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
2110.04667
Shivam Bajaj
Shivam Bajaj, Eric Torng, Shaunak D. Bopardikar, Alexander Von Moll, Isaac Weintraub, Eloy Garcia, David W. Casbeer
Competitive Perimeter Defense of Conical Environments
Version 2 has additional images
null
null
null
cs.DS cs.SY eess.SY
http://creativecommons.org/licenses/by/4.0/
We consider a perimeter defense problem in a planar conical environment in which a single vehicle, having a finite capture radius, aims to defend a concentric perimeter from mobile intruders. The intruders are arbitrarily released at the circumference of the environment and they move radially toward the perimeter wit...
[ { "created": "Sun, 10 Oct 2021 00:19:46 GMT", "version": "v1" }, { "created": "Wed, 30 Mar 2022 03:55:25 GMT", "version": "v2" } ]
2022-03-31
[ [ "Bajaj", "Shivam", "" ], [ "Torng", "Eric", "" ], [ "Bopardikar", "Shaunak D.", "" ], [ "Von Moll", "Alexander", "" ], [ "Weintraub", "Isaac", "" ], [ "Garcia", "Eloy", "" ], [ "Casbeer", "David W.", "" ]...
We consider a perimeter defense problem in a planar conical environment in which a single vehicle, having a finite capture radius, aims to defend a concentric perimeter from mobile intruders. The intruders are arbitrarily released at the circumference of the environment and they move radially toward the perimeter with ...
2311.12345
Yanan Jian
Yanan Jian, Fuxun Yu, Simranjit Singh, Dimitrios Stamoulis
Stable Diffusion For Aerial Object Detection
Accepted at NeurIPS 2023 Synthetic Data Generation with Generative AI workshop
null
null
null
cs.CV cs.AI cs.LG
http://creativecommons.org/licenses/by/4.0/
Aerial object detection is a challenging task, in which one major obstacle lies in the limitations of large-scale data collection and the long-tail distribution of certain classes. Synthetic data offers a promising solution, especially with recent advances in diffusion-based methods like stable diffusion (SD). Howeve...
[ { "created": "Tue, 21 Nov 2023 04:38:21 GMT", "version": "v1" } ]
2023-11-22
[ [ "Jian", "Yanan", "" ], [ "Yu", "Fuxun", "" ], [ "Singh", "Simranjit", "" ], [ "Stamoulis", "Dimitrios", "" ] ]
Aerial object detection is a challenging task, in which one major obstacle lies in the limitations of large-scale data collection and the long-tail distribution of certain classes. Synthetic data offers a promising solution, especially with recent advances in diffusion-based methods like stable diffusion (SD). However,...
2105.01899
Tsung Wei Tsai
Tsung Wei Tsai, Chongxuan Li, Jun Zhu
MiCE: Mixture of Contrastive Experts for Unsupervised Image Clustering
International Conference on Learning Representations (ICLR) 2021
null
null
null
cs.LG cs.CV
http://creativecommons.org/licenses/by/4.0/
We present Mixture of Contrastive Experts (MiCE), a unified probabilistic clustering framework that simultaneously exploits the discriminative representations learned by contrastive learning and the semantic structures captured by a latent mixture model. Motivated by the mixture of experts, MiCE employs a gating func...
[ { "created": "Wed, 5 May 2021 07:17:57 GMT", "version": "v1" } ]
2021-05-06
[ [ "Tsai", "Tsung Wei", "" ], [ "Li", "Chongxuan", "" ], [ "Zhu", "Jun", "" ] ]
We present Mixture of Contrastive Experts (MiCE), a unified probabilistic clustering framework that simultaneously exploits the discriminative representations learned by contrastive learning and the semantic structures captured by a latent mixture model. Motivated by the mixture of experts, MiCE employs a gating functi...
1805.05758
Thomas Wolf
Thomas Wolf, Julien Chaumond, Clement Delangue
Continuous Learning in a Hierarchical Multiscale Neural Network
5 pages, 2 figures, accepted as short paper at ACL 2018
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We reformulate the problem of encoding a multi-scale representation of a sequence in a language model by casting it in a continuous learning framework. We propose a hierarchical multi-scale language model in which short time-scale dependencies are encoded in the hidden state of a lower-level recurrent neural network ...
[ { "created": "Tue, 15 May 2018 13:37:33 GMT", "version": "v1" } ]
2018-05-16
[ [ "Wolf", "Thomas", "" ], [ "Chaumond", "Julien", "" ], [ "Delangue", "Clement", "" ] ]
We reformulate the problem of encoding a multi-scale representation of a sequence in a language model by casting it in a continuous learning framework. We propose a hierarchical multi-scale language model in which short time-scale dependencies are encoded in the hidden state of a lower-level recurrent neural network wh...
2312.06202
Yitong Wang
Yitong Wang, Chang Liu, Jun Zhao
Transforms for Multiplicative and Fractional Programming with Broad Applications in Edge Computing and Communication Networks
null
null
null
null
cs.CC cs.DM cs.NA cs.PF math.NA
http://creativecommons.org/licenses/by/4.0/
Multiplicative Programming (MP) pertains to a spectrum of optimization problems that involve product term(s). As computational paradigms of communication systems continue to evolve, particularly concerning the offloading strategies of computationally intensive tasks simultaneously to centralized or decentralized serv...
[ { "created": "Mon, 11 Dec 2023 08:36:17 GMT", "version": "v1" } ]
2023-12-12
[ [ "Wang", "Yitong", "" ], [ "Liu", "Chang", "" ], [ "Zhao", "Jun", "" ] ]
Multiplicative Programming (MP) pertains to a spectrum of optimization problems that involve product term(s). As computational paradigms of communication systems continue to evolve, particularly concerning the offloading strategies of computationally intensive tasks simultaneously to centralized or decentralized server...
1302.5848
Kalyana Babu Nakshatrala
D. Z. Turner, K. B. Nakshatrala, and M. J. Martinez
A framework for coupling flow and deformation of the porous solid
null
null
null
null
cs.NA math.NA physics.flu-dyn
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we consider the flow of an incompressible fluid in a deformable porous solid. We present a mathematical model using the framework offered by the theory of interacting continua. In its most general form, this framework provides a mechanism for capturing multiphase flow, deformation, chemical reactions a...
[ { "created": "Sat, 23 Feb 2013 22:03:45 GMT", "version": "v1" }, { "created": "Tue, 26 Feb 2013 05:16:27 GMT", "version": "v2" } ]
2013-02-27
[ [ "Turner", "D. Z.", "" ], [ "Nakshatrala", "K. B.", "" ], [ "Martinez", "M. J.", "" ] ]
In this paper, we consider the flow of an incompressible fluid in a deformable porous solid. We present a mathematical model using the framework offered by the theory of interacting continua. In its most general form, this framework provides a mechanism for capturing multiphase flow, deformation, chemical reactions and...
2005.05465
Tom Kr\"uger
Tom Kr\"uger, Wolfgang Mauerer
Quantum Annealing-Based Software Components: An Experimental Case Study with SAT Solving
null
null
10.1145/3387940.3391472
null
cs.ET quant-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Quantum computers have the potential of solving problems more efficiently than classical computers. While first commercial prototypes have become available, the performance of such machines in practical application is still subject to exploration. Quantum computers will not entirely replace classical machines, but se...
[ { "created": "Mon, 11 May 2020 22:20:17 GMT", "version": "v1" } ]
2020-05-13
[ [ "Krüger", "Tom", "" ], [ "Mauerer", "Wolfgang", "" ] ]
Quantum computers have the potential of solving problems more efficiently than classical computers. While first commercial prototypes have become available, the performance of such machines in practical application is still subject to exploration. Quantum computers will not entirely replace classical machines, but serv...
2202.06297
Alexey Ovchinnikov
Mariya Bessonov, Ilia Ilmer, Tatiana Konstantinova, Alexey Ovchinnikov, Gleb Pogudin, Pedro Soto
Faster Gr\"obner bases for Lie derivatives of ODE systems via monomial orderings
null
null
10.1145/3666000.3669695
null
cs.SC cs.MS q-bio.QM
http://creativecommons.org/licenses/by-nc-sa/4.0/
Symbolic computation for systems of differential equations is often computationally expensive. Many practical differential models have a form of polynomial or rational ODE system with specified outputs. A basic symbolic approach to analyze these models is to compute and then symbolically process the polynomial system...
[ { "created": "Sun, 13 Feb 2022 12:40:11 GMT", "version": "v1" }, { "created": "Thu, 2 Feb 2023 17:01:39 GMT", "version": "v2" }, { "created": "Thu, 6 Jun 2024 21:18:53 GMT", "version": "v3" } ]
2024-06-10
[ [ "Bessonov", "Mariya", "" ], [ "Ilmer", "Ilia", "" ], [ "Konstantinova", "Tatiana", "" ], [ "Ovchinnikov", "Alexey", "" ], [ "Pogudin", "Gleb", "" ], [ "Soto", "Pedro", "" ] ]
Symbolic computation for systems of differential equations is often computationally expensive. Many practical differential models have a form of polynomial or rational ODE system with specified outputs. A basic symbolic approach to analyze these models is to compute and then symbolically process the polynomial system o...
1611.06468
Rui Liu
Rui Liu, Xiaoli Zhang
Generating machine-executable plans from end-user's natural-language instructions
16 pages, 10 figures, article submitted to Robotics and Computer-Integrated Manufacturing, 2016 Aug
null
null
null
cs.AI cs.CL cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
It is critical for advanced manufacturing machines to autonomously execute a task by following an end-user's natural language (NL) instructions. However, NL instructions are usually ambiguous and abstract so that the machines may misunderstand and incorrectly execute the task. To address this NL-based human-machine c...
[ { "created": "Sun, 20 Nov 2016 04:06:47 GMT", "version": "v1" } ]
2016-11-22
[ [ "Liu", "Rui", "" ], [ "Zhang", "Xiaoli", "" ] ]
It is critical for advanced manufacturing machines to autonomously execute a task by following an end-user's natural language (NL) instructions. However, NL instructions are usually ambiguous and abstract so that the machines may misunderstand and incorrectly execute the task. To address this NL-based human-machine com...
1801.02358
Priyanka Mukhopadhyay Ms
Divesh Aggarwal, Priyanka Mukhopadhyay
Improved algorithms for the Shortest Vector Problem and the Closest Vector Problem in the infinity norm
Changed the title
null
null
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Blomer and Naewe[BN09] modified the randomized sieving algorithm of Ajtai, Kumar and Sivakumar[AKS01] to solve the shortest vector problem (SVP). The algorithm starts with $N = 2^{O(n)}$ randomly chosen vectors in the lattice and employs a sieving procedure to iteratively obtain shorter vectors in the lattice. The ru...
[ { "created": "Mon, 8 Jan 2018 09:43:43 GMT", "version": "v1" }, { "created": "Tue, 15 May 2018 17:04:41 GMT", "version": "v2" } ]
2018-05-16
[ [ "Aggarwal", "Divesh", "" ], [ "Mukhopadhyay", "Priyanka", "" ] ]
Blomer and Naewe[BN09] modified the randomized sieving algorithm of Ajtai, Kumar and Sivakumar[AKS01] to solve the shortest vector problem (SVP). The algorithm starts with $N = 2^{O(n)}$ randomly chosen vectors in the lattice and employs a sieving procedure to iteratively obtain shorter vectors in the lattice. The runn...
2009.11180
Lance Eliot
Lance Eliot
AI and Legal Argumentation: Aligning the Autonomous Levels of AI Legal Reasoning
26 pages, 9 figures. arXiv admin note: text overlap with arXiv:2009.02243
null
null
null
cs.CY cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Legal argumentation is a vital cornerstone of justice, underpinning an adversarial form of law, and extensive research has attempted to augment or undertake legal argumentation via the use of computer-based automation including Artificial Intelligence (AI). AI advances in Natural Language Processing (NLP) and Machine...
[ { "created": "Fri, 11 Sep 2020 22:05:40 GMT", "version": "v1" } ]
2020-09-24
[ [ "Eliot", "Lance", "" ] ]
Legal argumentation is a vital cornerstone of justice, underpinning an adversarial form of law, and extensive research has attempted to augment or undertake legal argumentation via the use of computer-based automation including Artificial Intelligence (AI). AI advances in Natural Language Processing (NLP) and Machine L...
2312.08888
Kyra Ahrens
Kyra Ahrens, Hans Hergen Lehmann, Jae Hee Lee, Stefan Wermter
Read Between the Layers: Leveraging Multi-Layer Representations for Rehearsal-Free Continual Learning with Pre-Trained Models
Accepted for publication in Transactions of Machine Learning Research (TMLR) journal
null
null
null
cs.LG cs.CV
http://creativecommons.org/licenses/by/4.0/
We address the Continual Learning (CL) problem, wherein a model must learn a sequence of tasks from non-stationary distributions while preserving prior knowledge upon encountering new experiences. With the advancement of foundation models, CL research has pivoted from the initial learning-from-scratch paradigm toward...
[ { "created": "Wed, 13 Dec 2023 13:11:44 GMT", "version": "v1" }, { "created": "Wed, 17 Apr 2024 19:32:47 GMT", "version": "v2" }, { "created": "Fri, 5 Jul 2024 09:43:41 GMT", "version": "v3" } ]
2024-07-08
[ [ "Ahrens", "Kyra", "" ], [ "Lehmann", "Hans Hergen", "" ], [ "Lee", "Jae Hee", "" ], [ "Wermter", "Stefan", "" ] ]
We address the Continual Learning (CL) problem, wherein a model must learn a sequence of tasks from non-stationary distributions while preserving prior knowledge upon encountering new experiences. With the advancement of foundation models, CL research has pivoted from the initial learning-from-scratch paradigm towards ...
1911.07875
Sandhya Tripathi
Aditya Petety, Sandhya Tripathi, N Hemachandra
Attribute noise robust binary classification
Accepted for Student Abstract presentation at AAAI2020
null
null
null
cs.LG stat.ML
http://creativecommons.org/licenses/by/4.0/
We consider the problem of learning linear classifiers when both features and labels are binary. In addition, the features are noisy, i.e., they could be flipped with an unknown probability. In Sy-De attribute noise model, where all features could be noisy together with same probability, we show that $0$-$1$ loss ($l...
[ { "created": "Mon, 18 Nov 2019 19:03:02 GMT", "version": "v1" } ]
2019-11-20
[ [ "Petety", "Aditya", "" ], [ "Tripathi", "Sandhya", "" ], [ "Hemachandra", "N", "" ] ]
We consider the problem of learning linear classifiers when both features and labels are binary. In addition, the features are noisy, i.e., they could be flipped with an unknown probability. In Sy-De attribute noise model, where all features could be noisy together with same probability, we show that $0$-$1$ loss ($l_{...
