzed and constructed in the recent work of the author \cite{dndiep3}, published in International Journal of Theoretical Physics (2020). In particular the Least Quare Problem (LSP) and the Linear Regression Problem (LRP) was discussed. In this second paper we continue to analy...
2205.10122
Diego Arg\"uello Ron
Egor Manuylovich, Diego Arg\"uello Ron, Morteza Kamalian-Kopae, Sergei Turitsyn
Stochastic resonance neurons in artificial neural networks
null
null
null
null
cs.NE cs.ET cs.LG physics.comp-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Many modern applications of the artificial neural networks ensue large number of layers making traditional digital implementations increasingly complex. Optical neural networks offer parallel processing at high bandwidth, but have the challenge of noise accumulation. We propose here a new type of neural networks usin...
[ { "created": "Fri, 6 May 2022 18:42:36 GMT", "version": "v1" }, { "created": "Tue, 23 Aug 2022 12:02:23 GMT", "version": "v2" } ]
2022-08-24
[ [ "Manuylovich", "Egor", "" ], [ "Ron", "Diego Argüello", "" ], [ "Kamalian-Kopae", "Morteza", "" ], [ "Turitsyn", "Sergei", "" ] ]
Many modern applications of the artificial neural networks ensue large number of layers making traditional digital implementations increasingly complex. Optical neural networks offer parallel processing at high bandwidth, but have the challenge of noise accumulation. We propose here a new type of neural networks using ...
1411.0198
Flion Tang
Changbing Tang, Ang Li, and Xiang Li
When reputation enforces evolutionary cooperation in unreliable MANETs
12pages, 11 figures
null
null
null
cs.GT cs.NI
http://creativecommons.org/licenses/by-nc-sa/3.0/
In self-organized mobile ad hoc networks (MANETs), network functions rely on cooperation of self-interested nodes, where a challenge is to enforce their mutual cooperation. In this paper, we study cooperative packet forwarding in a one-hop unreliable channel which results from loss of packets and noisy observation of...
[ { "created": "Sun, 2 Nov 2014 03:13:23 GMT", "version": "v1" } ]
2014-11-04
[ [ "Tang", "Changbing", "" ], [ "Li", "Ang", "" ], [ "Li", "Xiang", "" ] ]
In self-organized mobile ad hoc networks (MANETs), network functions rely on cooperation of self-interested nodes, where a challenge is to enforce their mutual cooperation. In this paper, we study cooperative packet forwarding in a one-hop unreliable channel which results from loss of packets and noisy observation of t...
2002.03415
Arsen Vasilyan
Ronitt Rubinfeld, Arsen Vasilyan
Monotone probability distributions over the Boolean cube can be learned with sublinear samples
null
null
10.4230/LIPIcs.ITCS.2020.28
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A probability distribution over the Boolean cube is monotone if flipping the value of a coordinate from zero to one can only increase the probability of an element. Given samples of an unknown monotone distribution over the Boolean cube, we give (to our knowledge) the first algorithm that learns an approximation of t...
[ { "created": "Sun, 9 Feb 2020 18:17:08 GMT", "version": "v1" } ]
2020-02-11
[ [ "Rubinfeld", "Ronitt", "" ], [ "Vasilyan", "Arsen", "" ] ]
A probability distribution over the Boolean cube is monotone if flipping the value of a coordinate from zero to one can only increase the probability of an element. Given samples of an unknown monotone distribution over the Boolean cube, we give (to our knowledge) the first algorithm that learns an approximation of the...
2308.09036
Liang Pan
Liang Pan, Jingbo Wang, Buzhen Huang, Junyu Zhang, Haofan Wang, Xu Tang, Yangang Wang
Synthesizing Physically Plausible Human Motions in 3D Scenes
null
null
null
null
cs.CV cs.AI cs.GR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Synthesizing physically plausible human motions in 3D scenes is a challenging problem. Kinematics-based methods cannot avoid inherent artifacts (e.g., penetration and foot skating) due to the lack of physical constraints. Meanwhile, existing physics-based methods cannot generalize to multi-object scenarios since the ...
[ { "created": "Thu, 17 Aug 2023 15:17:49 GMT", "version": "v1" } ]
2023-08-21
[ [ "Pan", "Liang", "" ], [ "Wang", "Jingbo", "" ], [ "Huang", "Buzhen", "" ], [ "Zhang", "Junyu", "" ], [ "Wang", "Haofan", "" ], [ "Tang", "Xu", "" ], [ "Wang", "Yangang", "" ] ]
Synthesizing physically plausible human motions in 3D scenes is a challenging problem. Kinematics-based methods cannot avoid inherent artifacts (e.g., penetration and foot skating) due to the lack of physical constraints. Meanwhile, existing physics-based methods cannot generalize to multi-object scenarios since the po...
2206.06355
Mustafa Abdallah
Mustafa Abdallah, Byung-Gun Joung, Wo Jae Lee, Charilaos Mousoulis, John W. Sutherland, and Saurabh Bagchi
Anomaly Detection and Inter-Sensor Transfer Learning on Smart Manufacturing Datasets
arXiv admin note: substantial text overlap with arXiv:2102.05814
null
null
null
cs.LG cs.AI cs.NE
http://creativecommons.org/licenses/by/4.0/
Smart manufacturing systems are being deployed at a growing rate because of their ability to interpret a wide variety of sensed information and act on the knowledge gleaned from system observations. In many cases, the principal goal of the smart manufacturing system is to rapidly detect (or anticipate) failures to re...
[ { "created": "Mon, 13 Jun 2022 17:51:24 GMT", "version": "v1" } ]
2022-06-14
[ [ "Abdallah", "Mustafa", "" ], [ "Joung", "Byung-Gun", "" ], [ "Lee", "Wo Jae", "" ], [ "Mousoulis", "Charilaos", "" ], [ "Sutherland", "John W.", "" ], [ "Bagchi", "Saurabh", "" ] ]
Smart manufacturing systems are being deployed at a growing rate because of their ability to interpret a wide variety of sensed information and act on the knowledge gleaned from system observations. In many cases, the principal goal of the smart manufacturing system is to rapidly detect (or anticipate) failures to redu...
2404.16393
Ana Klimovic
Lazar Cvetkovi\'c, Fran\c{c}ois Costa, Mihajlo Djokic, Michal Friedman, Ana Klimovic
Dirigent: Lightweight Serverless Orchestration
null
null
null
null
cs.DC cs.OS
http://creativecommons.org/licenses/by-sa/4.0/
While Function as a Service (FaaS) platforms can initialize function sandboxes on worker nodes in 10-100s of milliseconds, the latency to schedule functions in real FaaS clusters can be orders of magnitude higher. We find that the current approach of building FaaS cluster managers on top of legacy orchestration syste...
[ { "created": "Thu, 25 Apr 2024 08:01:11 GMT", "version": "v1" } ]
2024-04-26
[ [ "Cvetković", "Lazar", "" ], [ "Costa", "François", "" ], [ "Djokic", "Mihajlo", "" ], [ "Friedman", "Michal", "" ], [ "Klimovic", "Ana", "" ] ]
While Function as a Service (FaaS) platforms can initialize function sandboxes on worker nodes in 10-100s of milliseconds, the latency to schedule functions in real FaaS clusters can be orders of magnitude higher. We find that the current approach of building FaaS cluster managers on top of legacy orchestration systems...
2009.13521
Ian Malloy
Ian Malloy
Zero-Knowledge Games
14 pages, 1 figure, 5 tables
null
null
null
cs.GT cs.AI
http://creativecommons.org/licenses/by-nc-sa/4.0/
In this paper we model a game such that all strategies are non-revealing, with imperfect recall and incomplete information. We also introduce a modified sliding-block code as a linear transformation which generates common knowledge of how informed a player is. Ultimately, we see that between two players in a zero-kno...
[ { "created": "Mon, 28 Sep 2020 16:04:52 GMT", "version": "v1" }, { "created": "Tue, 13 Apr 2021 19:50:06 GMT", "version": "v2" }, { "created": "Fri, 10 May 2024 19:52:36 GMT", "version": "v3" }, { "created": "Sat, 18 May 2024 21:43:01 GMT", "version": "v4" }, { "c...
2024-05-24
[ [ "Malloy", "Ian", "" ] ]
In this paper we model a game such that all strategies are non-revealing, with imperfect recall and incomplete information. We also introduce a modified sliding-block code as a linear transformation which generates common knowledge of how informed a player is. Ultimately, we see that between two players in a zero-knowl...
1509.05330
Harry Boyer
Ali Hamada Fakra (PIMENT), Fr\'ed\'eric Miranville (PIMENT), Dimitri Bigot (PIMENT), Harry Boyer (PIMENT)
Elements of Validation of Artificial Lighting through the Software CODYRUN: Application to a Test Case of the International Commission on Illumination (CIE)
IASTED Power and Energy Systems 2010, Sep 2010, Gaborone, Botswana. 2010
null
null
null
cs.GR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
CODYRUN is a software for computational aeraulic and thermal simulation in buildings developed by the Laboratory of Building Physics and Systems (L.P.B.S). Numerical simulation codes of artificial lighting have been introduced to extend the tool capacity. These calculation codes are able to predict the amount of ligh...