2404.12821
Geoffrey Goodell
William Macpherson and Geoffrey Goodell
Benchmarking the performance of a self-custody, non-ledger-based, obliviously managed digital payment system
23 pages, 10 figures
null
null
null
cs.CY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
As global governments intensify efforts to operationalize retail central bank digital currencies (CBDCs), the imperative for architectures that preserve user privacy has never been more pronounced. This paper advances an existing retail CBDC framework developed at University College London. Utilizing the capabilities...
[ { "created": "Fri, 19 Apr 2024 11:57:32 GMT", "version": "v1" } ]
2024-04-22
[ [ "Macpherson", "William", "" ], [ "Goodell", "Geoffrey", "" ] ]
As global governments intensify efforts to operationalize retail central bank digital currencies (CBDCs), the imperative for architectures that preserve user privacy has never been more pronounced. This paper advances an existing retail CBDC framework developed at University College London. Utilizing the capabilities o...
1707.08273
Noseong Park
Noseong Park, Ankesh Anand, Joel Ruben Antony Moniz, Kookjin Lee, Tanmoy Chakraborty, Jaegul Choo, Hongkyu Park, Youngmin Kim
MMGAN: Manifold Matching Generative Adversarial Network
the 24th International Conference on Pattern Recognition (ICPR), 2018
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
It is well-known that GANs are difficult to train, and several different techniques have been proposed in order to stabilize their training. In this paper, we propose a novel training method called manifold-matching, and a new GAN model called manifold-matching GAN (MMGAN). MMGAN finds two manifolds representing the ...
[ { "created": "Wed, 26 Jul 2017 02:09:34 GMT", "version": "v1" }, { "created": "Sun, 30 Jul 2017 06:29:16 GMT", "version": "v2" }, { "created": "Thu, 21 Sep 2017 18:31:19 GMT", "version": "v3" }, { "created": "Thu, 12 Apr 2018 06:46:15 GMT", "version": "v4" } ]
2018-04-13
[ [ "Park", "Noseong", "" ], [ "Anand", "Ankesh", "" ], [ "Moniz", "Joel Ruben Antony", "" ], [ "Lee", "Kookjin", "" ], [ "Chakraborty", "Tanmoy", "" ], [ "Choo", "Jaegul", "" ], [ "Park", "Hongkyu", "" ], ...
It is well-known that GANs are difficult to train, and several different techniques have been proposed in order to stabilize their training. In this paper, we propose a novel training method called manifold-matching, and a new GAN model called manifold-matching GAN (MMGAN). MMGAN finds two manifolds representing the ve...
1811.06871
Sandor Kisfaludi-Bak
S\'andor Kisfaludi-Bak, Jesper Nederlof and Erik Jan van Leeuwen
Nearly ETH-Tight Algorithms for Planar Steiner Tree with Terminals on Few Faces
32 pages, 8 figures, accepted at SODA 2019
null
null
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The Planar Steiner Tree problem is one of the most fundamental NP-complete problems as it models many network design problems. Recall that an instance of this problem consists of a graph with edge weights, and a subset of vertices (often called terminals); the goal is to find a subtree of the graph of minimum total w...
[ { "created": "Fri, 16 Nov 2018 15:47:38 GMT", "version": "v1" } ]
2018-11-19
[ [ "Kisfaludi-Bak", "Sándor", "" ], [ "Nederlof", "Jesper", "" ], [ "van Leeuwen", "Erik Jan", "" ] ]
The Planar Steiner Tree problem is one of the most fundamental NP-complete problems as it models many network design problems. Recall that an instance of this problem consists of a graph with edge weights, and a subset of vertices (often called terminals); the goal is to find a subtree of the graph of minimum total wei...
2003.02638
Marcus Ebner Von Eschenbach
Marcus Ebner von Eschenbach, Binyamin Manela, Jan Peters, Armin Biess
Metric-Based Imitation Learning Between Two Dissimilar Anthropomorphic Robotic Arms
8 pages, 5 figures, submitted to IEEE Robotics and Automation Letters/IROS 2020
null
null
null
cs.RO cs.LG stat.ML
http://creativecommons.org/licenses/by/4.0/
The development of autonomous robotic systems that can learn from human demonstrations to imitate a desired behavior - rather than being manually programmed - has huge technological potential. One major challenge in imitation learning is the correspondence problem: how to establish corresponding states and actions be...
[ { "created": "Tue, 25 Feb 2020 19:47:19 GMT", "version": "v1" } ]
2020-03-06
[ [ "von Eschenbach", "Marcus Ebner", "" ], [ "Manela", "Binyamin", "" ], [ "Peters", "Jan", "" ], [ "Biess", "Armin", "" ] ]
The development of autonomous robotic systems that can learn from human demonstrations to imitate a desired behavior - rather than being manually programmed - has huge technological potential. One major challenge in imitation learning is the correspondence problem: how to establish corresponding states and actions betw...
0909.2455
Grenville Croll
Andrew McGeady, Joseph McGouran
End User Computing in AIB Capital Markets: A Management Summary
7 Pages. Referenced & submitted by GJC in Sept 2009
Proc. European Spreadsheet Risks Int. Grp. (EuSpRIG) 2008 25-31 ISBN 978-905617-69-2
null
null
cs.HC cs.CY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper is a management summary of how the area of End User Computing (EUC) has been addressed by AIB Capital Markets. The development of an effective policy is described, as well as the process by which a register of critical EUC applications was assembled and how those applications were brought into a controlled...
[ { "created": "Sun, 13 Sep 2009 23:51:59 GMT", "version": "v1" } ]
2009-09-15
[ [ "McGeady", "Andrew", "" ], [ "McGouran", "Joseph", "" ] ]
This paper is a management summary of how the area of End User Computing (EUC) has been addressed by AIB Capital Markets. The development of an effective policy is described, as well as the process by which a register of critical EUC applications was assembled and how those applications were brought into a controlled e...
2208.10552
Yahav Avigal
Yahav Avigal, Lars Berscheid, Tamim Asfour, Torsten Kr\"oger, Ken Goldberg
SpeedFolding: Learning Efficient Bimanual Folding of Garments
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2022
null
null
null
cs.RO cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Folding garments reliably and efficiently is a long standing challenge in robotic manipulation due to the complex dynamics and high dimensional configuration space of garments. An intuitive approach is to initially manipulate the garment to a canonical smooth configuration before folding. In this work, we develop Spe...
[ { "created": "Mon, 22 Aug 2022 19:01:31 GMT", "version": "v1" }, { "created": "Fri, 9 Sep 2022 18:04:21 GMT", "version": "v2" } ]
2022-09-13
[ [ "Avigal", "Yahav", "" ], [ "Berscheid", "Lars", "" ], [ "Asfour", "Tamim", "" ], [ "Kröger", "Torsten", "" ], [ "Goldberg", "Ken", "" ] ]
Folding garments reliably and efficiently is a long standing challenge in robotic manipulation due to the complex dynamics and high dimensional configuration space of garments. An intuitive approach is to initially manipulate the garment to a canonical smooth configuration before folding. In this work, we develop Speed...
1904.05754
Ping-En Lu
Yu-Hsien Peng, Ping-En Lu, Cheng-Shang Chang and Duan-Shin Lee
Percolation Threshold for Competitive Influence in Random Networks
11 pages, 9 figures, this article is the complete version (with proofs) of the IEEE Global Communications Conference 2019 review paper
in IEEE Transactions on Computational Social Systems, vol. 7, no. 4, pp. 991-1003, Aug. 2020
10.1109/TCSS.2020.2995740
null
cs.SI physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we propose a new averaging model for modeling the competitive influence of $K$ candidates among $n$ voters in an election process. For such an influence propagation model, we address the question of how many seeded voters a candidate needs to place among undecided voters in order to win an election. We...
[ { "created": "Thu, 11 Apr 2019 15:13:15 GMT", "version": "v1" }, { "created": "Sun, 14 Apr 2019 12:31:25 GMT", "version": "v2" }, { "created": "Sun, 21 Apr 2019 13:04:44 GMT", "version": "v3" } ]
2020-09-22
[ [ "Peng", "Yu-Hsien", "" ], [ "Lu", "Ping-En", "" ], [ "Chang", "Cheng-Shang", "" ], [ "Lee", "Duan-Shin", "" ] ]
In this paper, we propose a new averaging model for modeling the competitive influence of $K$ candidates among $n$ voters in an election process. For such an influence propagation model, we address the question of how many seeded voters a candidate needs to place among undecided voters in order to win an election. We s...
2104.00179
Chunhui Liu
Chunhui Liu, Xinyu Li, Hao Chen, Davide Modolo, Joseph Tighe
Selective Feature Compression for Efficient Activity Recognition Inference
Accepted by ICCV 2021
null
null
null
cs.CV
http://creativecommons.org/licenses/by-nc-sa/4.0/
Most action recognition solutions rely on dense sampling to precisely cover the informative temporal clip. Extensively searching temporal region is expensive for a real-world application. In this work, we focus on improving the inference efficiency of current action recognition backbones on trimmed videos, and illust...
[ { "created": "Thu, 1 Apr 2021 00:54:51 GMT", "version": "v1" }, { "created": "Thu, 29 Jul 2021 10:59:15 GMT", "version": "v2" } ]
2021-07-30
[ [ "Liu", "Chunhui", "" ], [ "Li", "Xinyu", "" ], [ "Chen", "Hao", "" ], [ "Modolo", "Davide", "" ], [ "Tighe", "Joseph", "" ] ]
Most action recognition solutions rely on dense sampling to precisely cover the informative temporal clip. Extensively searching temporal region is expensive for a real-world application. In this work, we focus on improving the inference efficiency of current action recognition backbones on trimmed videos, and illustra...
1705.01501
Shankara Narayanan Krishna
Shankara Narayanan Krishna, Khushraj Madnani, P. K. Pandya
Making Metric Temporal Logic Rational
null
null
null
null
cs.LO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We study an extension of $\mtl$ in pointwise time with rational expression guarded modality $\reg_I(\re)$ where $\re$ is a rational expression over subformulae. We study the decidability and expressiveness of this extension ($\mtl$+$\varphi \ureg_{I, \re} \varphi$+$\reg_{I,\re}\varphi$), called $\regmtl$, as well as ...
[ { "created": "Sat, 29 Apr 2017 18:08:50 GMT", "version": "v1" } ]
2017-05-04
[ [ "Krishna", "Shankara Narayanan", "" ], [ "Madnani", "Khushraj", "" ], [ "Pandya", "P. K.", "" ] ]
We study an extension of $\mtl$ in pointwise time with rational expression guarded modality $\reg_I(\re)$ where $\re$ is a rational expression over subformulae. We study the decidability and expressiveness of this extension ($\mtl$+$\varphi \ureg_{I, \re} \varphi$+$\reg_{I,\re}\varphi$), called $\regmtl$, as well as it...
2305.15431
Zimu Wang
Zimu Wang, Jiashuo Liu, Hao Zou, Xingxuan Zhang, Yue He, Dongxu Liang, Peng Cui
Exploring and Exploiting Data Heterogeneity in Recommendation
14 pages, 14 figures
null
null
null
cs.IR cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Massive amounts of data are the foundation of data-driven recommendation models. As an inherent nature of big data, data heterogeneity widely exists in real-world recommendation systems. It reflects the differences in the properties among sub-populations. Ignoring the heterogeneity in recommendation data could limit ...
[ { "created": "Sun, 21 May 2023 11:01:14 GMT", "version": "v1" } ]
2023-05-26
[ [ "Wang", "Zimu", "" ], [ "Liu", "Jiashuo", "" ], [ "Zou", "Hao", "" ], [ "Zhang", "Xingxuan", "" ], [ "He", "Yue", "" ], [ "Liang", "Dongxu", "" ], [ "Cui", "Peng", "" ] ]
Massive amounts of data are the foundation of data-driven recommendation models. As an inherent nature of big data, data heterogeneity widely exists in real-world recommendation systems. It reflects the differences in the properties among sub-populations. Ignoring the heterogeneity in recommendation data could limit th...
1911.11357
Samaneh Azadi
Samaneh Azadi, Michael Tschannen, Eric Tzeng, Sylvain Gelly, Trevor Darrell, Mario Lucic
Semantic Bottleneck Scene Generation
null
null
null
null
cs.LG cs.CV stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Coupling the high-fidelity generation capabilities of label-conditional image synthesis methods with the flexibility of unconditional generative models, we propose a semantic bottleneck GAN model for unconditional synthesis of complex scenes. We assume pixel-wise segmentation labels are available during training and ...
[ { "created": "Tue, 26 Nov 2019 06:01:09 GMT", "version": "v1" } ]
2019-11-27
[ [ "Azadi", "Samaneh", "" ], [ "Tschannen", "Michael", "" ], [ "Tzeng", "Eric", "" ], [ "Gelly", "Sylvain", "" ], [ "Darrell", "Trevor", "" ], [ "Lucic", "Mario", "" ] ]
Coupling the high-fidelity generation capabilities of label-conditional image synthesis methods with the flexibility of unconditional generative models, we propose a semantic bottleneck GAN model for unconditional synthesis of complex scenes. We assume pixel-wise segmentation labels are available during training and us...
1906.04964
Martianus Frederic Ezerman
Martianus Frederic Ezerman, San Ling, Buket \"Ozkaya, and Patrick Sol\'e
Good Stabilizer Codes from Quasi-Cyclic Codes over $\mathbb{F}_4$ and $\mathbb{F}_9$
Accepted ISIT 2019
null
10.1109/ISIT.2019.8849416
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We apply quantum Construction X on quasi-cyclic codes with large Hermitian hulls over $\mathbb{F}_4$ and $\mathbb{F}_9$ to derive good qubit and qutrit stabilizer codes, respectively. In several occasions we obtain quantum codes with stricly improved parameters than the current record. In numerous other occasions we ...
[ { "created": "Wed, 12 Jun 2019 06:45:51 GMT", "version": "v1" } ]
2020-04-28
[ [ "Ezerman", "Martianus Frederic", "" ], [ "Ling", "San", "" ], [ "Özkaya", "Buket", "" ], [ "Solé", "Patrick", "" ] ]
We apply quantum Construction X on quasi-cyclic codes with large Hermitian hulls over $\mathbb{F}_4$ and $\mathbb{F}_9$ to derive good qubit and qutrit stabilizer codes, respectively. In several occasions we obtain quantum codes with stricly improved parameters than the current record. In numerous other occasions we ob...