[ { "created": "Tue, 15 Sep 2015 09:32:17 GMT", "version": "v1" } ]
2015-09-18
[ [ "Fakra", "Ali Hamada", "", "PIMENT" ], [ "Miranville", "Frédéric", "", "PIMENT" ], [ "Bigot", "Dimitri", "", "PIMENT" ], [ "Boyer", "Harry", "", "PIMENT" ] ]
CODYRUN is a software for computational aeraulic and thermal simulation in buildings developed by the Laboratory of Building Physics and Systems (L.P.B.S). Numerical simulation codes of artificial lighting have been introduced to extend the tool capacity. These calculation codes are able to predict the amount of light ...
1804.01615
Ahmad Taha
Nafiseh Ebrahimi and Sebastian Nugroho and Ahmad F. Taha and Nikolaos Gatsis and Wei Gao and Amir Jafari
Dynamic Actuator Selection and Robust State-Feedback Control of Networked Soft Actuators
To appear at the 2018 International Conference on Robotics and Automation (ICRA), Brisbane, Australia, May 21, 2018--May 25, 2018
null
null
null
cs.SY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The design of robots that are light, soft, powerful is a grand challenge. Since they can easily adapt to dynamic environments, soft robotic systems have the potential of changing the status-quo of bulky robotics. A crucial component of soft robotics is a soft actuator that is activated by external stimuli to generate...
[ { "created": "Wed, 4 Apr 2018 22:03:05 GMT", "version": "v1" } ]
2018-04-06
[ [ "Ebrahimi", "Nafiseh", "" ], [ "Nugroho", "Sebastian", "" ], [ "Taha", "Ahmad F.", "" ], [ "Gatsis", "Nikolaos", "" ], [ "Gao", "Wei", "" ], [ "Jafari", "Amir", "" ] ]
The design of robots that are light, soft, powerful is a grand challenge. Since they can easily adapt to dynamic environments, soft robotic systems have the potential of changing the status-quo of bulky robotics. A crucial component of soft robotics is a soft actuator that is activated by external stimuli to generate d...
2002.00178
Pierre Wolinski
Pierre Wolinski, Guillaume Charpiat, Yann Ollivier
An Equivalence between Bayesian Priors and Penalties in Variational Inference
null
null
null
null
cs.LG math.ST stat.ML stat.TH
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In machine learning, it is common to optimize the parameters of a probabilistic model, modulated by an ad hoc regularization term that penalizes some values of the parameters. Regularization terms appear naturally in Variational Inference, a tractable way to approximate Bayesian posteriors: the loss to optimize conta...
[ { "created": "Sat, 1 Feb 2020 09:48:51 GMT", "version": "v1" }, { "created": "Wed, 26 May 2021 10:11:57 GMT", "version": "v2" }, { "created": "Wed, 7 Feb 2024 13:17:55 GMT", "version": "v3" } ]
2024-02-08
[ [ "Wolinski", "Pierre", "" ], [ "Charpiat", "Guillaume", "" ], [ "Ollivier", "Yann", "" ] ]
In machine learning, it is common to optimize the parameters of a probabilistic model, modulated by an ad hoc regularization term that penalizes some values of the parameters. Regularization terms appear naturally in Variational Inference, a tractable way to approximate Bayesian posteriors: the loss to optimize contain...
1809.07075
Judith B\"utepage
Judith B\"utepage, Danica Kragic
Detect, anticipate and generate: Semi-supervised recurrent latent variable models for human activity modeling
This paper has been accepted at the IROS 2018 workshop "Human-Robot Cooperation and Collaboration in Manipulation: Advancements and Challenges"
null
null
null
cs.CV
http://creativecommons.org/licenses/by-nc-sa/4.0/
Successful Human-Robot collaboration requires a predictive model of human behavior. The robot needs to be able to recognize current goals and actions and to predict future activities in a given context. However, the spatio-temporal sequence of human actions is difficult to model since latent factors such as intention...
[ { "created": "Wed, 19 Sep 2018 09:04:21 GMT", "version": "v1" } ]
2018-09-20
[ [ "Bütepage", "Judith", "" ], [ "Kragic", "Danica", "" ] ]
Successful Human-Robot collaboration requires a predictive model of human behavior. The robot needs to be able to recognize current goals and actions and to predict future activities in a given context. However, the spatio-temporal sequence of human actions is difficult to model since latent factors such as intention, ...
2109.02955
Katsuyuki Nakamura
Katsuyuki Nakamura, Hiroki Ohashi, Mitsuhiro Okada
Sensor-Augmented Egocentric-Video Captioning with Dynamic Modal Attention
Accepted to ACM Multimedia (ACMMM) 2021
null
10.1145/3474085.3475557
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Automatically describing video, or video captioning, has been widely studied in the multimedia field. This paper proposes a new task of sensor-augmented egocentric-video captioning, a newly constructed dataset for it called MMAC Captions, and a method for the newly proposed task that effectively utilizes multi-modal ...
[ { "created": "Tue, 7 Sep 2021 09:22:09 GMT", "version": "v1" } ]
2021-09-08
[ [ "Nakamura", "Katsuyuki", "" ], [ "Ohashi", "Hiroki", "" ], [ "Okada", "Mitsuhiro", "" ] ]
Automatically describing video, or video captioning, has been widely studied in the multimedia field. This paper proposes a new task of sensor-augmented egocentric-video captioning, a newly constructed dataset for it called MMAC Captions, and a method for the newly proposed task that effectively utilizes multi-modal da...
1409.2003
Vojt\v{e}ch Vorel
Vojt\v{e}ch Vorel
Complexity of a Problem Concerning Reset Words for Eulerian Binary Automata
Extended version of a paper presented at LATA 2014
null
null
null
cs.FL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A word is called a reset word for a deterministic finite automaton if it maps all the states of the automaton to a unique state. Deciding about the existence of a reset word of a given maximum length for a given automaton is known to be an NP-complete problem. We prove that it remains NP-complete even if restricted t...
[ { "created": "Sat, 6 Sep 2014 10:33:00 GMT", "version": "v1" } ]
2014-09-09
[ [ "Vorel", "Vojtěch", "" ] ]
A word is called a reset word for a deterministic finite automaton if it maps all the states of the automaton to a unique state. Deciding about the existence of a reset word of a given maximum length for a given automaton is known to be an NP-complete problem. We prove that it remains NP-complete even if restricted to ...
2209.14364
Alexandru Munteanu
Alexandru Munteanu, Marian Neagul
Semantic Segmentation of Vegetation in Remote Sensing Imagery Using Deep Learning
Masters thesis presented in 2021 at the West University of Timisoara, faculty of Mathematics and Computer Science
null
null
null
cs.CV cs.AI
http://creativecommons.org/licenses/by/4.0/
In recent years, the geospatial industry has been developing at a steady pace. This growth implies the addition of satellite constellations that produce a copious supply of satellite imagery and other Remote Sensing data on a daily basis. Sometimes, this information, even if in some cases we are referring to publicly...
[ { "created": "Wed, 28 Sep 2022 18:51:59 GMT", "version": "v1" } ]
2022-09-30
[ [ "Munteanu", "Alexandru", "" ], [ "Neagul", "Marian", "" ] ]
In recent years, the geospatial industry has been developing at a steady pace. This growth implies the addition of satellite constellations that produce a copious supply of satellite imagery and other Remote Sensing data on a daily basis. Sometimes, this information, even if in some cases we are referring to publicly a...
2402.08621
Mohammad Pedramfar
Mohammad Pedramfar, Vaneet Aggarwal
A Generalized Approach to Online Convex Optimization
null
null
null
null
cs.LG math.OC stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we analyze the problem of online convex optimization in different settings. We show that any algorithm for online linear optimization with fully adaptive adversaries is an algorithm for online convex optimization. We also show that any such algorithm that requires full-information feedback may be trans...
[ { "created": "Tue, 13 Feb 2024 17:42:27 GMT", "version": "v1" }, { "created": "Mon, 13 May 2024 23:14:37 GMT", "version": "v2" } ]
2024-05-15
[ [ "Pedramfar", "Mohammad", "" ], [ "Aggarwal", "Vaneet", "" ] ]
In this paper, we analyze the problem of online convex optimization in different settings. We show that any algorithm for online linear optimization with fully adaptive adversaries is an algorithm for online convex optimization. We also show that any such algorithm that requires full-information feedback may be transfo...
2209.10740
N M Anoop Krishnan
Suresh Bishnoi, Ravinder Bhattoo, Sayan Ranu, and N. M. Anoop Krishnan
Enhancing the Inductive Biases of Graph Neural ODE for Modeling Dynamical Systems
33 pages, 23 figures, Published as a conference paper at ICLR 2023
null
null
null
cs.LG nlin.CD
http://creativecommons.org/licenses/by-nc-nd/4.0/
Neural networks with physics based inductive biases such as Lagrangian neural networks (LNN), and Hamiltonian neural networks (HNN) learn the dynamics of physical systems by encoding strong inductive biases. Alternatively, Neural ODEs with appropriate inductive biases have also been shown to give similar performances...