2111.07129
Ajoy Mondal Dr.
Sachin Raja, Ajoy Mondal, and C V Jawahar
Visual Understanding of Complex Table Structures from Document Images
null
null
null
null
cs.CV cs.AI
http://creativecommons.org/licenses/by/4.0/
Table structure recognition is necessary for a comprehensive understanding of documents. Tables in unstructured business documents are tough to parse due to the high diversity of layouts, varying alignments of contents, and the presence of empty cells. The problem is particularly difficult because of challenges in id...
[ { "created": "Sat, 13 Nov 2021 14:54:33 GMT", "version": "v1" } ]
2021-11-16
[ [ "Raja", "Sachin", "" ], [ "Mondal", "Ajoy", "" ], [ "Jawahar", "C V", "" ] ]
Table structure recognition is necessary for a comprehensive understanding of documents. Tables in unstructured business documents are tough to parse due to the high diversity of layouts, varying alignments of contents, and the presence of empty cells. The problem is particularly difficult because of challenges in iden...
1302.2875
Frank Kschischang
Mansoor I. Yousefi and Frank R. Kschischang
Information Transmission using the Nonlinear Fourier Transform, Part III: Spectrum Modulation
Updated version of IEEE Transactions on Information Theory, vol. 60, no. 7, pp. 4346--4369, July, 2014
IEEE Transactions on Information Theory, vol. 60, no. 7, pp. 4346--4369, July, 2014
10.1109/TIT.2014.2321155
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Motivated by the looming "capacity crunch" in fiber-optic networks, information transmission over such systems is revisited. Among numerous distortions, inter-channel interference in multiuser wavelength-division multiplexing (WDM) is identified as the seemingly intractable factor limiting the achievable rate at high...
[ { "created": "Tue, 12 Feb 2013 17:52:11 GMT", "version": "v1" }, { "created": "Tue, 7 Oct 2014 21:29:50 GMT", "version": "v2" } ]
2014-10-09
[ [ "Yousefi", "Mansoor I.", "" ], [ "Kschischang", "Frank R.", "" ] ]
Motivated by the looming "capacity crunch" in fiber-optic networks, information transmission over such systems is revisited. Among numerous distortions, inter-channel interference in multiuser wavelength-division multiplexing (WDM) is identified as the seemingly intractable factor limiting the achievable rate at high l...
2206.06155
Felix Lanfermann
Felix Lanfermann and Sebastian Schmitt
Concept Identification for Complex Engineering Datasets
19 pages, 14 figures, accepted at Advanced Engineering Informatics
null
10.1016/j.aei.2022.101704
null
cs.LG
http://creativecommons.org/licenses/by-nc-nd/4.0/
Finding meaningful concepts in engineering application datasets which allow for a sensible grouping of designs is very helpful in many contexts. It allows for determining different groups of designs with similar properties and provides useful knowledge in the engineering decision making process. Also, it opens the ro...
[ { "created": "Thu, 9 Jun 2022 09:39:46 GMT", "version": "v1" }, { "created": "Fri, 22 Jul 2022 07:52:03 GMT", "version": "v2" } ]
2022-08-17
[ [ "Lanfermann", "Felix", "" ], [ "Schmitt", "Sebastian", "" ] ]
Finding meaningful concepts in engineering application datasets which allow for a sensible grouping of designs is very helpful in many contexts. It allows for determining different groups of designs with similar properties and provides useful knowledge in the engineering decision making process. Also, it opens the rout...
2308.10110
Yihua Zhang
Yihua Zhang, Ruisi Cai, Tianlong Chen, Guanhua Zhang, Huan Zhang, Pin-Yu Chen, Shiyu Chang, Zhangyang Wang, Sijia Liu
Robust Mixture-of-Expert Training for Convolutional Neural Networks
ICCV 2023
null
null
null
cs.CV cs.AI cs.LG
http://creativecommons.org/licenses/by/4.0/
Sparsely-gated Mixture of Expert (MoE), an emerging deep model architecture, has demonstrated a great promise to enable high-accuracy and ultra-efficient model inference. Despite the growing popularity of MoE, little work investigated its potential to advance convolutional neural networks (CNNs), especially in the pl...
[ { "created": "Sat, 19 Aug 2023 20:58:21 GMT", "version": "v1" } ]
2023-08-22
[ [ "Zhang", "Yihua", "" ], [ "Cai", "Ruisi", "" ], [ "Chen", "Tianlong", "" ], [ "Zhang", "Guanhua", "" ], [ "Zhang", "Huan", "" ], [ "Chen", "Pin-Yu", "" ], [ "Chang", "Shiyu", "" ], [ "Wang", "Zh...
Sparsely-gated Mixture of Expert (MoE), an emerging deep model architecture, has demonstrated a great promise to enable high-accuracy and ultra-efficient model inference. Despite the growing popularity of MoE, little work investigated its potential to advance convolutional neural networks (CNNs), especially in the plan...
2311.05863
Yuanmin Tang
Yuanmin Tang, Jing Yu, Keke Gai, Xiangyan Qu, Yue Hu, Gang Xiong, Qi Wu
Watermarking Vision-Language Pre-trained Models for Multi-modal Embedding as a Service
null
null
null
null
cs.CR cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recent advances in vision-language pre-trained models (VLPs) have significantly increased visual understanding and cross-modal analysis capabilities. Companies have emerged to provide multi-modal Embedding as a Service (EaaS) based on VLPs (e.g., CLIP-based VLPs), which cost a large amount of training data and resour...
[ { "created": "Fri, 10 Nov 2023 04:27:27 GMT", "version": "v1" } ]
2023-11-13
[ [ "Tang", "Yuanmin", "" ], [ "Yu", "Jing", "" ], [ "Gai", "Keke", "" ], [ "Qu", "Xiangyan", "" ], [ "Hu", "Yue", "" ], [ "Xiong", "Gang", "" ], [ "Wu", "Qi", "" ] ]
Recent advances in vision-language pre-trained models (VLPs) have significantly increased visual understanding and cross-modal analysis capabilities. Companies have emerged to provide multi-modal Embedding as a Service (EaaS) based on VLPs (e.g., CLIP-based VLPs), which cost a large amount of training data and resource...
1808.02633
Liting Sun
Liting Sun, Wei Zhan, Masayoshi Tomizuka, and Anca D. Dragan
Courteous Autonomous Cars
International Conference on Intelligent Robots (IROS) 2018
null
null
null
cs.RO cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Typically, autonomous cars optimize for a combination of safety, efficiency, and driving quality. But as we get better at this optimization, we start seeing behavior go from too conservative to too aggressive. The car's behavior exposes the incentives we provide in its cost function. In this work, we argue for cars t...
[ { "created": "Wed, 8 Aug 2018 05:45:24 GMT", "version": "v1" }, { "created": "Thu, 16 Aug 2018 02:47:58 GMT", "version": "v2" } ]
2018-08-17
[ [ "Sun", "Liting", "" ], [ "Zhan", "Wei", "" ], [ "Tomizuka", "Masayoshi", "" ], [ "Dragan", "Anca D.", "" ] ]
Typically, autonomous cars optimize for a combination of safety, efficiency, and driving quality. But as we get better at this optimization, we start seeing behavior go from too conservative to too aggressive. The car's behavior exposes the incentives we provide in its cost function. In this work, we argue for cars tha...
2407.05627
Surya Agustian Mr.
Surya Agustian, Muhammad Irfan Syah, Nurul Fatiara, and Rahmad Abdillah
New Directions in Text Classification Research: Maximizing The Performance of Sentiment Classification from Limited Data
9 pages, in Indonesian language. intro to a shared task in sentiment classification
null
null
null
cs.CL cs.IR cs.IT cs.LG cs.SI math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The stakeholders' needs in sentiment analysis for various issues, whether positive or negative, are speed and accuracy. One new challenge in sentiment analysis tasks is the limited training data, which often leads to suboptimal machine learning models and poor performance on test data. This paper discusses the proble...
[ { "created": "Mon, 8 Jul 2024 05:42:29 GMT", "version": "v1" } ]
2024-07-09
[ [ "Agustian", "Surya", "" ], [ "Syah", "Muhammad Irfan", "" ], [ "Fatiara", "Nurul", "" ], [ "Abdillah", "Rahmad", "" ] ]
The stakeholders' needs in sentiment analysis for various issues, whether positive or negative, are speed and accuracy. One new challenge in sentiment analysis tasks is the limited training data, which often leads to suboptimal machine learning models and poor performance on test data. This paper discusses the problem ...
1808.03485
Arno Solin
Santiago Cort\'es, Arno Solin, Juho Kannala
Deep Learning Based Speed Estimation for Constraining Strapdown Inertial Navigation on Smartphones
To appear in IEEE International Workshop on Machine Learning for Signal Processing (MLSP) 2018
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Strapdown inertial navigation systems are sensitive to the quality of the data provided by the accelerometer and gyroscope. Low-grade IMUs in handheld smart-devices pose a problem for inertial odometry on these devices. We propose a scheme for constraining the inertial odometry problem by complementing non-linear sta...
[ { "created": "Fri, 10 Aug 2018 11:03:58 GMT", "version": "v1" } ]
2018-08-13
[ [ "Cortés", "Santiago", "" ], [ "Solin", "Arno", "" ], [ "Kannala", "Juho", "" ] ]
Strapdown inertial navigation systems are sensitive to the quality of the data provided by the accelerometer and gyroscope. Low-grade IMUs in handheld smart-devices pose a problem for inertial odometry on these devices. We propose a scheme for constraining the inertial odometry problem by complementing non-linear state...
2403.18305
Youngbin Lee
Minjoo Choi, Seonmi Kim, Yejin Kim, Youngbin Lee, Joohwan Hong, Yongjae Lee
A Recommender System for NFT Collectibles with Item Feature
Presented at the AAAI 2023 Bridge on AI for Financial Services (https://sites.google.com/view/aaai-ai-fin/home)
null
null
null
cs.IR cs.AI
http://creativecommons.org/licenses/by/4.0/
Recommender systems have been actively studied and applied in various domains to deal with information overload. Although there are numerous studies on recommender systems for movies, music, and e-commerce, comparatively less attention has been paid to the recommender system for NFTs despite the continuous growth of ...
[ { "created": "Wed, 27 Mar 2024 06:59:39 GMT", "version": "v1" }, { "created": "Wed, 3 Apr 2024 06:52:50 GMT", "version": "v2" } ]
2024-04-04
[ [ "Choi", "Minjoo", "" ], [ "Kim", "Seonmi", "" ], [ "Kim", "Yejin", "" ], [ "Lee", "Youngbin", "" ], [ "Hong", "Joohwan", "" ], [ "Lee", "Yongjae", "" ] ]
Recommender systems have been actively studied and applied in various domains to deal with information overload. Although there are numerous studies on recommender systems for movies, music, and e-commerce, comparatively less attention has been paid to the recommender system for NFTs despite the continuous growth of th...
1709.05865
Shubham Dham
Shubham Dham, Anirudh Sharma, Abhinav Dhall
Depression Scale Recognition from Audio, Visual and Text Analysis
null
null
null
null
cs.CV cs.LG cs.MM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Depression is a major mental health disorder that is rapidly affecting lives worldwide. Depression not only impacts emotional but also physical and psychological state of the person. Its symptoms include lack of interest in daily activities, feeling low, anxiety, frustration, loss of weight and even feeling of self-h...
[ { "created": "Mon, 18 Sep 2017 11:26:01 GMT", "version": "v1" } ]
2017-09-19
[ [ "Dham", "Shubham", "" ], [ "Sharma", "Anirudh", "" ], [ "Dhall", "Abhinav", "" ] ]
Depression is a major mental health disorder that is rapidly affecting lives worldwide. Depression not only impacts emotional but also physical and psychological state of the person. Its symptoms include lack of interest in daily activities, feeling low, anxiety, frustration, loss of weight and even feeling of self-hat...
2311.04293
Tara Akhound-Sadegh
Tara Akhound-Sadegh, Laurence Perreault-Levasseur, Johannes Brandstetter, Max Welling, Siamak Ravanbakhsh
Lie Point Symmetry and Physics Informed Networks
NeurIPS 2023
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Symmetries have been leveraged to improve the generalization of neural networks through different mechanisms from data augmentation to equivariant architectures. However, despite their potential, their integration into neural solvers for partial differential equations (PDEs) remains largely unexplored. We explore the...
[ { "created": "Tue, 7 Nov 2023 19:07:16 GMT", "version": "v1" } ]
2023-11-09
[ [ "Akhound-Sadegh", "Tara", "" ], [ "Perreault-Levasseur", "Laurence", "" ], [ "Brandstetter", "Johannes", "" ], [ "Welling", "Max", "" ], [ "Ravanbakhsh", "Siamak", "" ] ]
Symmetries have been leveraged to improve the generalization of neural networks through different mechanisms from data augmentation to equivariant architectures. However, despite their potential, their integration into neural solvers for partial differential equations (PDEs) remains largely unexplored. We explore the i...
2108.12375
Ali Karimoddini
Muhammad Mobaidul Islam, Abdullah Al Redwan Newaz, and Ali Karimoddini
A Pedestrian Detection and Tracking Framework for Autonomous Cars: Efficient Fusion of Camera and LiDAR Data
null
null
null
null
cs.CV cs.AI cs.LG cs.RO
http://creativecommons.org/licenses/by-nc-sa/4.0/
This paper presents a novel method for pedestrian detection and tracking by fusing camera and LiDAR sensor data. To deal with the challenges associated with the autonomous driving scenarios, an integrated tracking and detection framework is proposed. The detection phase is performed by converting LiDAR streams to com...
[ { "created": "Fri, 27 Aug 2021 16:16:01 GMT", "version": "v1" } ]
2021-08-30
[ [ "Islam", "Muhammad Mobaidul", "" ], [ "Newaz", "Abdullah Al Redwan", "" ], [ "Karimoddini", "Ali", "" ] ]
This paper presents a novel method for pedestrian detection and tracking by fusing camera and LiDAR sensor data. To deal with the challenges associated with the autonomous driving scenarios, an integrated tracking and detection framework is proposed. The detection phase is performed by converting LiDAR streams to compu...
2104.07228
Wenhao Yu
Wenhao Yu, Chenguang Zhu, Tong Zhao, Zhichun Guo, Meng Jiang
Sentence-Permuted Paragraph Generation
EMNLP 2021 (long paper)
null
null
null
cs.CL cs.AI
http://creativecommons.org/licenses/by/4.0/
Generating paragraphs of diverse contents is important in many applications. Existing generation models produce similar contents from homogenized contexts due to the fixed left-to-right sentence order. Our idea is permuting the sentence orders to improve the content diversity of multi-sentence paragraph. We propose a...