[ { "created": "Thu, 22 Sep 2022 02:20:29 GMT", "version": "v1" }, { "created": "Sat, 15 Jun 2024 13:23:00 GMT", "version": "v2" } ]
2024-06-18
[ [ "Bishnoi", "Suresh", "" ], [ "Bhattoo", "Ravinder", "" ], [ "Ranu", "Sayan", "" ], [ "Krishnan", "N. M. Anoop", "" ] ]
Neural networks with physics based inductive biases such as Lagrangian neural networks (LNN), and Hamiltonian neural networks (HNN) learn the dynamics of physical systems by encoding strong inductive biases. Alternatively, Neural ODEs with appropriate inductive biases have also been shown to give similar performances. ...
1905.01590
Mostafa Ghobadi
Mostafa Ghobadi
Stability Control of Walking Biped Robots based on Total Momentum
in Farsi, https://ganj.irandoc.ac.ir/#/articles/8aec27fb776cf8f94bcfcba26d06b0eb
null
null
null
cs.RO math.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Principle Equation of Motion (for walkers) is derived that later results in introducing two piecewise-continuous dynamical systems namely Simplified Walking Model (SWM) and Complete Walking Model (CWM) which both describe the behavior of walker with emphasis on the motion in horizontal plane. By making some realistic...
[ { "created": "Sun, 5 May 2019 03:15:04 GMT", "version": "v1" } ]
2019-05-07
[ [ "Ghobadi", "Mostafa", "" ] ]
Principle Equation of Motion (for walkers) is derived that later results in introducing two piecewise-continuous dynamical systems namely Simplified Walking Model (SWM) and Complete Walking Model (CWM) which both describe the behavior of walker with emphasis on the motion in horizontal plane. By making some realistic a...
2405.11281
Jiahao You
Ziye Jia, Jiahao You, Chao Dong, Qihui Wu, Fuhui Zhou, Dusit Niyato, and Zhu Han
Cooperative Cognitive Dynamic System in UAV Swarms: Reconfigurable Mechanism and Framework
null
null
null
null
cs.DC cs.AI
http://creativecommons.org/licenses/by/4.0/
As the demands for immediate and effective responses increase in both civilian and military domains, the unmanned aerial vehicle (UAV) swarms emerge as effective solutions, in which multiple cooperative UAVs can work together to achieve specific goals. However, how to manage such complex systems to ensure real-time a...
[ { "created": "Sat, 18 May 2024 12:45:00 GMT", "version": "v1" } ]
2024-05-21
[ [ "Jia", "Ziye", "" ], [ "You", "Jiahao", "" ], [ "Dong", "Chao", "" ], [ "Wu", "Qihui", "" ], [ "Zhou", "Fuhui", "" ], [ "Niyato", "Dusit", "" ], [ "Han", "Zhu", "" ] ]
As the demands for immediate and effective responses increase in both civilian and military domains, the unmanned aerial vehicle (UAV) swarms emerge as effective solutions, in which multiple cooperative UAVs can work together to achieve specific goals. However, how to manage such complex systems to ensure real-time ada...
2006.07845
Prithviraj Dhar
Prithviraj Dhar, Joshua Gleason, Hossein Souri, Carlos D. Castillo, Rama Chellappa
Towards Gender-Neutral Face Descriptors for Mitigating Bias in Face Recognition
Under submission
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
State-of-the-art deep networks implicitly encode gender information while being trained for face recognition. Gender is often viewed as an important attribute with respect to identifying faces. However, the implicit encoding of gender information in face descriptors has two major issues: (a.) It makes the descriptors...
[ { "created": "Sun, 14 Jun 2020 08:54:03 GMT", "version": "v1" }, { "created": "Thu, 17 Sep 2020 06:25:31 GMT", "version": "v2" } ]
2020-09-18
[ [ "Dhar", "Prithviraj", "" ], [ "Gleason", "Joshua", "" ], [ "Souri", "Hossein", "" ], [ "Castillo", "Carlos D.", "" ], [ "Chellappa", "Rama", "" ] ]
State-of-the-art deep networks implicitly encode gender information while being trained for face recognition. Gender is often viewed as an important attribute with respect to identifying faces. However, the implicit encoding of gender information in face descriptors has two major issues: (a.) It makes the descriptors s...
2011.10520
Hugo Tessier
Hugo Tessier, Vincent Gripon, Mathieu L\'eonardon, Matthieu Arzel, Thomas Hannagan, David Bertrand
Rethinking Weight Decay For Efficient Neural Network Pruning
23 pages, 18 figures, published at Journal of Imaging, update : added new results, rewrite
Journal of Imaging 8 (2022), no. 3: 64
10.3390/jimaging8030064
null
cs.NE
http://creativecommons.org/licenses/by/4.0/
Introduced in the late 1980s for generalization purposes, pruning has now become a staple for compressing deep neural networks. Despite many innovations in recent decades, pruning approaches still face core issues that hinder their performance or scalability. Drawing inspiration from early work in the field, and espe...
[ { "created": "Fri, 20 Nov 2020 17:25:53 GMT", "version": "v1" }, { "created": "Tue, 22 Dec 2020 15:30:19 GMT", "version": "v2" }, { "created": "Tue, 16 Feb 2021 08:28:53 GMT", "version": "v3" }, { "created": "Wed, 9 Mar 2022 15:06:05 GMT", "version": "v4" } ]
2022-03-10
[ [ "Tessier", "Hugo", "" ], [ "Gripon", "Vincent", "" ], [ "Léonardon", "Mathieu", "" ], [ "Arzel", "Matthieu", "" ], [ "Hannagan", "Thomas", "" ], [ "Bertrand", "David", "" ] ]
Introduced in the late 1980s for generalization purposes, pruning has now become a staple for compressing deep neural networks. Despite many innovations in recent decades, pruning approaches still face core issues that hinder their performance or scalability. Drawing inspiration from early work in the field, and especi...
2004.00184
Michel Besserve
Michel Besserve, R\'emy Sun, Dominik Janzing and Bernhard Sch\"olkopf
A theory of independent mechanisms for extrapolation in generative models
21 pages
null
null
null
cs.LG cs.CV stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Generative models can be trained to emulate complex empirical data, but are they useful to make predictions in the context of previously unobserved environments? An intuitive idea to promote such extrapolation capabilities is to have the architecture of such model reflect a causal graph of the true data generating pr...
[ { "created": "Wed, 1 Apr 2020 01:01:43 GMT", "version": "v1" }, { "created": "Fri, 31 Dec 2021 18:33:04 GMT", "version": "v2" } ]
2022-01-03
[ [ "Besserve", "Michel", "" ], [ "Sun", "Rémy", "" ], [ "Janzing", "Dominik", "" ], [ "Schölkopf", "Bernhard", "" ] ]
Generative models can be trained to emulate complex empirical data, but are they useful to make predictions in the context of previously unobserved environments? An intuitive idea to promote such extrapolation capabilities is to have the architecture of such model reflect a causal graph of the true data generating proc...
2404.01583
Yinqiu Liu
Yinqiu Liu, Ruichen Zhang, Hongyang Du, Dusit Niyato, Jiawen Kang, Zehui Xiong, Dong In Kim
Defining Problem from Solutions: Inverse Reinforcement Learning (IRL) and Its Applications for Next-Generation Networking
9 pages
null
null
null
cs.NI
http://creativecommons.org/licenses/by/4.0/
Performance optimization is a critical concern in networking, on which Deep Reinforcement Learning (DRL) has achieved great success. Nonetheless, DRL training relies on precisely defined reward functions, which formulate the optimization objective and indicate the positive/negative progress towards the optimal. With ...
[ { "created": "Tue, 2 Apr 2024 02:23:35 GMT", "version": "v1" } ]
2024-04-03
[ [ "Liu", "Yinqiu", "" ], [ "Zhang", "Ruichen", "" ], [ "Du", "Hongyang", "" ], [ "Niyato", "Dusit", "" ], [ "Kang", "Jiawen", "" ], [ "Xiong", "Zehui", "" ], [ "Kim", "Dong In", "" ] ]
Performance optimization is a critical concern in networking, on which Deep Reinforcement Learning (DRL) has achieved great success. Nonetheless, DRL training relies on precisely defined reward functions, which formulate the optimization objective and indicate the positive/negative progress towards the optimal. With th...
2212.10624
Yufan Li Mr.
Yufan Li, Zhou Fan, Subhabrata Sen, Yihong Wu
Random linear estimation with rotationally-invariant designs: Asymptotics at high temperature
null
null
null
null
cs.IT math-ph math.IT math.MP
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We study estimation in the linear model $y=A\beta^\star+\epsilon$, in a Bayesian setting where $\beta^\star$ has an entrywise i.i.d. prior and the design $A$ is rotationally-invariant in law. In the large system limit as dimension and sample size increase proportionally, a set of related conjectures have been postula...
[ { "created": "Tue, 20 Dec 2022 19:59:58 GMT", "version": "v1" } ]
2022-12-22
[ [ "Li", "Yufan", "" ], [ "Fan", "Zhou", "" ], [ "Sen", "Subhabrata", "" ], [ "Wu", "Yihong", "" ] ]
We study estimation in the linear model $y=A\beta^\star+\epsilon$, in a Bayesian setting where $\beta^\star$ has an entrywise i.i.d. prior and the design $A$ is rotationally-invariant in law. In the large system limit as dimension and sample size increase proportionally, a set of related conjectures have been postulate...
2108.06594
Doseok Jang
Doseok Jang, Lucas Spangher, Manan Khattar, Utkarsha Agwan, Selvaprabuh Nadarajah, Costas Spanos
Offline-Online Reinforcement Learning for Energy Pricing in Office Demand Response: Lowering Energy and Data Costs
arXiv admin note: text overlap with arXiv:2104.14670
null
null
null
cs.LG cs.AI
http://creativecommons.org/licenses/by-sa/4.0/
Our team is proposing to run a full-scale energy demand response experiment in an office building. Although this is an exciting endeavor which will provide value to the community, collecting training data for the reinforcement learning agent is costly and will be limited. In this work, we examine how offline training...
[ { "created": "Sat, 14 Aug 2021 17:29:59 GMT", "version": "v1" } ]
2021-08-21
[ [ "Jang", "Doseok", "" ], [ "Spangher", "Lucas", "" ], [ "Khattar", "Manan", "" ], [ "Agwan", "Utkarsha", "" ], [ "Nadarajah", "Selvaprabuh", "" ], [ "Spanos", "Costas", "" ] ]
Our team is proposing to run a full-scale energy demand response experiment in an office building. Although this is an exciting endeavor which will provide value to the community, collecting training data for the reinforcement learning agent is costly and will be limited. In this work, we examine how offline training c...
2010.14684
Maciej Besta
Maciej Besta, Marc Fischer, Tal Ben-Nun, Dimitri Stanojevic, Johannes De Fine Licht, Torsten Hoefler
Substream-Centric Maximum Matchings on FPGA
Best Paper finalist at ACM FPGA'19, invited to special issue of ACM TRETS'20
Proceedings of the ACM Transactions on Reconfigurable Technology and Systems (TRETS), 2020. Proceedings of the 27th ACM/SIGDA International Symposium on Field-Programmable Gate Arrays (FPGA), 2019
null
null
cs.DC cs.AR cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Developing high-performance and energy-efficient algorithms for maximum matchings is becoming increasingly important in social network analysis, computational sciences, scheduling, and others. In this work, we propose the first maximum matching algorithm designed for FPGAs; it is energy-efficient and has provable gua...
[ { "created": "Wed, 28 Oct 2020 00:31:27 GMT", "version": "v1" } ]
2020-10-29
[ [ "Besta", "Maciej", "" ], [ "Fischer", "Marc", "" ], [ "Ben-Nun", "Tal", "" ], [ "Stanojevic", "Dimitri", "" ], [ "Licht", "Johannes De Fine", "" ], [ "Hoefler", "Torsten", "" ] ]
Developing high-performance and energy-efficient algorithms for maximum matchings is becoming increasingly important in social network analysis, computational sciences, scheduling, and others. In this work, we propose the first maximum matching algorithm designed for FPGAs; it is energy-efficient and has provable guara...
2101.06495
Livia Elena Chatzieleftheriou
Livia Elena Chatzieleftheriou, Apostolos Destounis, Georgios Paschos and Iordanis Koutsopoulos
Blind Optimal User Association in Small-Cell Networks
To appear in IEEE International Conference on Computer Communication (INFOCOM) 2021
null
null
null
cs.NI
http://creativecommons.org/licenses/by-nc-nd/4.0/
We learn optimal user association policies for traffic from different locations to Access Points(APs), in the presence of unknown dynamic traffic demand. We aim at minimizing a broad family of $\alpha$-fair cost functions that express various objectives in load assignment in the wireless downlink, such as total load ...
[ { "created": "Sat, 16 Jan 2021 18:12:39 GMT", "version": "v1" } ]
2021-01-19
[ [ "Chatzieleftheriou", "Livia Elena", "" ], [ "Destounis", "Apostolos", "" ], [ "Paschos", "Georgios", "" ], [ "Koutsopoulos", "Iordanis", "" ] ]
We learn optimal user association policies for traffic from different locations to Access Points(APs), in the presence of unknown dynamic traffic demand. We aim at minimizing a broad family of $\alpha$-fair cost functions that express various objectives in load assignment in the wireless downlink, such as total load or...
1604.07342
Mahyar Najibi
Bahadir Ozdemir and Mahyar Najibi and Larry S. Davis
Supervised Incremental Hashing
14 pages, 6 figures
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We propose an incremental strategy for learning hash functions with kernels for large-scale image search. Our method is based on a two-stage classification framework that treats binary codes as intermediate variables between the feature space and the semantic space. In the first stage of classification, binary codes ...
[ { "created": "Mon, 25 Apr 2016 17:50:05 GMT", "version": "v1" }, { "created": "Thu, 9 Jun 2016 17:24:25 GMT", "version": "v2" } ]
2016-06-10
[ [ "Ozdemir", "Bahadir", "" ], [ "Najibi", "Mahyar", "" ], [ "Davis", "Larry S.", "" ] ]
We propose an incremental strategy for learning hash functions with kernels for large-scale image search. Our method is based on a two-stage classification framework that treats binary codes as intermediate variables between the feature space and the semantic space. In the first stage of classification, binary codes ar...
1804.00779
Chin-Wei Huang
Chin-Wei Huang, David Krueger, Alexandre Lacoste, Aaron Courville
Neural Autoregressive Flows
16 pages, 10 figures, 3 tables
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Normalizing flows and autoregressive models have been successfully combined to produce state-of-the-art results in density estimation, via Masked Autoregressive Flows (MAF), and to accelerate state-of-the-art WaveNet-based speech synthesis to 20x faster than real-time, via Inverse Autoregressive Flows (IAF). We unify...
[ { "created": "Tue, 3 Apr 2018 01:41:27 GMT", "version": "v1" } ]
2018-04-04
[ [ "Huang", "Chin-Wei", "" ], [ "Krueger", "David", "" ], [ "Lacoste", "Alexandre", "" ], [ "Courville", "Aaron", "" ] ]
Normalizing flows and autoregressive models have been successfully combined to produce state-of-the-art results in density estimation, via Masked Autoregressive Flows (MAF), and to accelerate state-of-the-art WaveNet-based speech synthesis to 20x faster than real-time, via Inverse Autoregressive Flows (IAF). We unify a...
2009.01188
Toktam Amanzadeh Oghaz
Ece \c{C}i\u{g}dem Mutlu, Toktam A. Oghaz, Jasser Jasser, Ege T\"ut\"unc\"uler, Amirarsalan Rajabi, Aida Tayebi, Ozlem Ozmen, Ivan Garibay
A Stance Data Set on Polarized Conversations on Twitter about the Efficacy of Hydroxychloroquine as a Treatment for COVID-19
11 pages, 3 figures
null
null
null
cs.SI cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
At the time of this study, the SARS-CoV-2 virus that caused the COVID-19 pandemic has spread significantly across the world. Considering the uncertainty about policies, health risks, financial difficulties, etc. the online media, specially the Twitter platform, is experiencing a high volume of activity related to thi...
[ { "created": "Wed, 19 Aug 2020 21:58:58 GMT", "version": "v1" }, { "created": "Sat, 5 Sep 2020 18:37:17 GMT", "version": "v2" } ]
2020-09-08
[ [ "Mutlu", "Ece Çiğdem", "" ], [ "Oghaz", "Toktam A.", "" ], [ "Jasser", "Jasser", "" ], [ "Tütüncüler", "Ege", "" ], [ "Rajabi", "Amirarsalan", "" ], [ "Tayebi", "Aida", "" ], [ "Ozmen", "Ozlem", "" ], [...
At the time of this study, the SARS-CoV-2 virus that caused the COVID-19 pandemic has spread significantly across the world. Considering the uncertainty about policies, health risks, financial difficulties, etc. the online media, specially the Twitter platform, is experiencing a high volume of activity related to this ...
2302.07478
Hongtao Zhong
Hongtao Zhong, Zhonghao Chen, Wenqin Huangfu, Chen Wang, Yixin Xu, Tianyi Wang, Yao Yu, Yongpan Liu, Vijaykrishnan Narayanan, Huazhong Yang, Xueqing Li
ASMCap: An Approximate String Matching Accelerator for Genome Sequence Analysis Based on Capacitive Content Addressable Memory
Accepted by Design Automation Conference (DAC) 2023
null
null
null
cs.AR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Genome sequence analysis is a powerful tool in medical and scientific research. Considering the inevitable sequencing errors and genetic variations, approximate string matching (ASM) has been adopted in practice for genome sequencing. However, with exponentially increasing bio-data, ASM hardware acceleration is facin...
[ { "created": "Wed, 15 Feb 2023 05:49:56 GMT", "version": "v1" } ]
2023-02-16
[ [ "Zhong", "Hongtao", "" ], [ "Chen", "Zhonghao", "" ], [ "Huangfu", "Wenqin", "" ], [ "Wang", "Chen", "" ], [ "Xu", "Yixin", "" ], [ "Wang", "Tianyi", "" ], [ "Yu", "Yao", "" ], [ "Liu", "Yongpan...