[ { "created": "Thu, 15 Apr 2021 04:17:03 GMT", "version": "v1" }, { "created": "Tue, 7 Sep 2021 05:41:59 GMT", "version": "v2" } ]
2021-09-08
[ [ "Yu", "Wenhao", "" ], [ "Zhu", "Chenguang", "" ], [ "Zhao", "Tong", "" ], [ "Guo", "Zhichun", "" ], [ "Jiang", "Meng", "" ] ]
Generating paragraphs of diverse contents is important in many applications. Existing generation models produce similar contents from homogenized contexts due to the fixed left-to-right sentence order. Our idea is permuting the sentence orders to improve the content diversity of multi-sentence paragraph. We propose a n...
2102.03234
David Hafner
Vladlen Koltun, David Hafner
The h-index is no longer an effective correlate of scientific reputation
An interactive visualization of our work can be found at https://h-frac.org
null
10.1371/journal.pone.0253397
null
cs.DL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The impact of individual scientists is commonly quantified using citation-based measures. The most common such measure is the h-index. A scientist's h-index affects hiring, promotion, and funding decisions, and thus shapes the progress of science. Here we report a large-scale study of scientometric measures, analyzin...
[ { "created": "Fri, 5 Feb 2021 15:28:39 GMT", "version": "v1" } ]
2021-09-15
[ [ "Koltun", "Vladlen", "" ], [ "Hafner", "David", "" ] ]
The impact of individual scientists is commonly quantified using citation-based measures. The most common such measure is the h-index. A scientist's h-index affects hiring, promotion, and funding decisions, and thus shapes the progress of science. Here we report a large-scale study of scientometric measures, analyzing ...
2303.11866
Zaid Khan
Zaid Khan and Yun Fu
Contrastive Alignment of Vision to Language Through Parameter-Efficient Transfer Learning
Accepted to ICLR 2023
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Contrastive vision-language models (e.g. CLIP) are typically created by updating all the parameters of a vision model and language model through contrastive training. Can such models be created by a small number of parameter updates to an already-trained language model and vision model? The literature describes techn...
[ { "created": "Tue, 21 Mar 2023 14:12:08 GMT", "version": "v1" } ]
2023-03-22
[ [ "Khan", "Zaid", "" ], [ "Fu", "Yun", "" ] ]
Contrastive vision-language models (e.g. CLIP) are typically created by updating all the parameters of a vision model and language model through contrastive training. Can such models be created by a small number of parameter updates to an already-trained language model and vision model? The literature describes techniq...
2302.12689
Silvan Mertes
Tobias Huber, Maximilian Demmler, Silvan Mertes, Matthew L. Olson, Elisabeth Andr\'e
GANterfactual-RL: Understanding Reinforcement Learning Agents' Strategies through Visual Counterfactual Explanations
null
null
null
null
cs.LG cs.AI
http://creativecommons.org/licenses/by/4.0/
Counterfactual explanations are a common tool to explain artificial intelligence models. For Reinforcement Learning (RL) agents, they answer "Why not?" or "What if?" questions by illustrating what minimal change to a state is needed such that an agent chooses a different action. Generating counterfactual explanations...
[ { "created": "Fri, 24 Feb 2023 15:29:43 GMT", "version": "v1" } ]
2023-02-27
[ [ "Huber", "Tobias", "" ], [ "Demmler", "Maximilian", "" ], [ "Mertes", "Silvan", "" ], [ "Olson", "Matthew L.", "" ], [ "André", "Elisabeth", "" ] ]
Counterfactual explanations are a common tool to explain artificial intelligence models. For Reinforcement Learning (RL) agents, they answer "Why not?" or "What if?" questions by illustrating what minimal change to a state is needed such that an agent chooses a different action. Generating counterfactual explanations f...
1805.11272
Cecilia Summers
Cecilia Summers, Michael J. Dinneen
Improved Mixed-Example Data Augmentation
9 pages
null
null
null
cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In order to reduce overfitting, neural networks are typically trained with data augmentation, the practice of artificially generating additional training data via label-preserving transformations of existing training examples. While these types of transformations make intuitive sense, recent work has demonstrated tha...
[ { "created": "Tue, 29 May 2018 07:06:58 GMT", "version": "v1" }, { "created": "Fri, 1 Jun 2018 06:50:22 GMT", "version": "v2" }, { "created": "Thu, 18 Oct 2018 06:10:23 GMT", "version": "v3" }, { "created": "Sat, 19 Jan 2019 07:04:35 GMT", "version": "v4" } ]
2019-01-23
[ [ "Summers", "Cecilia", "" ], [ "Dinneen", "Michael J.", "" ] ]
In order to reduce overfitting, neural networks are typically trained with data augmentation, the practice of artificially generating additional training data via label-preserving transformations of existing training examples. While these types of transformations make intuitive sense, recent work has demonstrated that ...
2306.00188
Guangyao Zheng
Guangyao Zheng, Shuhao Lai, Vladimir Braverman, Michael A. Jacobs, Vishwa S. Parekh
Multi-environment lifelong deep reinforcement learning for medical imaging
null
null
null
null
cs.LG cs.CV eess.IV
http://creativecommons.org/licenses/by/4.0/
Deep reinforcement learning(DRL) is increasingly being explored in medical imaging. However, the environments for medical imaging tasks are constantly evolving in terms of imaging orientations, imaging sequences, and pathologies. To that end, we developed a Lifelong DRL framework, SERIL to continually learn new tasks...
[ { "created": "Wed, 31 May 2023 21:06:42 GMT", "version": "v1" } ]
2023-06-02
[ [ "Zheng", "Guangyao", "" ], [ "Lai", "Shuhao", "" ], [ "Braverman", "Vladimir", "" ], [ "Jacobs", "Michael A.", "" ], [ "Parekh", "Vishwa S.", "" ] ]
Deep reinforcement learning(DRL) is increasingly being explored in medical imaging. However, the environments for medical imaging tasks are constantly evolving in terms of imaging orientations, imaging sequences, and pathologies. To that end, we developed a Lifelong DRL framework, SERIL to continually learn new tasks i...
2112.06374
Yunhai Han
Yunhai Han, Kelin Yu, Rahul Batra, Nathan Boyd, Chaitanya Mehta, Tuo Zhao, Yu She, Seth Hutchinson, and Ye Zhao
Learning Generalizable Vision-Tactile Robotic Grasping Strategy for Deformable Objects via Transformer
null
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Reliable robotic grasping, especially with deformable objects such as fruits, remains a challenging task due to underactuated contact interactions with a gripper, unknown object dynamics and geometries. In this study, we propose a Transformer-based robotic grasping framework for rigid grippers that leverage tactile a...
[ { "created": "Mon, 13 Dec 2021 02:07:21 GMT", "version": "v1" }, { "created": "Mon, 20 Dec 2021 03:42:03 GMT", "version": "v2" }, { "created": "Tue, 8 Mar 2022 14:36:14 GMT", "version": "v3" }, { "created": "Wed, 4 Jan 2023 03:07:44 GMT", "version": "v4" }, { "cre...
2023-07-25
[ [ "Han", "Yunhai", "" ], [ "Yu", "Kelin", "" ], [ "Batra", "Rahul", "" ], [ "Boyd", "Nathan", "" ], [ "Mehta", "Chaitanya", "" ], [ "Zhao", "Tuo", "" ], [ "She", "Yu", "" ], [ "Hutchinson", "Seth"...
Reliable robotic grasping, especially with deformable objects such as fruits, remains a challenging task due to underactuated contact interactions with a gripper, unknown object dynamics and geometries. In this study, we propose a Transformer-based robotic grasping framework for rigid grippers that leverage tactile and...
2110.12334
Jingyuan Yang
Jingyuan Yang, Xinbo Gao, Leida Li, Xiumei Wang, and Jinshan Ding
SOLVER: Scene-Object Interrelated Visual Emotion Reasoning Network
Accepted by TIP
in IEEE Transactions on Image Processing, vol. 30, pp. 8686-8701, 2021
10.1109/TIP.2021.3118983
null
cs.CV cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Visual Emotion Analysis (VEA) aims at finding out how people feel emotionally towards different visual stimuli, which has attracted great attention recently with the prevalence of sharing images on social networks. Since human emotion involves a highly complex and abstract cognitive process, it is difficult to infer ...
[ { "created": "Sun, 24 Oct 2021 02:41:41 GMT", "version": "v1" } ]
2021-10-26
[ [ "Yang", "Jingyuan", "" ], [ "Gao", "Xinbo", "" ], [ "Li", "Leida", "" ], [ "Wang", "Xiumei", "" ], [ "Ding", "Jinshan", "" ] ]
Visual Emotion Analysis (VEA) aims at finding out how people feel emotionally towards different visual stimuli, which has attracted great attention recently with the prevalence of sharing images on social networks. Since human emotion involves a highly complex and abstract cognitive process, it is difficult to infer vi...
1904.02348
Yanchao Wang
Yan-Chao Wang and Feng Lin and Hock-Soon Seah
Orthogonal Voronoi Diagram and Treemap
null
null
null
null
cs.DS cs.GR cs.HC cs.MM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we propose a novel space partitioning strategy for implicit hierarchy visualization such that the new plot not only has a tidy layout similar to the treemap, but also is flexible to data changes similar to the Voronoi treemap. To achieve this, we define a new distance function and neighborhood relation...
[ { "created": "Thu, 4 Apr 2019 05:05:49 GMT", "version": "v1" } ]
2020-09-17
[ [ "Wang", "Yan-Chao", "" ], [ "Lin", "Feng", "" ], [ "Seah", "Hock-Soon", "" ] ]
In this paper, we propose a novel space partitioning strategy for implicit hierarchy visualization such that the new plot not only has a tidy layout similar to the treemap, but also is flexible to data changes similar to the Voronoi treemap. To achieve this, we define a new distance function and neighborhood relationsh...
1805.05132
Chunbiao Zhu
Chunbiao Zhu, Wenhao Zhang, Thomas H. Li, Ge Li
Exploiting the Value of the Center-dark Channel Prior for Salient Object Detection
Project website: https://chunbiaozhu.github.io/ACVR2017/
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Saliency detection aims to detect the most attractive objects in images and is widely used as a foundation for various applications. In this paper, we propose a novel salient object detection algorithm for RGB-D images using center-dark channel priors. First, we generate an initial saliency map based on a color salie...
[ { "created": "Mon, 14 May 2018 12:02:20 GMT", "version": "v1" } ]
2018-05-15
[ [ "Zhu", "Chunbiao", "" ], [ "Zhang", "Wenhao", "" ], [ "Li", "Thomas H.", "" ], [ "Li", "Ge", "" ] ]
Saliency detection aims to detect the most attractive objects in images and is widely used as a foundation for various applications. In this paper, we propose a novel salient object detection algorithm for RGB-D images using center-dark channel priors. First, we generate an initial saliency map based on a color salienc...
2210.05895
Haodong Duan
Haodong Duan, Jiaqi Wang, Kai Chen, Dahua Lin
DG-STGCN: Dynamic Spatial-Temporal Modeling for Skeleton-based Action Recognition
Codes will be released in https://github.com/kennymckormick/pyskl
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Graph convolution networks (GCN) have been widely used in skeleton-based action recognition. We note that existing GCN-based approaches primarily rely on prescribed graphical structures (ie., a manually defined topology of skeleton joints), which limits their flexibility to capture complicated correlations between jo...
[ { "created": "Wed, 12 Oct 2022 03:17:37 GMT", "version": "v1" } ]
2022-10-13
[ [ "Duan", "Haodong", "" ], [ "Wang", "Jiaqi", "" ], [ "Chen", "Kai", "" ], [ "Lin", "Dahua", "" ] ]
Graph convolution networks (GCN) have been widely used in skeleton-based action recognition. We note that existing GCN-based approaches primarily rely on prescribed graphical structures (ie., a manually defined topology of skeleton joints), which limits their flexibility to capture complicated correlations between join...
2407.12999
Mihai Christodorescu
Mihai Christodorescu, Ryan Craven, Soheil Feizi, Neil Gong, Mia Hoffmann, Somesh Jha, Zhengyuan Jiang, Mehrdad Saberi Kamarposhti, John Mitchell, Jessica Newman, Emelia Probasco, Yanjun Qi, Khawaja Shams, Matthew Turek
Securing the Future of GenAI: Policy and Technology
null
null
null
null
cs.CY cs.AI cs.CR
http://creativecommons.org/licenses/by/4.0/
The rise of Generative AI (GenAI) brings about transformative potential across sectors, but its dual-use nature also amplifies risks. Governments globally are grappling with the challenge of regulating GenAI, balancing innovation against safety. China, the United States (US), and the European Union (EU) are at the fo...
[ { "created": "Tue, 21 May 2024 20:30:01 GMT", "version": "v1" } ]
2024-07-19
[ [ "Christodorescu", "Mihai", "" ], [ "Craven", "Ryan", "" ], [ "Feizi", "Soheil", "" ], [ "Gong", "Neil", "" ], [ "Hoffmann", "Mia", "" ], [ "Jha", "Somesh", "" ], [ "Jiang", "Zhengyuan", "" ], [ "Kam...
The rise of Generative AI (GenAI) brings about transformative potential across sectors, but its dual-use nature also amplifies risks. Governments globally are grappling with the challenge of regulating GenAI, balancing innovation against safety. China, the United States (US), and the European Union (EU) are at the fore...
2403.06173
Johann Huber
Johann Huber, Fran\c{c}ois H\'el\'enon, Mathilde Kappel, Elie Chelly, Mahdi Khoramshahi, Fa\"iz Ben Amar, St\'ephane Doncieux
Speeding up 6-DoF Grasp Sampling with Quality-Diversity
7 pages, 8 figures. Preprint version
null
null
null
cs.RO cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recent advances in AI have led to significant results in robotic learning, including natural language-conditioned planning and efficient optimization of controllers using generative models. However, the interaction data remains the bottleneck for generalization. Getting data for grasping is a critical challenge, as t...
[ { "created": "Sun, 10 Mar 2024 10:58:54 GMT", "version": "v1" } ]
2024-03-12
[ [ "Huber", "Johann", "" ], [ "Hélénon", "François", "" ], [ "Kappel", "Mathilde", "" ], [ "Chelly", "Elie", "" ], [ "Khoramshahi", "Mahdi", "" ], [ "Amar", "Faïz Ben", "" ], [ "Doncieux", "Stéphane", "" ] ]
Recent advances in AI have led to significant results in robotic learning, including natural language-conditioned planning and efficient optimization of controllers using generative models. However, the interaction data remains the bottleneck for generalization. Getting data for grasping is a critical challenge, as thi...