Genome sequence analysis is a powerful tool in medical and scientific research. Considering the inevitable sequencing errors and genetic variations, approximate string matching (ASM) has been adopted in practice for genome sequencing. However, with exponentially increasing bio-data, ASM hardware acceleration is facing ...
2009.11160
Junichiro Iwasawa
Junichiro Iwasawa, Yuichiro Hirano and Yohei Sugawara
Label-Efficient Multi-Task Segmentation using Contrastive Learning
Accepted to MICCAI BrainLes 2020 workshop
null
null
null
cs.CV q-bio.TO
http://creativecommons.org/licenses/by/4.0/
Obtaining annotations for 3D medical images is expensive and time-consuming, despite its importance for automating segmentation tasks. Although multi-task learning is considered an effective method for training segmentation models using small amounts of annotated data, a systematic understanding of various subtasks i...
[ { "created": "Wed, 23 Sep 2020 14:12:17 GMT", "version": "v1" } ]
2020-09-24
[ [ "Iwasawa", "Junichiro", "" ], [ "Hirano", "Yuichiro", "" ], [ "Sugawara", "Yohei", "" ] ]
Obtaining annotations for 3D medical images is expensive and time-consuming, despite its importance for automating segmentation tasks. Although multi-task learning is considered an effective method for training segmentation models using small amounts of annotated data, a systematic understanding of various subtasks is ...
2212.05153
Tamay Besiroglu
Ege Erdil and Tamay Besiroglu
Algorithmic progress in computer vision
null
null
null
null
cs.CV cs.LG
http://creativecommons.org/licenses/by/4.0/
We investigate algorithmic progress in image classification on ImageNet, perhaps the most well-known test bed for computer vision. We estimate a model, informed by work on neural scaling laws, and infer a decomposition of progress into the scaling of compute, data, and algorithms. Using Shapley values to attribute pe...
[ { "created": "Sat, 10 Dec 2022 00:18:05 GMT", "version": "v1" }, { "created": "Fri, 16 Dec 2022 18:18:59 GMT", "version": "v2" }, { "created": "Sun, 15 Jan 2023 20:27:39 GMT", "version": "v3" }, { "created": "Thu, 24 Aug 2023 15:15:44 GMT", "version": "v4" } ]
2023-08-25
[ [ "Erdil", "Ege", "" ], [ "Besiroglu", "Tamay", "" ] ]
We investigate algorithmic progress in image classification on ImageNet, perhaps the most well-known test bed for computer vision. We estimate a model, informed by work on neural scaling laws, and infer a decomposition of progress into the scaling of compute, data, and algorithms. Using Shapley values to attribute perf...
0705.3992
Tadashi Wadyama
Tadashi Wadayama
Average Stopping Set Weight Distribution of Redundant Random Matrix Ensembles
14 pages, 7 figures, Conference version to appear at the 2007 IEEE International Symposium on Information Theory, Nice, France, June 2007
null
10.1109/ISIT.2007.4557663
null
cs.IT math.IT
null
In this paper, redundant random matrix ensembles (abbreviated as redundant random ensembles) are defined and their stopping set (SS) weight distributions are analyzed. A redundant random ensemble consists of a set of binary matrices with linearly dependent rows. These linearly dependent rows (redundant rows) signific...
[ { "created": "Mon, 28 May 2007 01:55:36 GMT", "version": "v1" } ]
2016-11-15
[ [ "Wadayama", "Tadashi", "" ] ]
In this paper, redundant random matrix ensembles (abbreviated as redundant random ensembles) are defined and their stopping set (SS) weight distributions are analyzed. A redundant random ensemble consists of a set of binary matrices with linearly dependent rows. These linearly dependent rows (redundant rows) significan...
2405.20067
Stavros Diolatzis
Stavros Diolatzis, Tobias Zirr, Alexandr Kuznetsov, Georgios Kopanas, Anton Kaplanyan
N-Dimensional Gaussians for Fitting of High Dimensional Functions
https://www.sdiolatz.info/ndg-fitting/
null
10.1145/3641519.3657502
null
cs.CV cs.GR
http://creativecommons.org/licenses/by/4.0/
In the wake of many new ML-inspired approaches for reconstructing and representing high-quality 3D content, recent hybrid and explicitly learned representations exhibit promising performance and quality characteristics. However, their scaling to higher dimensions is challenging, e.g. when accounting for dynamic conte...
[ { "created": "Thu, 30 May 2024 13:56:58 GMT", "version": "v1" }, { "created": "Fri, 31 May 2024 08:11:24 GMT", "version": "v2" } ]
2024-06-03
[ [ "Diolatzis", "Stavros", "" ], [ "Zirr", "Tobias", "" ], [ "Kuznetsov", "Alexandr", "" ], [ "Kopanas", "Georgios", "" ], [ "Kaplanyan", "Anton", "" ] ]
In the wake of many new ML-inspired approaches for reconstructing and representing high-quality 3D content, recent hybrid and explicitly learned representations exhibit promising performance and quality characteristics. However, their scaling to higher dimensions is challenging, e.g. when accounting for dynamic content...
2305.17812
Jin Ziqi
Ziqi Jin and Wei Lu
Tab-CoT: Zero-shot Tabular Chain of Thought
accepted by ACL 2023 Finding
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
The chain-of-though (CoT) prompting methods were successful in various natural language processing (NLP) tasks thanks to their ability to unveil the underlying complex reasoning processes. Such reasoning processes typically exhibit implicitly structured steps. Recent efforts also started investigating methods to enco...
[ { "created": "Sun, 28 May 2023 20:49:52 GMT", "version": "v1" } ]
2023-05-30
[ [ "Jin", "Ziqi", "" ], [ "Lu", "Wei", "" ] ]
The chain-of-though (CoT) prompting methods were successful in various natural language processing (NLP) tasks thanks to their ability to unveil the underlying complex reasoning processes. Such reasoning processes typically exhibit implicitly structured steps. Recent efforts also started investigating methods to encour...
1902.06410
Lana Sinapayen
Lana Sinapayen, Atsushi Masumori, Ikegami Takashi
Reactive, Proactive, and Inductive Agents: An evolutionary path for biological and artificial spiking networks
null
null
null
null
cs.NE cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Complex environments provide structured yet variable sensory inputs. To best exploit information from these environments, organisms must evolve the ability to anticipate consequences of unknown stimuli, and act on these predictions. We propose an evolutionary path for neural networks, leading an organism from reactiv...
[ { "created": "Mon, 18 Feb 2019 05:38:39 GMT", "version": "v1" }, { "created": "Mon, 15 Jul 2019 06:58:49 GMT", "version": "v2" } ]
2019-07-16
[ [ "Sinapayen", "Lana", "" ], [ "Masumori", "Atsushi", "" ], [ "Takashi", "Ikegami", "" ] ]
Complex environments provide structured yet variable sensory inputs. To best exploit information from these environments, organisms must evolve the ability to anticipate consequences of unknown stimuli, and act on these predictions. We propose an evolutionary path for neural networks, leading an organism from reactive ...
1904.02795
Aditya Vamsikrishna Mandalika
Aditya Mandalika, Sanjiban Choudhury, Oren Salzman and Siddhartha Srinivasa
Generalized Lazy Search for Robot Motion Planning: Interleaving Search and Edge Evaluation via Event-based Toggles
Accepted at International Conference on Automated Planning and Scheduling (ICAPS) 2019
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Lazy search algorithms can efficiently solve problems where edge evaluation is the bottleneck in computation, as is the case for robotic motion planning. The optimal algorithm in this class, LazySP, lazily restricts edge evaluation to only the shortest path. Doing so comes at the expense of search effort, i.e., LazyS...
[ { "created": "Thu, 4 Apr 2019 21:24:29 GMT", "version": "v1" }, { "created": "Mon, 8 Apr 2019 19:09:11 GMT", "version": "v2" }, { "created": "Wed, 26 Jun 2019 07:33:15 GMT", "version": "v3" }, { "created": "Mon, 22 Jul 2019 21:08:20 GMT", "version": "v4" } ]
2019-07-24
[ [ "Mandalika", "Aditya", "" ], [ "Choudhury", "Sanjiban", "" ], [ "Salzman", "Oren", "" ], [ "Srinivasa", "Siddhartha", "" ] ]
Lazy search algorithms can efficiently solve problems where edge evaluation is the bottleneck in computation, as is the case for robotic motion planning. The optimal algorithm in this class, LazySP, lazily restricts edge evaluation to only the shortest path. Doing so comes at the expense of search effort, i.e., LazySP ...
2404.15264
Jiahe Li
Jiahe Li, Jiawei Zhang, Xiao Bai, Jin Zheng, Xin Ning, Jun Zhou, Lin Gu
TalkingGaussian: Structure-Persistent 3D Talking Head Synthesis via Gaussian Splatting
Accepted at ECCV 2024. Project page: https://fictionarry.github.io/TalkingGaussian/
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Radiance fields have demonstrated impressive performance in synthesizing lifelike 3D talking heads. However, due to the difficulty in fitting steep appearance changes, the prevailing paradigm that presents facial motions by directly modifying point appearance may lead to distortions in dynamic regions. To tackle this...
[ { "created": "Tue, 23 Apr 2024 17:55:07 GMT", "version": "v1" }, { "created": "Fri, 5 Jul 2024 04:09:46 GMT", "version": "v2" } ]
2024-07-08
[ [ "Li", "Jiahe", "" ], [ "Zhang", "Jiawei", "" ], [ "Bai", "Xiao", "" ], [ "Zheng", "Jin", "" ], [ "Ning", "Xin", "" ], [ "Zhou", "Jun", "" ], [ "Gu", "Lin", "" ] ]
Radiance fields have demonstrated impressive performance in synthesizing lifelike 3D talking heads. However, due to the difficulty in fitting steep appearance changes, the prevailing paradigm that presents facial motions by directly modifying point appearance may lead to distortions in dynamic regions. To tackle this c...
2010.00840
Peng Xu
Peng Xu, Mostofa Patwary, Mohammad Shoeybi, Raul Puri, Pascale Fung, Anima Anandkumar and Bryan Catanzaro
MEGATRON-CNTRL: Controllable Story Generation with External Knowledge Using Large-Scale Language Models
Accepted in EMNLP 2020 main conference
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Existing pre-trained large language models have shown unparalleled generative capabilities. However, they are not controllable. In this paper, we propose MEGATRON-CNTRL, a novel framework that uses large-scale language models and adds control to text generation by incorporating an external knowledge base. Our framewo...
[ { "created": "Fri, 2 Oct 2020 08:07:12 GMT", "version": "v1" } ]
2020-10-05
[ [ "Xu", "Peng", "" ], [ "Patwary", "Mostofa", "" ], [ "Shoeybi", "Mohammad", "" ], [ "Puri", "Raul", "" ], [ "Fung", "Pascale", "" ], [ "Anandkumar", "Anima", "" ], [ "Catanzaro", "Bryan", "" ] ]
Existing pre-trained large language models have shown unparalleled generative capabilities. However, they are not controllable. In this paper, we propose MEGATRON-CNTRL, a novel framework that uses large-scale language models and adds control to text generation by incorporating an external knowledge base. Our framework...
2209.04242
Rand Muhtaseb
Rand Muhtaseb and Mohammad Yaqub
EchoCoTr: Estimation of the Left Ventricular Ejection Fraction from Spatiotemporal Echocardiography
null
null
null
null
cs.CV
http://creativecommons.org/licenses/by-nc-sa/4.0/
Learning spatiotemporal features is an important task for efficient video understanding especially in medical images such as echocardiograms. Convolutional neural networks (CNNs) and more recent vision transformers (ViTs) are the most commonly used methods with limitations per each. CNNs are good at capturing local c...
[ { "created": "Fri, 9 Sep 2022 11:01:59 GMT", "version": "v1" } ]
2022-09-12
[ [ "Muhtaseb", "Rand", "" ], [ "Yaqub", "Mohammad", "" ] ]
Learning spatiotemporal features is an important task for efficient video understanding especially in medical images such as echocardiograms. Convolutional neural networks (CNNs) and more recent vision transformers (ViTs) are the most commonly used methods with limitations per each. CNNs are good at capturing local con...
2011.10709
Kareem M. Attiah
Kareem M. Attiah, Foad Sohrabi, and Wei Yu
Deep Learning for Channel Sensing and Hybrid Precoding in TDD Massive MIMO OFDM Systems
15 Pages, 16 figures, Accepted at IEEE Transactions in Wireless Communications
null
10.1109/TWC.2022.3187790
null
cs.IT eess.SP math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper proposes a deep learning approach to channel sensing and downlink hybrid beamforming for massive multiple-input multiple-output systems operating in the time division duplex mode and employing either single-carrier or multicarrier transmission. The conventional precoding design involves a two-step process ...
[ { "created": "Sat, 21 Nov 2020 02:46:35 GMT", "version": "v1" }, { "created": "Sat, 2 Oct 2021 01:10:06 GMT", "version": "v2" }, { "created": "Wed, 29 Jun 2022 17:27:30 GMT", "version": "v3" } ]
2022-06-30
[ [ "Attiah", "Kareem M.", "" ], [ "Sohrabi", "Foad", "" ], [ "Yu", "Wei", "" ] ]
This paper proposes a deep learning approach to channel sensing and downlink hybrid beamforming for massive multiple-input multiple-output systems operating in the time division duplex mode and employing either single-carrier or multicarrier transmission. The conventional precoding design involves a two-step process of...
2403.09625
Fangfu Liu
Fangfu Liu, Hanyang Wang, Weiliang Chen, Haowen Sun, Yueqi Duan
Make-Your-3D: Fast and Consistent Subject-Driven 3D Content Generation
Project page: https://liuff19.github.io/Make-Your-3D
null
null
null
cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recent years have witnessed the strong power of 3D generation models, which offer a new level of creative flexibility by allowing users to guide the 3D content generation process through a single image or natural language. However, it remains challenging for existing 3D generation methods to create subject-driven 3D ...
[ { "created": "Thu, 14 Mar 2024 17:57:04 GMT", "version": "v1" } ]
2024-03-15
[ [ "Liu", "Fangfu", "" ], [ "Wang", "Hanyang", "" ], [ "Chen", "Weiliang", "" ], [ "Sun", "Haowen", "" ], [ "Duan", "Yueqi", "" ] ]
Recent years have witnessed the strong power of 3D generation models, which offer a new level of creative flexibility by allowing users to guide the 3D content generation process through a single image or natural language. However, it remains challenging for existing 3D generation methods to create subject-driven 3D co...
2003.14177
Micha{\l} Pilipczuk
Adam Paszke and Micha{\l} Pilipczuk
VC density of set systems defnable in tree-like graphs
14 pages, 1 figure
null
null
null
cs.LO cs.DM cs.FL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We study set systems definable in graphs using variants of logic with different expressive power. Our focus is on the notion of Vapnik-Chervonenkis density: the smallest possible degree of a polynomial bounding the cardinalities of restrictions of such set systems. On one hand, we prove that if $\varphi(\bar x,\bar y...
[ { "created": "Tue, 31 Mar 2020 13:21:59 GMT", "version": "v1" } ]
2020-04-01
[ [ "Paszke", "Adam", "" ], [ "Pilipczuk", "Michał", "" ] ]
We study set systems definable in graphs using variants of logic with different expressive power. Our focus is on the notion of Vapnik-Chervonenkis density: the smallest possible degree of a polynomial bounding the cardinalities of restrictions of such set systems. On one hand, we prove that if $\varphi(\bar x,\bar y)$...
2107.09833
Md Hafizul Islam Chowdhuryy
Md Hafizul Islam Chowdhuryy, Fan Yao
Leaking Secrets through Modern Branch Predictor in the Speculative World
Camera ready version will appear in a future issue of IEEE Transactions on Computers (TC). DOI: https://doi.org/10.1109/TC.2021.3122830
null
10.1109/TC.2021.3122830
null
cs.CR cs.AR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Transient execution attacks that exploit speculation have raised significant concerns in computer systems. Typically, branch predictors are leveraged to trigger mis-speculation in transient execution attacks. In this work, we demonstrate a new class of speculation-based attack that targets branch prediction unit (BPU...
[ { "created": "Wed, 21 Jul 2021 02:01:12 GMT", "version": "v1" }, { "created": "Fri, 29 Oct 2021 22:14:37 GMT", "version": "v2" } ]
2021-11-02
[ [ "Chowdhuryy", "Md Hafizul Islam", "" ], [ "Yao", "Fan", "" ] ]
Transient execution attacks that exploit speculation have raised significant concerns in computer systems. Typically, branch predictors are leveraged to trigger mis-speculation in transient execution attacks. In this work, we demonstrate a new class of speculation-based attack that targets branch prediction unit (BPU)....
2212.14448
Sergey Saltykov
Sergey A. Saltykov
On the utility of feature selection in building two-tier decision trees
13 pages, 2 figures, 4 tables
null
null
null
cs.LG cs.AI
http://creativecommons.org/licenses/by-nc-nd/4.0/
Nowadays, feature selection is frequently used in machine learning when there is a risk of performance degradation due to overfitting or when computational resources are limited. During the feature selection process, the subset of features that are most relevant and least redundant is chosen. In recent years, it has ...
[ { "created": "Thu, 29 Dec 2022 20:10:45 GMT", "version": "v1" } ]
2023-01-02
[ [ "Saltykov", "Sergey A.", "" ] ]
Nowadays, feature selection is frequently used in machine learning when there is a risk of performance degradation due to overfitting or when computational resources are limited. During the feature selection process, the subset of features that are most relevant and least redundant is chosen. In recent years, it has be...
1110.0477
Christian Schulz
Peter Sanders and Christian Schulz
Distributed Evolutionary Graph Partitioning
null
null
null
null
cs.NE cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present a novel distributed evolutionary algorithm, KaFFPaE, to solve the Graph Partitioning Problem, which makes use of KaFFPa (Karlsruhe Fast Flow Partitioner). The use of our multilevel graph partitioner KaFFPa provides new effective crossover and mutation operators. By combining these with a scalable communica...