1904.01569
Saining Xie
Saining Xie, Alexander Kirillov, Ross Girshick, Kaiming He
Exploring Randomly Wired Neural Networks for Image Recognition
Technical report
null
null
null
cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Neural networks for image recognition have evolved through extensive manual design from simple chain-like models to structures with multiple wiring paths. The success of ResNets and DenseNets is due in large part to their innovative wiring plans. Now, neural architecture search (NAS) studies are exploring the joint o...
[ { "created": "Tue, 2 Apr 2019 17:57:16 GMT", "version": "v1" }, { "created": "Mon, 8 Apr 2019 17:50:26 GMT", "version": "v2" } ]
2019-04-09
[ [ "Xie", "Saining", "" ], [ "Kirillov", "Alexander", "" ], [ "Girshick", "Ross", "" ], [ "He", "Kaiming", "" ] ]
Neural networks for image recognition have evolved through extensive manual design from simple chain-like models to structures with multiple wiring paths. The success of ResNets and DenseNets is due in large part to their innovative wiring plans. Now, neural architecture search (NAS) studies are exploring the joint opt...
1912.10702
Bin Dai
Bin Dai, Ziyu Wang, David Wipf
The Usual Suspects? Reassessing Blame for VAE Posterior Collapse
null
null
null
null
cs.LG cs.CV stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In narrow asymptotic settings Gaussian VAE models of continuous data have been shown to possess global optima aligned with ground-truth distributions. Even so, it is well known that poor solutions whereby the latent posterior collapses to an uninformative prior are sometimes obtained in practice. However, contrary to...
[ { "created": "Mon, 23 Dec 2019 09:40:30 GMT", "version": "v1" } ]
2019-12-24
[ [ "Dai", "Bin", "" ], [ "Wang", "Ziyu", "" ], [ "Wipf", "David", "" ] ]
In narrow asymptotic settings Gaussian VAE models of continuous data have been shown to possess global optima aligned with ground-truth distributions. Even so, it is well known that poor solutions whereby the latent posterior collapses to an uninformative prior are sometimes obtained in practice. However, contrary to c...
1910.09704
Vamsi Amalladinne
Vamsi K. Amalladinne, Jean-Francois Chamberland, Krishna R. Narayanan
An enhanced decoding algorithm for coded compressed sensing
Submitted to ICASSP2020
null
null
null
cs.IT eess.SP math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Coded compressed sensing is an algorithmic framework tailored to sparse recovery in very large dimensional spaces. This framework is originally envisioned for the unsourced multiple access channel, a wireless paradigm attuned to machine-type communications. Coded compressed sensing uses a divide-and-conquer approach ...
[ { "created": "Tue, 22 Oct 2019 00:17:37 GMT", "version": "v1" } ]
2019-10-23
[ [ "Amalladinne", "Vamsi K.", "" ], [ "Chamberland", "Jean-Francois", "" ], [ "Narayanan", "Krishna R.", "" ] ]
Coded compressed sensing is an algorithmic framework tailored to sparse recovery in very large dimensional spaces. This framework is originally envisioned for the unsourced multiple access channel, a wireless paradigm attuned to machine-type communications. Coded compressed sensing uses a divide-and-conquer approach to...
2006.10909
Yatin Chaudhary
Pankaj Gupta and Yatin Chaudhary and Thomas Runkler and Hinrich Sch\"utze
Neural Topic Modeling with Continual Lifelong Learning
Accepted at ICML2020 (13 pages, 11 figures, 9 tables)
null
null
null
cs.CL cs.IR cs.LG cs.NE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Lifelong learning has recently attracted attention in building machine learning systems that continually accumulate and transfer knowledge to help future learning. Unsupervised topic modeling has been popularly used to discover topics from document collections. However, the application of topic modeling is challengin...
[ { "created": "Fri, 19 Jun 2020 00:43:23 GMT", "version": "v1" }, { "created": "Tue, 27 Jun 2023 05:32:12 GMT", "version": "v2" } ]
2023-06-28
[ [ "Gupta", "Pankaj", "" ], [ "Chaudhary", "Yatin", "" ], [ "Runkler", "Thomas", "" ], [ "Schütze", "Hinrich", "" ] ]
Lifelong learning has recently attracted attention in building machine learning systems that continually accumulate and transfer knowledge to help future learning. Unsupervised topic modeling has been popularly used to discover topics from document collections. However, the application of topic modeling is challenging ...
1806.07226
Wei Jiang
Wei Jiang, Yan Wu
DFNet: Semantic Segmentation on Panoramic Images with Dynamic Loss Weights and Residual Fusion Block
6 pages,3 figures
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
For the self-driving and automatic parking, perception is the basic and critical technique, moreover, the detection of lane markings and parking slots is an important part of visual perception. In this paper, we use the semantic segmentation method to segment the area and classify the class of lane makings and parkin...
[ { "created": "Mon, 11 Jun 2018 05:09:25 GMT", "version": "v1" } ]
2018-06-20
[ [ "Jiang", "Wei", "" ], [ "Wu", "Yan", "" ] ]
For the self-driving and automatic parking, perception is the basic and critical technique, moreover, the detection of lane markings and parking slots is an important part of visual perception. In this paper, we use the semantic segmentation method to segment the area and classify the class of lane makings and parking ...
2109.12008
Bruno Taill\'e
Bruno Taill\'e, Vincent Guigue, Geoffrey Scoutheeten and Patrick Gallinari
Separating Retention from Extraction in the Evaluation of End-to-end Relation Extraction
Accepted at EMNLP 2021
null
null
null
cs.CL cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
State-of-the-art NLP models can adopt shallow heuristics that limit their generalization capability (McCoy et al., 2019). Such heuristics include lexical overlap with the training set in Named-Entity Recognition (Taill\'e et al., 2020) and Event or Type heuristics in Relation Extraction (Rosenman et al., 2020). In th...
[ { "created": "Fri, 24 Sep 2021 15:04:39 GMT", "version": "v1" } ]
2021-09-27
[ [ "Taillé", "Bruno", "" ], [ "Guigue", "Vincent", "" ], [ "Scoutheeten", "Geoffrey", "" ], [ "Gallinari", "Patrick", "" ] ]
State-of-the-art NLP models can adopt shallow heuristics that limit their generalization capability (McCoy et al., 2019). Such heuristics include lexical overlap with the training set in Named-Entity Recognition (Taill\'e et al., 2020) and Event or Type heuristics in Relation Extraction (Rosenman et al., 2020). In the ...
2402.15174
Pablo Donato
Pablo Donato (PARTOUT)
The Flower Calculus
null
Leibniz International Proceedings in Informatics , 2024, 9th International Conference on Formal Structures for Computation and Deduction (FSCD 2024) (299), pp.5:1-5:24
null
null
cs.LO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We introduce the flower calculus, a deep inference proof system for intuitionistic first-order logic inspired by Peirce's existential graphs. It works as a rewriting system over inductive objects called ''flowers'', that enjoy both a graphical interpretation as topological diagrams, and a textual presentation as nest...
[ { "created": "Fri, 23 Feb 2024 08:13:22 GMT", "version": "v1" }, { "created": "Thu, 11 Jul 2024 08:45:34 GMT", "version": "v2" }, { "created": "Mon, 15 Jul 2024 08:29:07 GMT", "version": "v3" } ]
2024-07-16
[ [ "Donato", "Pablo", "", "PARTOUT" ] ]
We introduce the flower calculus, a deep inference proof system for intuitionistic first-order logic inspired by Peirce's existential graphs. It works as a rewriting system over inductive objects called ''flowers'', that enjoy both a graphical interpretation as topological diagrams, and a textual presentation as nested...
1101.0698
Gerhard de Koning Gans
Gerhard de Koning Gans and Eric R. Verheul
Best Effort and Practice Activation Codes
15 pages, 3 figures, TrustBus 2011
null
null
null
cs.CR cs.CE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Activation Codes are used in many different digital services and known by many different names including voucher, e-coupon and discount code. In this paper we focus on a specific class of ACs that are short, human-readable, fixed-length and represent value. Even though this class of codes is extensively used there ar...
[ { "created": "Tue, 4 Jan 2011 10:41:27 GMT", "version": "v1" }, { "created": "Thu, 23 Jun 2011 11:26:51 GMT", "version": "v2" } ]
2011-06-24
[ [ "Gans", "Gerhard de Koning", "" ], [ "Verheul", "Eric R.", "" ] ]
Activation Codes are used in many different digital services and known by many different names including voucher, e-coupon and discount code. In this paper we focus on a specific class of ACs that are short, human-readable, fixed-length and represent value. Even though this class of codes is extensively used there are ...
1504.07384
Andreas Pavlogiannis
Krishnendu Chatterjee and Rasmus Ibsen-Jensen and Andreas Pavlogiannis
Faster Algorithms for Quantitative Verification in Constant Treewidth Graphs
null
null
null
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We consider the core algorithmic problems related to verification of systems with respect to three classical quantitative properties, namely, the mean-payoff property, the ratio property, and the minimum initial credit for energy property. The algorithmic problem given a graph and a quantitative property asks to comp...
[ { "created": "Tue, 28 Apr 2015 08:53:53 GMT", "version": "v1" } ]
2015-04-29
[ [ "Chatterjee", "Krishnendu", "" ], [ "Ibsen-Jensen", "Rasmus", "" ], [ "Pavlogiannis", "Andreas", "" ] ]
We consider the core algorithmic problems related to verification of systems with respect to three classical quantitative properties, namely, the mean-payoff property, the ratio property, and the minimum initial credit for energy property. The algorithmic problem given a graph and a quantitative property asks to comput...
2310.05597
Molly Petersen
Molly R. Petersen, Lonneke van der Plas
Can language models learn analogical reasoning? Investigating training objectives and comparisons to human performance
null
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
While analogies are a common way to evaluate word embeddings in NLP, it is also of interest to investigate whether or not analogical reasoning is a task in itself that can be learned. In this paper, we test several ways to learn basic analogical reasoning, specifically focusing on analogies that are more typical of w...
[ { "created": "Mon, 9 Oct 2023 10:34:38 GMT", "version": "v1" }, { "created": "Fri, 13 Oct 2023 15:07:28 GMT", "version": "v2" }, { "created": "Sun, 22 Oct 2023 09:17:30 GMT", "version": "v3" }, { "created": "Fri, 3 May 2024 10:22:13 GMT", "version": "v4" } ]
2024-05-06
[ [ "Petersen", "Molly R.", "" ], [ "van der Plas", "Lonneke", "" ] ]
While analogies are a common way to evaluate word embeddings in NLP, it is also of interest to investigate whether or not analogical reasoning is a task in itself that can be learned. In this paper, we test several ways to learn basic analogical reasoning, specifically focusing on analogies that are more typical of wha...
2206.06975
Min Li
Zhengyuan Shi, Min Li, Sadaf Khan, Liuzheng Wang, Naixing Wang, Yu Huang, Qiang Xu
DeepTPI: Test Point Insertion with Deep Reinforcement Learning
Accepted by ITC 2022
null
null
null
cs.LG cs.AI cs.AR
http://creativecommons.org/licenses/by/4.0/
Test point insertion (TPI) is a widely used technique for testability enhancement, especially for logic built-in self-test (LBIST) due to its relatively low fault coverage. In this paper, we propose a novel TPI approach based on deep reinforcement learning (DRL), named DeepTPI. Unlike previous learning-based solution...
[ { "created": "Tue, 7 Jun 2022 14:13:42 GMT", "version": "v1" }, { "created": "Mon, 27 Jun 2022 13:56:05 GMT", "version": "v2" } ]
2022-06-29
[ [ "Shi", "Zhengyuan", "" ], [ "Li", "Min", "" ], [ "Khan", "Sadaf", "" ], [ "Wang", "Liuzheng", "" ], [ "Wang", "Naixing", "" ], [ "Huang", "Yu", "" ], [ "Xu", "Qiang", "" ] ]
Test point insertion (TPI) is a widely used technique for testability enhancement, especially for logic built-in self-test (LBIST) due to its relatively low fault coverage. In this paper, we propose a novel TPI approach based on deep reinforcement learning (DRL), named DeepTPI. Unlike previous learning-based solutions ...
2405.01734
Jai Singhal
Ankush Jain, Rinav Gupta, Jai Singhal
Diabetic Retinopathy Detection Using Quantum Transfer Learning
14 pages, 12 figures and 5 tables
null
null
null
cs.CV cs.AI
http://creativecommons.org/licenses/by/4.0/
Diabetic Retinopathy (DR), a prevalent complication in diabetes patients, can lead to vision impairment due to lesions formed on the retina. Detecting DR at an advanced stage often results in irreversible blindness. The traditional process of diagnosing DR through retina fundus images by ophthalmologists is not only ...
[ { "created": "Thu, 2 May 2024 21:09:39 GMT", "version": "v1" } ]
2024-05-06
[ [ "Jain", "Ankush", "" ], [ "Gupta", "Rinav", "" ], [ "Singhal", "Jai", "" ] ]
Diabetic Retinopathy (DR), a prevalent complication in diabetes patients, can lead to vision impairment due to lesions formed on the retina. Detecting DR at an advanced stage often results in irreversible blindness. The traditional process of diagnosing DR through retina fundus images by ophthalmologists is not only ti...
1904.00948
Maxwell Scale Uwadia Osagie
Maxwell Scale Uwadia Osagie, Osatohanmwen Enagbonma and Amanda Iriagbonse Inyang
The Historical Perspective of Botnet tools
null
null
10.9734/CJAST/2019/v32i630040
null
cs.CY
http://creativecommons.org/licenses/by-nc-sa/4.0/
Bot as it is popularly called is an inherent attributes of botnet tool. Botnet is a group of malicious tools acting as an entity. Furthermore, history has it that the aim of what gave rise to botnet was the idea to simplify the method of message exchange within networking platform. However, this has led to several bo...
[ { "created": "Sat, 2 Mar 2019 22:49:20 GMT", "version": "v1" } ]
2019-04-02
[ [ "Osagie", "Maxwell Scale Uwadia", "" ], [ "Enagbonma", "Osatohanmwen", "" ], [ "Inyang", "Amanda Iriagbonse", "" ] ]
Bot as it is popularly called is an inherent attributes of botnet tool. Botnet is a group of malicious tools acting as an entity. Furthermore, history has it that the aim of what gave rise to botnet was the idea to simplify the method of message exchange within networking platform. However, this has led to several botn...
2407.18571
Mahmoud Salhab
Mahmoud Salhab and Haidar Harmanani
Speech Bandwidth Expansion Via High Fidelity Generative Adversarial Networks
null
null
null
null
cs.SD cs.AI eess.AS
http://creativecommons.org/licenses/by/4.0/
Speech bandwidth expansion is crucial for expanding the frequency range of low-bandwidth speech signals, thereby improving audio quality, clarity and perceptibility in digital applications. Its applications span telephony, compression, text-to-speech synthesis, and speech recognition. This paper presents a novel appr...
[ { "created": "Fri, 26 Jul 2024 07:54:47 GMT", "version": "v1" }, { "created": "Mon, 29 Jul 2024 07:29:17 GMT", "version": "v2" } ]
2024-07-30
[ [ "Salhab", "Mahmoud", "" ], [ "Harmanani", "Haidar", "" ] ]
Speech bandwidth expansion is crucial for expanding the frequency range of low-bandwidth speech signals, thereby improving audio quality, clarity and perceptibility in digital applications. Its applications span telephony, compression, text-to-speech synthesis, and speech recognition. This paper presents a novel approa...
2009.13957
Jinting Wu
Jinting Wu, Yujia Zhang and Xiaoguang Zhao
A Prototype-Based Generalized Zero-Shot Learning Framework for Hand Gesture Recognition
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Hand gesture recognition plays a significant role in human-computer interaction for understanding various human gestures and their intent. However, most prior works can only recognize gestures of limited labeled classes and fail to adapt to new categories. The task of Generalized Zero-Shot Learning (GZSL) for hand ge...
[ { "created": "Tue, 29 Sep 2020 12:18:35 GMT", "version": "v1" } ]
2020-09-30
[ [ "Wu", "Jinting", "" ], [ "Zhang", "Yujia", "" ], [ "Zhao", "Xiaoguang", "" ] ]
Hand gesture recognition plays a significant role in human-computer interaction for understanding various human gestures and their intent. However, most prior works can only recognize gestures of limited labeled classes and fail to adapt to new categories. The task of Generalized Zero-Shot Learning (GZSL) for hand gest...
2005.06803
Limin Wang
Zhaoyang Liu, Limin Wang, Wayne Wu, Chen Qian, Tong Lu
TAM: Temporal Adaptive Module for Video Recognition
ICCV 2021 camera-ready version. Code is available at https://github.com/liu-zhy/temporal-adaptive-module
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Video data is with complex temporal dynamics due to various factors such as camera motion, speed variation, and different activities. To effectively capture this diverse motion pattern, this paper presents a new temporal adaptive module ({\bf TAM}) to generate video-specific temporal kernels based on its own feature ...
[ { "created": "Thu, 14 May 2020 08:22:45 GMT", "version": "v1" }, { "created": "Wed, 14 Oct 2020 02:00:40 GMT", "version": "v2" }, { "created": "Wed, 18 Aug 2021 12:19:06 GMT", "version": "v3" } ]
2021-08-19
[ [ "Liu", "Zhaoyang", "" ], [ "Wang", "Limin", "" ], [ "Wu", "Wayne", "" ], [ "Qian", "Chen", "" ], [ "Lu", "Tong", "" ] ]
Video data is with complex temporal dynamics due to various factors such as camera motion, speed variation, and different activities. To effectively capture this diverse motion pattern, this paper presents a new temporal adaptive module ({\bf TAM}) to generate video-specific temporal kernels based on its own feature ma...
2404.04405
Haiguang Li
Haiguang Li, Usama Pervaiz, Micha{\l} Matuszak, Robert Kamara, Gilles Roux, Trausti Thormundsson, Joseph Antognini
Dynamic Switch Layers For Unsupervised Learning
Initial Submission
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
On-device machine learning (ODML) enables intelligent applications on resource-constrained devices. However, power consumption poses a major challenge, forcing a trade-off between model accuracy and power efficiency that often limits model complexity. The previously established Gated Compression (GC) layers offer a s...
[ { "created": "Fri, 5 Apr 2024 21:03:11 GMT", "version": "v1" } ]
2024-04-09
[ [ "Li", "Haiguang", "" ], [ "Pervaiz", "Usama", "" ], [ "Matuszak", "Michał", "" ], [ "Kamara", "Robert", "" ], [ "Roux", "Gilles", "" ], [ "Thormundsson", "Trausti", "" ], [ "Antognini", "Joseph", "" ] ]
On-device machine learning (ODML) enables intelligent applications on resource-constrained devices. However, power consumption poses a major challenge, forcing a trade-off between model accuracy and power efficiency that often limits model complexity. The previously established Gated Compression (GC) layers offer a sol...
2406.08188
Bruno Roy
Bruno Roy
Attention-Based Learning for Fluid State Interpolation and Editing in a Time-Continuous Framework
5 pages, 3 figures, submitted and accepted to SIGGRAPH
null
10.1145/3641234.3671085
null
cs.LG cs.GR
http://creativecommons.org/licenses/by-nc-nd/4.0/
In this work, we introduce FluidsFormer: a transformer-based approach for fluid interpolation within a continuous-time framework. By combining the capabilities of PITT and a residual neural network (RNN), we analytically predict the physical properties of the fluid state. This enables us to interpolate substep frames...
[ { "created": "Wed, 12 Jun 2024 13:19:42 GMT", "version": "v1" } ]
2024-06-13
[ [ "Roy", "Bruno", "" ] ]
In this work, we introduce FluidsFormer: a transformer-based approach for fluid interpolation within a continuous-time framework. By combining the capabilities of PITT and a residual neural network (RNN), we analytically predict the physical properties of the fluid state. This enables us to interpolate substep frames b...
2310.08659
Yixiao Li
Yixiao Li, Yifan Yu, Chen Liang, Pengcheng He, Nikos Karampatziakis, Weizhu Chen, Tuo Zhao
LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models
null
null
null
null
cs.CL cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Quantization is an indispensable technique for serving Large Language Models (LLMs) and has recently found its way into LoRA fine-tuning. In this work we focus on the scenario where quantization and LoRA fine-tuning are applied together on a pre-trained model. In such cases it is common to observe a consistent gap in...
[ { "created": "Thu, 12 Oct 2023 18:34:08 GMT", "version": "v1" }, { "created": "Tue, 17 Oct 2023 01:35:10 GMT", "version": "v2" }, { "created": "Mon, 23 Oct 2023 02:49:42 GMT", "version": "v3" }, { "created": "Tue, 28 Nov 2023 16:06:59 GMT", "version": "v4" } ]
2023-11-29
[ [ "Li", "Yixiao", "" ], [ "Yu", "Yifan", "" ], [ "Liang", "Chen", "" ], [ "He", "Pengcheng", "" ], [ "Karampatziakis", "Nikos", "" ], [ "Chen", "Weizhu", "" ], [ "Zhao", "Tuo", "" ] ]
Quantization is an indispensable technique for serving Large Language Models (LLMs) and has recently found its way into LoRA fine-tuning. In this work we focus on the scenario where quantization and LoRA fine-tuning are applied together on a pre-trained model. In such cases it is common to observe a consistent gap in t...
2208.13714
Qingsong Yan
Qingsong Yan, Qiang Wang, Kaiyong Zhao, Bo Li, Xiaowen Chu, Fei Deng
SphereDepth: Panorama Depth Estimation from Spherical Domain
Conference accept at 3DV 2022
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The panorama image can simultaneously demonstrate complete information of the surrounding environment and has many advantages in virtual tourism, games, robotics, etc. However, the progress of panorama depth estimation cannot completely solve the problems of distortion and discontinuity caused by the commonly used pr...
[ { "created": "Mon, 29 Aug 2022 16:50:19 GMT", "version": "v1" }, { "created": "Tue, 30 Aug 2022 03:01:52 GMT", "version": "v2" }, { "created": "Sun, 4 Dec 2022 16:51:00 GMT", "version": "v3" } ]
2022-12-06
[ [ "Yan", "Qingsong", "" ], [ "Wang", "Qiang", "" ], [ "Zhao", "Kaiyong", "" ], [ "Li", "Bo", "" ], [ "Chu", "Xiaowen", "" ], [ "Deng", "Fei", "" ] ]
The panorama image can simultaneously demonstrate complete information of the surrounding environment and has many advantages in virtual tourism, games, robotics, etc. However, the progress of panorama depth estimation cannot completely solve the problems of distortion and discontinuity caused by the commonly used proj...
2312.03897
Tiago Pimentel
Tiago Pimentel, Clara Meister, Ethan Gotlieb Wilcox, Kyle Mahowald, Ryan Cotterell
Revisiting the Optimality of Word Lengths
Published at EMNLP 2023
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Zipf (1935) posited that wordforms are optimized to minimize utterances' communicative costs. Under the assumption that cost is given by an utterance's length, he supported this claim by showing that words' lengths are inversely correlated with their frequencies. Communicative cost, however, can be operationalized in...
[ { "created": "Wed, 6 Dec 2023 20:41:47 GMT", "version": "v1" } ]
2023-12-08
[ [ "Pimentel", "Tiago", "" ], [ "Meister", "Clara", "" ], [ "Wilcox", "Ethan Gotlieb", "" ], [ "Mahowald", "Kyle", "" ], [ "Cotterell", "Ryan", "" ] ]
Zipf (1935) posited that wordforms are optimized to minimize utterances' communicative costs. Under the assumption that cost is given by an utterance's length, he supported this claim by showing that words' lengths are inversely correlated with their frequencies. Communicative cost, however, can be operationalized in d...
2202.04696
Amir Masoud Jafarpisheh
Amir Masoud Jafarpisheh, Mahtab Mirmohseni, and Mohammad Ali Maddah-Ali
Distributed Attribute-based Private Access Control
null
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In attribute-based access control, users with certain verified attributes will gain access to some particular data. Concerning with privacy of the users' attributes, we study the problem of distributed attribute-based private access control (DAPAC) with multiple authorities, where each authority will learn and verify...
[ { "created": "Wed, 9 Feb 2022 19:44:53 GMT", "version": "v1" } ]
2022-02-11
[ [ "Jafarpisheh", "Amir Masoud", "" ], [ "Mirmohseni", "Mahtab", "" ], [ "Maddah-Ali", "Mohammad Ali", "" ] ]
In attribute-based access control, users with certain verified attributes will gain access to some particular data. Concerning with privacy of the users' attributes, we study the problem of distributed attribute-based private access control (DAPAC) with multiple authorities, where each authority will learn and verify o...
2104.07414
AnChen Li
Anchen Li, Bo Yang, Hongxu Chen, Guandong Xu
Hyperbolic Neural Collaborative Recommender
arXiv admin note: substantial text overlap with arXiv:2102.09389
null
null
null
cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper explores the use of hyperbolic geometry and deep learning techniques for recommendation. We present Hyperbolic Neural Collaborative Recommender (HNCR), a deep hyperbolic representation learning method that exploits mutual semantic relations among users/items for collaborative filtering (CF) tasks. HNCR con...
[ { "created": "Thu, 15 Apr 2021 12:28:09 GMT", "version": "v1" } ]
2021-04-16
[ [ "Li", "Anchen", "" ], [ "Yang", "Bo", "" ], [ "Chen", "Hongxu", "" ], [ "Xu", "Guandong", "" ] ]
This paper explores the use of hyperbolic geometry and deep learning techniques for recommendation. We present Hyperbolic Neural Collaborative Recommender (HNCR), a deep hyperbolic representation learning method that exploits mutual semantic relations among users/items for collaborative filtering (CF) tasks. HNCR conta...
2404.15882
Eunsu Baek
Eunsu Baek, Keondo Park, Jiyoon Kim and Hyung-Sin Kim
Unexplored Faces of Robustness and Out-of-Distribution: Covariate Shifts in Environment and Sensor Domains
Published as a conference paper at CVPR 2024
null
null
null
cs.CV cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Computer vision applications predict on digital images acquired by a camera from physical scenes through light. However, conventional robustness benchmarks rely on perturbations in digitized images, diverging from distribution shifts occurring in the image acquisition process. To bridge this gap, we introduce a new d...
[ { "created": "Wed, 24 Apr 2024 13:59:19 GMT", "version": "v1" }, { "created": "Thu, 25 Apr 2024 05:38:52 GMT", "version": "v2" } ]
2024-04-26
[ [ "Baek", "Eunsu", "" ], [ "Park", "Keondo", "" ], [ "Kim", "Jiyoon", "" ], [ "Kim", "Hyung-Sin", "" ] ]
Computer vision applications predict on digital images acquired by a camera from physical scenes through light. However, conventional robustness benchmarks rely on perturbations in digitized images, diverging from distribution shifts occurring in the image acquisition process. To bridge this gap, we introduce a new dis...
2304.05368
Yun Zhao
Yuqing Wang, Yun Zhao, Linda Petzold
Are Large Language Models Ready for Healthcare? A Comparative Study on Clinical Language Understanding
24 pages
Machine Learning for Healthcare Conference, PMLR, 2023
null
null
cs.CL cs.AI
http://creativecommons.org/licenses/by-nc-sa/4.0/
Large language models (LLMs) have made significant progress in various domains, including healthcare. However, the specialized nature of clinical language understanding tasks presents unique challenges and limitations that warrant further investigation. In this study, we conduct a comprehensive evaluation of state-of...
[ { "created": "Sun, 9 Apr 2023 16:31:47 GMT", "version": "v1" }, { "created": "Thu, 13 Apr 2023 05:32:44 GMT", "version": "v2" }, { "created": "Sun, 30 Jul 2023 19:09:02 GMT", "version": "v3" } ]
2023-08-01
[ [ "Wang", "Yuqing", "" ], [ "Zhao", "Yun", "" ], [ "Petzold", "Linda", "" ] ]
Large language models (LLMs) have made significant progress in various domains, including healthcare. However, the specialized nature of clinical language understanding tasks presents unique challenges and limitations that warrant further investigation. In this study, we conduct a comprehensive evaluation of state-of-t...
1901.03728
Valsamis Ntouskos
Fiora Pirri, Lorenzo Mauro, Edoardo Alati, Valsamis Ntouskos, Mahdieh Izadpanahkakhk, Elham Omrani
Anticipation and next action forecasting in video: an end-to-end model with memory
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Action anticipation and forecasting in videos do not require a hat-trick, as far as there are signs in the context to foresee how actions are going to be deployed. Capturing these signs is hard because the context includes the past. We propose an end-to-end network for action anticipation and forecasting with memory,...