[ { "created": "Mon, 3 Oct 2011 20:03:46 GMT", "version": "v1" } ]
2011-10-05
[ [ "Sanders", "Peter", "" ], [ "Schulz", "Christian", "" ] ]
We present a novel distributed evolutionary algorithm, KaFFPaE, to solve the Graph Partitioning Problem, which makes use of KaFFPa (Karlsruhe Fast Flow Partitioner). The use of our multilevel graph partitioner KaFFPa provides new effective crossover and mutation operators. By combining these with a scalable communicati...
2106.10893
Yuwei Li
Yuwei Li, Minye Wu, Yuyao Zhang, Lan Xu, Jingyi Yu
PIANO: A Parametric Hand Bone Model from Magnetic Resonance Imaging
Accepted to IJCAI 2021
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Hand modeling is critical for immersive VR/AR, action understanding, or human healthcare. Existing parametric models account only for hand shape, pose, or texture, without modeling the anatomical attributes like bone, which is essential for realistic hand biomechanics analysis. In this paper, we present PIANO, the fi...
[ { "created": "Mon, 21 Jun 2021 07:21:20 GMT", "version": "v1" } ]
2021-06-22
[ [ "Li", "Yuwei", "" ], [ "Wu", "Minye", "" ], [ "Zhang", "Yuyao", "" ], [ "Xu", "Lan", "" ], [ "Yu", "Jingyi", "" ] ]
Hand modeling is critical for immersive VR/AR, action understanding, or human healthcare. Existing parametric models account only for hand shape, pose, or texture, without modeling the anatomical attributes like bone, which is essential for realistic hand biomechanics analysis. In this paper, we present PIANO, the firs...
2302.04373
Huixin Zhan
Huixin Zhan, Kun Zhang, Keyi Lu, Victor S. Sheng
Measuring the Privacy Leakage via Graph Reconstruction Attacks on Simplicial Neural Networks (Student Abstract)
Accepted at AAAI 2023
null
null
null
cs.LG cs.CR
http://creativecommons.org/licenses/by/4.0/
In this paper, we measure the privacy leakage via studying whether graph representations can be inverted to recover the graph used to generate them via graph reconstruction attack (GRA). We propose a GRA that recovers a graph's adjacency matrix from the representations via a graph decoder that minimizes the reconstru...
[ { "created": "Wed, 8 Feb 2023 23:40:24 GMT", "version": "v1" } ]
2023-02-10
[ [ "Zhan", "Huixin", "" ], [ "Zhang", "Kun", "" ], [ "Lu", "Keyi", "" ], [ "Sheng", "Victor S.", "" ] ]
In this paper, we measure the privacy leakage via studying whether graph representations can be inverted to recover the graph used to generate them via graph reconstruction attack (GRA). We propose a GRA that recovers a graph's adjacency matrix from the representations via a graph decoder that minimizes the reconstruct...
2308.12950
Baptiste Roziere
Baptiste Rozi\`ere, Jonas Gehring, Fabian Gloeckle, Sten Sootla, Itai Gat, Xiaoqing Ellen Tan, Yossi Adi, Jingyu Liu, Romain Sauvestre, Tal Remez, J\'er\'emy Rapin, Artyom Kozhevnikov, Ivan Evtimov, Joanna Bitton, Manish Bhatt, Cristian Canton Ferrer, Aaron Grattafiori, Wenhan Xiong, Alexandre D\'efossez, Jade ...
Code Llama: Open Foundation Models for Code
null
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
We release Code Llama, a family of large language models for code based on Llama 2 providing state-of-the-art performance among open models, infilling capabilities, support for large input contexts, and zero-shot instruction following ability for programming tasks. We provide multiple flavors to cover a wide range of...
[ { "created": "Thu, 24 Aug 2023 17:39:13 GMT", "version": "v1" }, { "created": "Fri, 25 Aug 2023 08:51:22 GMT", "version": "v2" }, { "created": "Wed, 31 Jan 2024 19:47:26 GMT", "version": "v3" } ]
2024-02-02
[ [ "Rozière", "Baptiste", "" ], [ "Gehring", "Jonas", "" ], [ "Gloeckle", "Fabian", "" ], [ "Sootla", "Sten", "" ], [ "Gat", "Itai", "" ], [ "Tan", "Xiaoqing Ellen", "" ], [ "Adi", "Yossi", "" ], [ "Li...
We release Code Llama, a family of large language models for code based on Llama 2 providing state-of-the-art performance among open models, infilling capabilities, support for large input contexts, and zero-shot instruction following ability for programming tasks. We provide multiple flavors to cover a wide range of a...
2302.04782
Sheng Yue
Sheng Yue, Guanbo Wang, Wei Shao, Zhaofeng Zhang, Sen Lin, Ju Ren, Junshan Zhang
CLARE: Conservative Model-Based Reward Learning for Offline Inverse Reinforcement Learning
null
null
null
null
cs.LG cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This work aims to tackle a major challenge in offline Inverse Reinforcement Learning (IRL), namely the reward extrapolation error, where the learned reward function may fail to explain the task correctly and misguide the agent in unseen environments due to the intrinsic covariate shift. Leveraging both expert data an...
[ { "created": "Thu, 9 Feb 2023 17:16:29 GMT", "version": "v1" }, { "created": "Tue, 21 Feb 2023 02:39:33 GMT", "version": "v2" } ]
2023-02-22
[ [ "Yue", "Sheng", "" ], [ "Wang", "Guanbo", "" ], [ "Shao", "Wei", "" ], [ "Zhang", "Zhaofeng", "" ], [ "Lin", "Sen", "" ], [ "Ren", "Ju", "" ], [ "Zhang", "Junshan", "" ] ]
This work aims to tackle a major challenge in offline Inverse Reinforcement Learning (IRL), namely the reward extrapolation error, where the learned reward function may fail to explain the task correctly and misguide the agent in unseen environments due to the intrinsic covariate shift. Leveraging both expert data and ...
2407.16729
Huandong Wang
Huandong Wang, Changzheng Gao, Yuchen Wu, Depeng Jin, Lina Yao, Yong Li
PateGail: A Privacy-Preserving Mobility Trajectory Generator with Imitation Learning
null
null
null
null
cs.LG cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Generating human mobility trajectories is of great importance to solve the lack of large-scale trajectory data in numerous applications, which is caused by privacy concerns. However, existing mobility trajectory generation methods still require real-world human trajectories centrally collected as the training data, w...
[ { "created": "Tue, 23 Jul 2024 14:59:23 GMT", "version": "v1" } ]
2024-07-25
[ [ "Wang", "Huandong", "" ], [ "Gao", "Changzheng", "" ], [ "Wu", "Yuchen", "" ], [ "Jin", "Depeng", "" ], [ "Yao", "Lina", "" ], [ "Li", "Yong", "" ] ]
Generating human mobility trajectories is of great importance to solve the lack of large-scale trajectory data in numerous applications, which is caused by privacy concerns. However, existing mobility trajectory generation methods still require real-world human trajectories centrally collected as the training data, whe...
2106.02685
Peilin Zhong
Alessandro Epasto, Mohammad Mahdian, Vahab Mirrokni, Peilin Zhong
Massively Parallel and Dynamic Algorithms for Minimum Size Clustering
null
null
null
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we study the $r$-gather problem, a natural formulation of minimum-size clustering in metric spaces. The goal of $r$-gather is to partition $n$ points into clusters such that each cluster has size at least $r$, and the maximum radius of the clusters is minimized. This additional constraint completely ch...
[ { "created": "Fri, 4 Jun 2021 19:49:43 GMT", "version": "v1" } ]
2021-06-08
[ [ "Epasto", "Alessandro", "" ], [ "Mahdian", "Mohammad", "" ], [ "Mirrokni", "Vahab", "" ], [ "Zhong", "Peilin", "" ] ]
In this paper, we study the $r$-gather problem, a natural formulation of minimum-size clustering in metric spaces. The goal of $r$-gather is to partition $n$ points into clusters such that each cluster has size at least $r$, and the maximum radius of the clusters is minimized. This additional constraint completely chan...
1906.04293
Ryan Kim
Shouvik Musavvir, Anwesha Chatterjee, Ryan Gary Kim, Dae Hyun Kim, Partha Pratim Pande
Inter-Tier Process Variation-Aware Monolithic 3D NoC Architectures
Submitted to IEEE TVLSI (Under Review)
null
null
null
cs.ET cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Monolithic 3D (M3D) technology enables high density integration, performance, and energy-efficiency by sequentially stacking tiers on top of each other. M3D-based network-on-chip (NoC) architectures can exploit these benefits by adopting tier partitioning for intra-router stages. However, conventional fabrication met...
[ { "created": "Mon, 10 Jun 2019 22:01:04 GMT", "version": "v1" } ]
2019-06-12
[ [ "Musavvir", "Shouvik", "" ], [ "Chatterjee", "Anwesha", "" ], [ "Kim", "Ryan Gary", "" ], [ "Kim", "Dae Hyun", "" ], [ "Pande", "Partha Pratim", "" ] ]
Monolithic 3D (M3D) technology enables high density integration, performance, and energy-efficiency by sequentially stacking tiers on top of each other. M3D-based network-on-chip (NoC) architectures can exploit these benefits by adopting tier partitioning for intra-router stages. However, conventional fabrication metho...