[ { "created": "Fri, 11 Jan 2019 19:47:53 GMT", "version": "v1" } ]
2019-01-15
[ [ "Pirri", "Fiora", "" ], [ "Mauro", "Lorenzo", "" ], [ "Alati", "Edoardo", "" ], [ "Ntouskos", "Valsamis", "" ], [ "Izadpanahkakhk", "Mahdieh", "" ], [ "Omrani", "Elham", "" ] ]
Action anticipation and forecasting in videos do not require a hat-trick, as far as there are signs in the context to foresee how actions are going to be deployed. Capturing these signs is hard because the context includes the past. We propose an end-to-end network for action anticipation and forecasting with memory, t...
2405.16494
Hao Hao
Hao Hao, Xiaoqun Zhang, Bingdong Li and Aimin Zhou
A First Look at Kolmogorov-Arnold Networks in Surrogate-assisted Evolutionary Algorithms
null
null
null
null
cs.NE
http://creativecommons.org/licenses/by/4.0/
Surrogate-assisted Evolutionary Algorithm (SAEA) is an essential method for solving expensive expensive problems. Utilizing surrogate models to substitute the optimization function can significantly reduce reliance on the function evaluations during the search process, thereby lowering the optimization costs. The con...
[ { "created": "Sun, 26 May 2024 09:12:44 GMT", "version": "v1" } ]
2024-05-28
[ [ "Hao", "Hao", "" ], [ "Zhang", "Xiaoqun", "" ], [ "Li", "Bingdong", "" ], [ "Zhou", "Aimin", "" ] ]
Surrogate-assisted Evolutionary Algorithm (SAEA) is an essential method for solving expensive expensive problems. Utilizing surrogate models to substitute the optimization function can significantly reduce reliance on the function evaluations during the search process, thereby lowering the optimization costs. The const...
1810.03611
Marc-Etienne Brunet
Marc-Etienne Brunet, Colleen Alkalay-Houlihan, Ashton Anderson, Richard Zemel
Understanding the Origins of Bias in Word Embeddings
null
null
null
null
cs.LG cs.CY stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The power of machine learning systems not only promises great technical progress, but risks societal harm. As a recent example, researchers have shown that popular word embedding algorithms exhibit stereotypical biases, such as gender bias. The widespread use of these algorithms in machine learning systems, from auto...
[ { "created": "Mon, 8 Oct 2018 18:00:00 GMT", "version": "v1" }, { "created": "Fri, 7 Jun 2019 18:26:54 GMT", "version": "v2" } ]
2019-06-11
[ [ "Brunet", "Marc-Etienne", "" ], [ "Alkalay-Houlihan", "Colleen", "" ], [ "Anderson", "Ashton", "" ], [ "Zemel", "Richard", "" ] ]
The power of machine learning systems not only promises great technical progress, but risks societal harm. As a recent example, researchers have shown that popular word embedding algorithms exhibit stereotypical biases, such as gender bias. The widespread use of these algorithms in machine learning systems, from automa...
1601.01597
Jonathan S Turner
Jonathan Turner
Grafalgo - A Library of Graph Algorithms and Supporting Data Structures (revised)
null
null
null
WUCSE-2016-01
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This report provides an (updated) overview of {\sl Grafalgo}, an open-source library of graph algorithms and the data structures used to implement them. The programs in this library were originally written to support a graduate class in advanced data structures and algorithms at Washington University. Because the cod...
[ { "created": "Thu, 7 Jan 2016 16:57:17 GMT", "version": "v1" } ]
2016-01-08
[ [ "Turner", "Jonathan", "" ] ]
This report provides an (updated) overview of {\sl Grafalgo}, an open-source library of graph algorithms and the data structures used to implement them. The programs in this library were originally written to support a graduate class in advanced data structures and algorithms at Washington University. Because the code'...
0911.4329
Ki-Hoon Lee
Ki-Hoon Lee, Kyu-Young Whang, Wook-Shin Han, and Min-Soo Kim
Structural Consistency: Enabling XML Keyword Search to Eliminate Spurious Results Consistently
null
null
null
null
cs.DB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
XML keyword search is a user-friendly way to query XML data using only keywords. In XML keyword search, to achieve high precision without sacrificing recall, it is important to remove spurious results not intended by the user. Efforts to eliminate spurious results have enjoyed some success by using the concepts of LC...
[ { "created": "Mon, 23 Nov 2009 06:45:37 GMT", "version": "v1" }, { "created": "Tue, 24 Nov 2009 01:00:10 GMT", "version": "v2" } ]
2009-11-24
[ [ "Lee", "Ki-Hoon", "" ], [ "Whang", "Kyu-Young", "" ], [ "Han", "Wook-Shin", "" ], [ "Kim", "Min-Soo", "" ] ]
XML keyword search is a user-friendly way to query XML data using only keywords. In XML keyword search, to achieve high precision without sacrificing recall, it is important to remove spurious results not intended by the user. Efforts to eliminate spurious results have enjoyed some success by using the concepts of LCA ...
2303.15663
Ankita Agarwal
Ankita Agarwal (1), Tanvi Banerjee (1), Joy Gockel (2), Saniya LeBlanc (3), Joe Walker (4), John Middendorf (4) ((1) Wright State University, (2) Colorado School of Mines, (3) The George Washington University, (4) Open Additive, LLC)
Predicting Thermoelectric Power Factor of Bismuth Telluride During Laser Powder Bed Fusion Additive Manufacturing
8 pages, 2 figures, 2 tables, accepted at Data Science for Smart Manufacturing and Healthcare workshop (DS2-MH) at SIAM International Conference on Data Mining (SDM23) conference
null
null
null
cs.LG cs.CE
http://creativecommons.org/licenses/by/4.0/
An additive manufacturing (AM) process, like laser powder bed fusion, allows for the fabrication of objects by spreading and melting powder in layers until a freeform part shape is created. In order to improve the properties of the material involved in the AM process, it is important to predict the material character...
[ { "created": "Tue, 28 Mar 2023 01:09:15 GMT", "version": "v1" } ]
2023-03-29
[ [ "Agarwal", "Ankita", "" ], [ "Banerjee", "Tanvi", "" ], [ "Gockel", "Joy", "" ], [ "LeBlanc", "Saniya", "" ], [ "Walker", "Joe", "" ], [ "Middendorf", "John", "" ] ]
An additive manufacturing (AM) process, like laser powder bed fusion, allows for the fabrication of objects by spreading and melting powder in layers until a freeform part shape is created. In order to improve the properties of the material involved in the AM process, it is important to predict the material characteriz...
2103.12195
Shayan Zargari
Shayan Zargari, Ata Khalili, Qingqing Wu, Mohammad Robat Mili, and Derrick Wing Kwan Ng
Max-Min Fair Energy-Efficient Beamforming Design for Intelligent Reflecting Surface-Aided SWIPT Systems with Non-linear Energy Harvesting Model
Minor Revision by IEEE TVT
null
null
null
cs.IT eess.SP math.IT
http://creativecommons.org/licenses/by-nc-sa/4.0/
This paper considers an intelligent reflecting sur-face (IRS)-aided simultaneous wireless information and power transfer (SWIPT) network, where multiple users decode data and harvest energy from the transmitted signal of a transmit-ter. The proposed design framework exploits the cost-effective IRS to establish favora...
[ { "created": "Mon, 22 Mar 2021 21:57:51 GMT", "version": "v1" } ]
2021-03-24
[ [ "Zargari", "Shayan", "" ], [ "Khalili", "Ata", "" ], [ "Wu", "Qingqing", "" ], [ "Mili", "Mohammad Robat", "" ], [ "Ng", "Derrick Wing Kwan", "" ] ]
This paper considers an intelligent reflecting sur-face (IRS)-aided simultaneous wireless information and power transfer (SWIPT) network, where multiple users decode data and harvest energy from the transmitted signal of a transmit-ter. The proposed design framework exploits the cost-effective IRS to establish favorabl...
2406.03793
Yue Xu
Yue Xu, Zhilin Lin, Yusong Qiu, Cewu Lu, Yong-Lu Li
Low-Rank Similarity Mining for Multimodal Dataset Distillation
Accepted at ICML 2024
null
null
null
cs.LG cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Though dataset distillation has witnessed rapid development in recent years, the distillation of multimodal data, e.g., image-text pairs, poses unique and under-explored challenges. Unlike unimodal data, image-text contrastive learning (ITC) data lack inherent categorization and should instead place greater emphasis ...
[ { "created": "Thu, 6 Jun 2024 07:05:20 GMT", "version": "v1" } ]
2024-06-07
[ [ "Xu", "Yue", "" ], [ "Lin", "Zhilin", "" ], [ "Qiu", "Yusong", "" ], [ "Lu", "Cewu", "" ], [ "Li", "Yong-Lu", "" ] ]
Though dataset distillation has witnessed rapid development in recent years, the distillation of multimodal data, e.g., image-text pairs, poses unique and under-explored challenges. Unlike unimodal data, image-text contrastive learning (ITC) data lack inherent categorization and should instead place greater emphasis on...
1907.05231
Shuai Ma
Shuai Ma and Jia Yuan Yu
Variance-Based Risk Estimations in Markov Processes via Transformation with State Lumping
7 pages, 7 figures, SMC 2019 accepted. arXiv admin note: text overlap with arXiv:1907.04269
null
null
null
cs.LG cs.AI stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Variance plays a crucial role in risk-sensitive reinforcement learning, and most risk measures can be analyzed via variance. In this paper, we consider two law-invariant risks as examples: mean-variance risk and exponential utility risk. With the aid of the state-augmentation transformation (SAT), we show that, the t...
[ { "created": "Tue, 9 Jul 2019 16:04:33 GMT", "version": "v1" } ]
2019-07-12
[ [ "Ma", "Shuai", "" ], [ "Yu", "Jia Yuan", "" ] ]
Variance plays a crucial role in risk-sensitive reinforcement learning, and most risk measures can be analyzed via variance. In this paper, we consider two law-invariant risks as examples: mean-variance risk and exponential utility risk. With the aid of the state-augmentation transformation (SAT), we show that, the two...
2406.14442
Elisa G\'omez De Lope
Elisa G\'omez de Lope, Saurabh Deshpande, Ram\'on Vi\~nas Torn\'e, Pietro Li\`o, Enrico Glaab (on behalf of the NCER-PD consortium) and St\'ephane P. A. Bordas
Graph Representation Learning Strategies for Omics Data: A Case Study on Parkinson's Disease
Submitted to Machine Learning in Computational Biology 2024 as an extended abstract, 2 pages + 1 appendix
null
null
null
cs.LG cs.AI cs.CE q-bio.BM q-bio.MN
http://creativecommons.org/licenses/by-nc-nd/4.0/
Omics data analysis is crucial for studying complex diseases, but its high dimensionality and heterogeneity challenge classical statistical and machine learning methods. Graph neural networks have emerged as promising alternatives, yet the optimal strategies for their design and optimization in real-world biomedical ...
[ { "created": "Thu, 20 Jun 2024 16:06:39 GMT", "version": "v1" } ]
2024-06-24
[ [ "de Lope", "Elisa Gómez", "", "on behalf of the NCER-PD consortium" ], [ "Deshpande", "Saurabh", "", "on behalf of the NCER-PD consortium" ], [ "Torné", "Ramón Viñas", "", "on behalf of the NCER-PD consortium" ], [ "Liò", "Pietro", "", "o...
Omics data analysis is crucial for studying complex diseases, but its high dimensionality and heterogeneity challenge classical statistical and machine learning methods. Graph neural networks have emerged as promising alternatives, yet the optimal strategies for their design and optimization in real-world biomedical ch...
2106.02435
Shaokun Zhang
Shaokun Zhang, Xiawu Zheng, Chenyi Yang, Yuchao Li, Yan Wang, Fei Chao, Mengdi Wang, Shen Li, Jun Yang, Rongrong Ji
You Only Compress Once: Towards Effective and Elastic BERT Compression via Exploit-Explore Stochastic Nature Gradient
12 pages, 3 figures
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
Despite superior performance on various natural language processing tasks, pre-trained models such as BERT are challenged by deploying on resource-constraint devices. Most existing model compression approaches require re-compression or fine-tuning across diverse constraints to accommodate various hardware deployments...
[ { "created": "Fri, 4 Jun 2021 12:17:44 GMT", "version": "v1" } ]
2021-06-07
[ [ "Zhang", "Shaokun", "" ], [ "Zheng", "Xiawu", "" ], [ "Yang", "Chenyi", "" ], [ "Li", "Yuchao", "" ], [ "Wang", "Yan", "" ], [ "Chao", "Fei", "" ], [ "Wang", "Mengdi", "" ], [ "Li", "Shen", ...
Despite superior performance on various natural language processing tasks, pre-trained models such as BERT are challenged by deploying on resource-constraint devices. Most existing model compression approaches require re-compression or fine-tuning across diverse constraints to accommodate various hardware deployments. ...
1410.1639
Yichen Jiang
Yichen Jiang, Yi Ji, Tianhua Liu
An Anonymous Communication Scheme based on Ring Signature in VANETs
null
null
null
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Vehicular ad hoc networks allow vehicles to connect themselves as networks so that cars could communicate with each other. This paper introduces an anonymous communication scheme providing integrity protection, multi-level privacy and auditability. The scheme is based on a certificateless ring signature proposed in t...
[ { "created": "Tue, 7 Oct 2014 08:31:34 GMT", "version": "v1" } ]
2014-10-08
[ [ "Jiang", "Yichen", "" ], [ "Ji", "Yi", "" ], [ "Liu", "Tianhua", "" ] ]
Vehicular ad hoc networks allow vehicles to connect themselves as networks so that cars could communicate with each other. This paper introduces an anonymous communication scheme providing integrity protection, multi-level privacy and auditability. The scheme is based on a certificateless ring signature proposed in thi...
2311.07822
Pei Zhang
Pei Zhang, Zhaobo Hua, Jinliang Ding
A Central Motor System Inspired Pre-training Reinforcement Learning for Robotic Control
null
null
null
null
cs.RO cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Designing controllers to achieve natural motor capabilities for multi-joint robots is a significant challenge. However, animals in nature are naturally with basic motor abilities and can master various complex motor skills through acquired learning. On the basis of analyzing the mechanism of the central motor system ...
[ { "created": "Tue, 14 Nov 2023 00:49:12 GMT", "version": "v1" }, { "created": "Tue, 5 Dec 2023 00:47:30 GMT", "version": "v2" }, { "created": "Tue, 16 Jul 2024 06:57:18 GMT", "version": "v3" } ]
2024-07-17
[ [ "Zhang", "Pei", "" ], [ "Hua", "Zhaobo", "" ], [ "Ding", "Jinliang", "" ] ]
Designing controllers to achieve natural motor capabilities for multi-joint robots is a significant challenge. However, animals in nature are naturally with basic motor abilities and can master various complex motor skills through acquired learning. On the basis of analyzing the mechanism of the central motor system in...
2008.06069
Changjae Oh
Ali Shahin Shamsabadi, Changjae Oh, Andrea Cavallaro
Semantically Adversarial Learnable Filters
13 pages
IEEE Transactions on Image Processing, 2021
10.1109/TIP.2021.3112290
null
cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present an adversarial framework to craft perturbations that mislead classifiers by accounting for the image content and the semantics of the labels. The proposed framework combines a structure loss and a semantic adversarial loss in a multi-task objective function to train a fully convolutional neural network. Th...
[ { "created": "Thu, 13 Aug 2020 18:12:40 GMT", "version": "v1" }, { "created": "Sun, 2 May 2021 18:12:06 GMT", "version": "v2" }, { "created": "Tue, 5 Apr 2022 21:03:21 GMT", "version": "v3" } ]
2022-04-07
[ [ "Shamsabadi", "Ali Shahin", "" ], [ "Oh", "Changjae", "" ], [ "Cavallaro", "Andrea", "" ] ]
We present an adversarial framework to craft perturbations that mislead classifiers by accounting for the image content and the semantics of the labels. The proposed framework combines a structure loss and a semantic adversarial loss in a multi-task objective function to train a fully convolutional neural network. The ...
2307.09819
Dimitrios Panteleimon Giakatos
Ilias Dimitriadis, Dimitrios P. Giakatos, Stelios Karamanidis, Pavlos Sermpezis, Kelly Kiki, Athena Vakali
Analyzing large scale political discussions on Twitter: the use case of the Greek wiretapping scandal (#ypoklopes)
null
null
null
null
cs.SI
http://creativecommons.org/licenses/by-nc-sa/4.0/
In this paper, we study the Greek wiretappings scandal, which has been revealed in 2022 and attracted a lot of attention by press and citizens. Specifically, we propose a methodology for collecting data and analyzing patterns of online public discussions on Twitter. We apply our methodology to the Greek wiretappings ...
[ { "created": "Wed, 19 Jul 2023 08:08:00 GMT", "version": "v1" } ]
2023-07-20
[ [ "Dimitriadis", "Ilias", "" ], [ "Giakatos", "Dimitrios P.", "" ], [ "Karamanidis", "Stelios", "" ], [ "Sermpezis", "Pavlos", "" ], [ "Kiki", "Kelly", "" ], [ "Vakali", "Athena", "" ] ]
In this paper, we study the Greek wiretappings scandal, which has been revealed in 2022 and attracted a lot of attention by press and citizens. Specifically, we propose a methodology for collecting data and analyzing patterns of online public discussions on Twitter. We apply our methodology to the Greek wiretappings us...
2312.03806
Xuanchi Ren
Xuanchi Ren, Jiahui Huang, Xiaohui Zeng, Ken Museth, Sanja Fidler, Francis Williams
XCube: Large-Scale 3D Generative Modeling using Sparse Voxel Hierarchies
CVPR 2024 Highlight. Code: https://github.com/nv-tlabs/XCube/ Website: https://research.nvidia.com/labs/toronto-ai/xcube/
null
null
null
cs.CV cs.GR cs.LG
http://creativecommons.org/licenses/by/4.0/
We present XCube (abbreviated as $\mathcal{X}^3$), a novel generative model for high-resolution sparse 3D voxel grids with arbitrary attributes. Our model can generate millions of voxels with a finest effective resolution of up to $1024^3$ in a feed-forward fashion without time-consuming test-time optimization. To ac...
[ { "created": "Wed, 6 Dec 2023 16:23:26 GMT", "version": "v1" }, { "created": "Tue, 25 Jun 2024 17:01:54 GMT", "version": "v2" } ]
2024-06-26
[ [ "Ren", "Xuanchi", "" ], [ "Huang", "Jiahui", "" ], [ "Zeng", "Xiaohui", "" ], [ "Museth", "Ken", "" ], [ "Fidler", "Sanja", "" ], [ "Williams", "Francis", "" ] ]
We present XCube (abbreviated as $\mathcal{X}^3$), a novel generative model for high-resolution sparse 3D voxel grids with arbitrary attributes. Our model can generate millions of voxels with a finest effective resolution of up to $1024^3$ in a feed-forward fashion without time-consuming test-time optimization. To achi...
2207.09564
Thomas G Kelly
Thomas G. Kelly, Mohammad Divband Soorati, Klaus-Peter Zauner, Sarvapali D. Ramchurn, Danesh Tarapore
Collective Decision Making in Communication-Constrained Environments
6 pages, 7 figures, accepted to the 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2022)
null
null
null
cs.RO cs.MA
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
One of the main tasks for autonomous robot swarms is to collectively decide on the best available option. Achieving that requires a high quality communication between the agents that may not be always available in a real world environment. In this paper we introduce the communication-constrained collective decision-m...
[ { "created": "Tue, 19 Jul 2022 21:48:15 GMT", "version": "v1" } ]
2022-07-21
[ [ "Kelly", "Thomas G.", "" ], [ "Soorati", "Mohammad Divband", "" ], [ "Zauner", "Klaus-Peter", "" ], [ "Ramchurn", "Sarvapali D.", "" ], [ "Tarapore", "Danesh", "" ] ]
One of the main tasks for autonomous robot swarms is to collectively decide on the best available option. Achieving that requires a high quality communication between the agents that may not be always available in a real world environment. In this paper we introduce the communication-constrained collective decision-mak...
1705.04839
Firoj Alam
Firoj Alam, Morena Danieli and Giuseppe Riccardi
Annotating and Modeling Empathy in Spoken Conversations
Journal of Computer Speech and Language
null
10.1016/j.csl.2017.12.003
null
cs.CL
http://creativecommons.org/licenses/by-nc-sa/4.0/
Empathy, as defined in behavioral sciences, expresses the ability of human beings to recognize, understand and react to emotions, attitudes and beliefs of others. The lack of an operational definition of empathy makes it difficult to measure it. In this paper, we address two related problems in automatic affective be...
[ { "created": "Sat, 13 May 2017 14:49:08 GMT", "version": "v1" }, { "created": "Thu, 21 Dec 2017 20:13:29 GMT", "version": "v2" }, { "created": "Fri, 29 Dec 2017 12:52:49 GMT", "version": "v3" } ]
2018-01-01
[ [ "Alam", "Firoj", "" ], [ "Danieli", "Morena", "" ], [ "Riccardi", "Giuseppe", "" ] ]
Empathy, as defined in behavioral sciences, expresses the ability of human beings to recognize, understand and react to emotions, attitudes and beliefs of others. The lack of an operational definition of empathy makes it difficult to measure it. In this paper, we address two related problems in automatic affective beha...
1707.06307
Vincent Knight Dr
Marc Harper and Vincent Knight and Martin Jones and Georgios Koutsovoulos and Nikoleta E. Glynatsi and Owen Campbell
Reinforcement Learning Produces Dominant Strategies for the Iterated Prisoner's Dilemma
null
null
10.1371/journal.pone.0188046
null
cs.GT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present tournament results and several powerful strategies for the Iterated Prisoner's Dilemma created using reinforcement learning techniques (evolutionary and particle swarm algorithms). These strategies are trained to perform well against a corpus of over 170 distinct opponents, including many well-known and cl...
[ { "created": "Wed, 19 Jul 2017 21:47:19 GMT", "version": "v1" } ]
2018-02-07
[ [ "Harper", "Marc", "" ], [ "Knight", "Vincent", "" ], [ "Jones", "Martin", "" ], [ "Koutsovoulos", "Georgios", "" ], [ "Glynatsi", "Nikoleta E.", "" ], [ "Campbell", "Owen", "" ] ]
We present tournament results and several powerful strategies for the Iterated Prisoner's Dilemma created using reinforcement learning techniques (evolutionary and particle swarm algorithms). These strategies are trained to perform well against a corpus of over 170 distinct opponents, including many well-known and clas...
2312.01151
Zilong Liu
Zilong Liu, Krzysztof Janowicz, Kitty Currier, Meilin Shi, Jinmeng Rao, Song Gao, Ling Cai, and Anita Graser
Here Is Not There: Measuring Entailment-Based Trajectory Similarity for Location-Privacy Protection and Beyond
null
null
10.5281/zenodo.8286277
null
cs.CY cs.CL cs.SC
http://creativecommons.org/licenses/by/4.0/
While the paths humans take play out in social as well as physical space, measures to describe and compare their trajectories are carried out in abstract, typically Euclidean, space. When these measures are applied to trajectories of actual individuals in an application area, alterations that are inconsequential in a...
[ { "created": "Sat, 2 Dec 2023 14:41:01 GMT", "version": "v1" } ]
2023-12-05
[ [ "Liu", "Zilong", "" ], [ "Janowicz", "Krzysztof", "" ], [ "Currier", "Kitty", "" ], [ "Shi", "Meilin", "" ], [ "Rao", "Jinmeng", "" ], [ "Gao", "Song", "" ], [ "Cai", "Ling", "" ], [ "Graser", "...
While the paths humans take play out in social as well as physical space, measures to describe and compare their trajectories are carried out in abstract, typically Euclidean, space. When these measures are applied to trajectories of actual individuals in an application area, alterations that are inconsequential in abs...
2309.13907
Dake Guo
Dake Guo, Xinfa Zhu, Liumeng Xue, Tao Li, Yuanjun Lv, Yuepeng Jiang, Lei Xie
HiGNN-TTS: Hierarchical Prosody Modeling with Graph Neural Networks for Expressive Long-form TTS
Accepted by ASRU2023
null
null
null
cs.SD eess.AS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recent advances in text-to-speech, particularly those based on Graph Neural Networks (GNNs), have significantly improved the expressiveness of short-form synthetic speech. However, generating human-parity long-form speech with high dynamic prosodic variations is still challenging. To address this problem, we expand t...
[ { "created": "Mon, 25 Sep 2023 07:07:02 GMT", "version": "v1" }, { "created": "Sat, 7 Oct 2023 01:56:04 GMT", "version": "v2" } ]
2023-10-10
[ [ "Guo", "Dake", "" ], [ "Zhu", "Xinfa", "" ], [ "Xue", "Liumeng", "" ], [ "Li", "Tao", "" ], [ "Lv", "Yuanjun", "" ], [ "Jiang", "Yuepeng", "" ], [ "Xie", "Lei", "" ] ]
Recent advances in text-to-speech, particularly those based on Graph Neural Networks (GNNs), have significantly improved the expressiveness of short-form synthetic speech. However, generating human-parity long-form speech with high dynamic prosodic variations is still challenging. To address this problem, we expand the...
2312.04183
Amin Radbord
Amin Radbord, Italo Atzeni, Antti Tolli
Enhanced data Detection for Massive MIMO with 1-Bit ADCs
Presented at the IEEE Asilomar Conference on Signals, Systems, and Computers 2023. arXiv admin note: text overlap with arXiv:2303.18061
null
null
null
cs.IT eess.SP math.IT
http://creativecommons.org/licenses/by/4.0/
We present new insightful results on the uplink data detection for massive multiple-input multiple-output systems with 1-bit analog-to-digital converters. The expected values of the soft-estimated symbols (i.e., after the linear combining and prior to the data detection) have been recently characterized for multiple ...
[ { "created": "Thu, 7 Dec 2023 10:11:20 GMT", "version": "v1" } ]
2023-12-08
[ [ "Radbord", "Amin", "" ], [ "Atzeni", "Italo", "" ], [ "Tolli", "Antti", "" ] ]
We present new insightful results on the uplink data detection for massive multiple-input multiple-output systems with 1-bit analog-to-digital converters. The expected values of the soft-estimated symbols (i.e., after the linear combining and prior to the data detection) have been recently characterized for multiple us...
1904.04195
Hao Tan
Hao Tan, Licheng Yu, Mohit Bansal
Learning to Navigate Unseen Environments: Back Translation with Environmental Dropout
NAACL 2019 (12 pages)
null
null
null
cs.CL cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A grand goal in AI is to build a robot that can accurately navigate based on natural language instructions, which requires the agent to perceive the scene, understand and ground language, and act in the real-world environment. One key challenge here is to learn to navigate in new environments that are unseen during t...
[ { "created": "Mon, 8 Apr 2019 17:14:52 GMT", "version": "v1" } ]
2019-04-09
[ [ "Tan", "Hao", "" ], [ "Yu", "Licheng", "" ], [ "Bansal", "Mohit", "" ] ]
A grand goal in AI is to build a robot that can accurately navigate based on natural language instructions, which requires the agent to perceive the scene, understand and ground language, and act in the real-world environment. One key challenge here is to learn to navigate in new environments that are unseen during tra...
2207.00622
Zurab Khasidashvili
Zurab Khasidashvili
Accelerating System-Level Debug Using Rule Learning and Subgroup Discovery Techniques
33 pages, 6 figures
null
null
null
cs.SE cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We propose a root-causing procedure for accelerating system-level debug using rule-based techniques. We describe the procedure and how it provides high quality debug hints for reducing the debug effort. This includes the heuristics for engineering features from logs of many tests, and the data analytics techniques fo...
[ { "created": "Sat, 2 Jul 2022 22:00:30 GMT", "version": "v1" }, { "created": "Sat, 1 Jun 2024 21:57:06 GMT", "version": "v2" } ]
2024-06-04
[ [ "Khasidashvili", "Zurab", "" ] ]
We propose a root-causing procedure for accelerating system-level debug using rule-based techniques. We describe the procedure and how it provides high quality debug hints for reducing the debug effort. This includes the heuristics for engineering features from logs of many tests, and the data analytics techniques for ...
1911.01509
Karthikeyan Natesan Ramamurthy
Moninder Singh and Karthikeyan Natesan Ramamurthy
Understanding racial bias in health using the Medical Expenditure Panel Survey data
8 pages, 8 tables
null
null
null
cs.LG cs.CY stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Over the years, several studies have demonstrated that there exist significant disparities in health indicators in the United States population across various groups. Healthcare expense is used as a proxy for health in algorithms that drive healthcare systems and this exacerbates the existing bias. In this work, we f...
[ { "created": "Mon, 4 Nov 2019 22:14:52 GMT", "version": "v1" } ]
2019-11-06
[ [ "Singh", "Moninder", "" ], [ "Ramamurthy", "Karthikeyan Natesan", "" ] ]
Over the years, several studies have demonstrated that there exist significant disparities in health indicators in the United States population across various groups. Healthcare expense is used as a proxy for health in algorithms that drive healthcare systems and this exacerbates the existing bias. In this work, we foc...