2309.05276
Charitha Madapatha Mr.
Sneha Madhusudan, Charitha Madapatha, Behrooz Makki, Hao Guo, Tommy Svensson
Beamforming in Wireless Coded-Caching Systems
Submitted to IEEE Future Networks World Forum, 2023
null
null
null
cs.IT cs.LG cs.NI eess.SP math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Increased capacity in the access network poses capacity challenges on the transport network due to the aggregated traffic. However, there are spatial and time correlation in the user data demands that could potentially be utilized. To that end, we investigate a wireless transport network architecture that integrates ...
[ { "created": "Mon, 11 Sep 2023 07:21:57 GMT", "version": "v1" } ]
2023-09-12
[ [ "Madhusudan", "Sneha", "" ], [ "Madapatha", "Charitha", "" ], [ "Makki", "Behrooz", "" ], [ "Guo", "Hao", "" ], [ "Svensson", "Tommy", "" ] ]
Increased capacity in the access network poses capacity challenges on the transport network due to the aggregated traffic. However, there are spatial and time correlation in the user data demands that could potentially be utilized. To that end, we investigate a wireless transport network architecture that integrates be...
2012.09762
Aleksei Shpilman
Aleksandra Malysheva, Daniel Kudenko, Aleksei Shpilman
MAGNet: Multi-agent Graph Network for Deep Multi-agent Reinforcement Learning
arXiv admin note: substantial text overlap with arXiv:1811.12557
null
10.1109/REDUNDANCY48165.2019.9003345
null
cs.LG
http://creativecommons.org/licenses/by/4.0/
Over recent years, deep reinforcement learning has shown strong successes in complex single-agent tasks, and more recently this approach has also been applied to multi-agent domains. In this paper, we propose a novel approach, called MAGNet, to multi-agent reinforcement learning that utilizes a relevance graph repres...
[ { "created": "Thu, 17 Dec 2020 17:19:36 GMT", "version": "v1" } ]
2020-12-18
[ [ "Malysheva", "Aleksandra", "" ], [ "Kudenko", "Daniel", "" ], [ "Shpilman", "Aleksei", "" ] ]
Over recent years, deep reinforcement learning has shown strong successes in complex single-agent tasks, and more recently this approach has also been applied to multi-agent domains. In this paper, we propose a novel approach, called MAGNet, to multi-agent reinforcement learning that utilizes a relevance graph represen...
1808.02084
Zaiwei Zhang
Zaiwei Zhang, Zhenpei Yang, Chongyang Ma, Linjie Luo, Alexander Huth, Etienne Vouga, Qixing Huang
Deep Generative Modeling for Scene Synthesis via Hybrid Representations
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present a deep generative scene modeling technique for indoor environments. Our goal is to train a generative model using a feed-forward neural network that maps a prior distribution (e.g., a normal distribution) to the distribution of primary objects in indoor scenes. We introduce a 3D object arrangement represen...
[ { "created": "Mon, 6 Aug 2018 19:42:24 GMT", "version": "v1" } ]
2018-08-08
[ [ "Zhang", "Zaiwei", "" ], [ "Yang", "Zhenpei", "" ], [ "Ma", "Chongyang", "" ], [ "Luo", "Linjie", "" ], [ "Huth", "Alexander", "" ], [ "Vouga", "Etienne", "" ], [ "Huang", "Qixing", "" ] ]
We present a deep generative scene modeling technique for indoor environments. Our goal is to train a generative model using a feed-forward neural network that maps a prior distribution (e.g., a normal distribution) to the distribution of primary objects in indoor scenes. We introduce a 3D object arrangement representa...
2210.08481
Peggy Tang
Peggy Tang, Kun Hu, Lei Zhang, Jiebo Luo, Zhiyong Wang
TLDW: Extreme Multimodal Summarisation of News Videos
null
null
null
null
cs.CV cs.CL cs.MM
http://creativecommons.org/licenses/by/4.0/
Multimodal summarisation with multimodal output is drawing increasing attention due to the rapid growth of multimedia data. While several methods have been proposed to summarise visual-text contents, their multimodal outputs are not succinct enough at an extreme level to address the information overload issue. To the...
[ { "created": "Sun, 16 Oct 2022 08:19:59 GMT", "version": "v1" } ]
2022-10-18
[ [ "Tang", "Peggy", "" ], [ "Hu", "Kun", "" ], [ "Zhang", "Lei", "" ], [ "Luo", "Jiebo", "" ], [ "Wang", "Zhiyong", "" ] ]
Multimodal summarisation with multimodal output is drawing increasing attention due to the rapid growth of multimedia data. While several methods have been proposed to summarise visual-text contents, their multimodal outputs are not succinct enough at an extreme level to address the information overload issue. To the e...
2201.09284
Pablo Dorta-Gonzalez
Pablo Dorta-Gonz\'alez and Mar\'ia Isabel Dorta-Gonz\'alez
Contribution of the Open Access modality to the impact of hybrid journals controlling by field and time effects
28 pages, 5 figures, 7 tables
null
null
null
cs.DL
http://creativecommons.org/licenses/by/4.0/
Researchers are more likely to read and cite papers to which they have access than those that they cannot obtain. Thus, the objective of this work is to analyze the contribution of the Open Access (OA) modality to the impact of hybrid journals. For this, the research articles in the year 2017 from 200 hybrid journals...
[ { "created": "Sun, 23 Jan 2022 14:57:35 GMT", "version": "v1" } ]
2022-01-25
[ [ "Dorta-González", "Pablo", "" ], [ "Dorta-González", "María Isabel", "" ] ]
Researchers are more likely to read and cite papers to which they have access than those that they cannot obtain. Thus, the objective of this work is to analyze the contribution of the Open Access (OA) modality to the impact of hybrid journals. For this, the research articles in the year 2017 from 200 hybrid journals i...
cs/0405012
Ajith Abraham
Ajith Abraham & Dan Steinberg
Is Neural Network a Reliable Forecaster on Earth? A MARS Query!
null
Bio-Inspired Applications of Connectionism, Lecture Notes in Computer Science. Volume. 2085, Springer Verlag Germany, Jose Mira and Alberto Prieto (Eds.), ISBN 3540422374, Spain, pp.679-686, 2001
null
null
cs.AI
null
Long-term rainfall prediction is a challenging task especially in the modern world where we are facing the major environmental problem of global warming. In general, climate and rainfall are highly non-linear phenomena in nature exhibiting what is known as the butterfly effect. While some regions of the world are not...
[ { "created": "Wed, 5 May 2004 00:36:17 GMT", "version": "v1" } ]
2007-05-23
[ [ "Abraham", "Ajith", "" ], [ "Steinberg", "Dan", "" ] ]
Long-term rainfall prediction is a challenging task especially in the modern world where we are facing the major environmental problem of global warming. In general, climate and rainfall are highly non-linear phenomena in nature exhibiting what is known as the butterfly effect. While some regions of the world are notic...
2404.00230
Zheling Meng
Zheling Meng, Bo Peng, Jing Dong
Latent Watermark: Inject and Detect Watermarks in Latent Diffusion Space
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Watermarking is a tool for actively identifying and attributing the images generated by latent diffusion models. Existing methods face the dilemma of image quality and watermark robustness. Watermarks with superior image quality usually have inferior robustness against attacks such as blurring and JPEG compression, w...
[ { "created": "Sat, 30 Mar 2024 03:19:50 GMT", "version": "v1" }, { "created": "Fri, 12 Jul 2024 01:41:44 GMT", "version": "v2" } ]
2024-07-15
[ [ "Meng", "Zheling", "" ], [ "Peng", "Bo", "" ], [ "Dong", "Jing", "" ] ]
Watermarking is a tool for actively identifying and attributing the images generated by latent diffusion models. Existing methods face the dilemma of image quality and watermark robustness. Watermarks with superior image quality usually have inferior robustness against attacks such as blurring and JPEG compression, whi...
2103.00452
Yanlong Huang
Yanlong Huang
EKMP: Generalized Imitation Learning with Adaptation, Nonlinear Hard Constraints and Obstacle Avoidance
8 pages
null
null
null
cs.RO
http://creativecommons.org/licenses/by/4.0/
As a user-friendly and straightforward solution for robot trajectory generation, imitation learning has been viewed as a vital direction in the context of robot skill learning. In contrast to unconstrained imitation learning which ignores possible internal and external constraints arising from environments and robot ...
[ { "created": "Sun, 28 Feb 2021 11:06:55 GMT", "version": "v1" }, { "created": "Fri, 12 Mar 2021 15:57:04 GMT", "version": "v2" } ]
2021-03-15
[ [ "Huang", "Yanlong", "" ] ]
As a user-friendly and straightforward solution for robot trajectory generation, imitation learning has been viewed as a vital direction in the context of robot skill learning. In contrast to unconstrained imitation learning which ignores possible internal and external constraints arising from environments and robot ki...