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2104.08500
Mingjian Zhu
Mingjian Zhu, Yehui Tang, Kai Han
Vision Transformer Pruning
Accepted by the KDD 2021 Workshop on Model Mining
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Vision transformer has achieved competitive performance on a variety of computer vision applications. However, their storage, run-time memory, and computational demands are hindering the deployment to mobile devices. Here we present a vision transformer pruning approach, which identifies the impacts of dimensions in ...
[ { "created": "Sat, 17 Apr 2021 09:49:24 GMT", "version": "v1" }, { "created": "Tue, 20 Apr 2021 04:50:49 GMT", "version": "v2" }, { "created": "Wed, 14 Jul 2021 06:36:01 GMT", "version": "v3" }, { "created": "Sat, 14 Aug 2021 06:06:37 GMT", "version": "v4" } ]
2021-08-17
[ [ "Zhu", "Mingjian", "" ], [ "Tang", "Yehui", "" ], [ "Han", "Kai", "" ] ]
Vision transformer has achieved competitive performance on a variety of computer vision applications. However, their storage, run-time memory, and computational demands are hindering the deployment to mobile devices. Here we present a vision transformer pruning approach, which identifies the impacts of dimensions in ea...
2111.03573
David Balash
David G. Balash (1), Xiaoyuan Wu (1), Miles Grant (1), Irwin Reyes (2), Adam J. Aviv (1) ((1) The George Washington University, (2) Two Six Technologies)
Security and Privacy Perceptions of Third-Party Application Access for Google Accounts (Extended Version)
null
null
null
null
cs.CR
http://creativecommons.org/licenses/by/4.0/
Online services like Google provide a variety of application programming interfaces (APIs). These online APIs enable authenticated third-party services and applications (apps) to access a user's account data for tasks such as single sign-on (SSO), calendar integration, and sending email on behalf of the user, among o...
[ { "created": "Fri, 5 Nov 2021 15:49:38 GMT", "version": "v1" } ]
2021-11-08
[ [ "Balash", "David G.", "" ], [ "Wu", "Xiaoyuan", "" ], [ "Grant", "Miles", "" ], [ "Reyes", "Irwin", "" ], [ "Aviv", "Adam J.", "" ] ]
Online services like Google provide a variety of application programming interfaces (APIs). These online APIs enable authenticated third-party services and applications (apps) to access a user's account data for tasks such as single sign-on (SSO), calendar integration, and sending email on behalf of the user, among oth...
2309.12029
Kailun Yang
Yifei Chen, Kunyu Peng, Alina Roitberg, David Schneider, Jiaming Zhang, Junwei Zheng, Ruiping Liu, Yufan Chen, Kailun Yang, Rainer Stiefelhagen
Unveiling the Hidden Realm: Self-supervised Skeleton-based Action Recognition in Occluded Environments
The source code will be made publicly available at https://github.com/cyfml/OPSTL
null
null
null
cs.CV cs.MM cs.RO eess.IV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
To integrate action recognition methods into autonomous robotic systems, it is crucial to consider adverse situations involving target occlusions. Such a scenario, despite its practical relevance, is rarely addressed in existing self-supervised skeleton-based action recognition methods. To empower robots with the cap...
[ { "created": "Thu, 21 Sep 2023 12:51:11 GMT", "version": "v1" } ]
2023-09-22
[ [ "Chen", "Yifei", "" ], [ "Peng", "Kunyu", "" ], [ "Roitberg", "Alina", "" ], [ "Schneider", "David", "" ], [ "Zhang", "Jiaming", "" ], [ "Zheng", "Junwei", "" ], [ "Liu", "Ruiping", "" ], [ "Chen", ...
To integrate action recognition methods into autonomous robotic systems, it is crucial to consider adverse situations involving target occlusions. Such a scenario, despite its practical relevance, is rarely addressed in existing self-supervised skeleton-based action recognition methods. To empower robots with the capac...
2102.07007
Siwen Yan
Devendra Singh Dhami (1 and 2), Siwen Yan (2), Sriraam Natarajan (2) ((1) Technical University of Darmstadt, Germany, (2) The University of Texas at Dallas, USA)
A Statistical Relational Approach to Learning Distance-based GCNs
8 pages, 5 figures, 4 tables; accepted to STARAI workshop
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We consider the problem of learning distance-based Graph Convolutional Networks (GCNs) for relational data. Specifically, we first embed the original graph into the Euclidean space $\mathbb{R}^m$ using a relational density estimation technique thereby constructing a secondary Euclidean graph. The graph vertices corre...
[ { "created": "Sat, 13 Feb 2021 21:34:44 GMT", "version": "v1" }, { "created": "Thu, 18 Feb 2021 20:03:42 GMT", "version": "v2" }, { "created": "Fri, 8 Oct 2021 23:51:59 GMT", "version": "v3" }, { "created": "Tue, 12 Oct 2021 18:56:33 GMT", "version": "v4" } ]
2021-10-14
[ [ "Dhami", "Devendra Singh", "", "1 and 2" ], [ "Yan", "Siwen", "" ], [ "Natarajan", "Sriraam", "" ] ]
We consider the problem of learning distance-based Graph Convolutional Networks (GCNs) for relational data. Specifically, we first embed the original graph into the Euclidean space $\mathbb{R}^m$ using a relational density estimation technique thereby constructing a secondary Euclidean graph. The graph vertices corresp...
1102.1502
Maxime Gariel
Maxime Gariel and Kevin Spieser and Emilio Frazzoli
On the Statistics and Predictability of Go-Arounds
10 pages, 14 figures, Submitted to USA/Europe ATM Seminar 2011
null
null
null
cs.SY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper takes an empirical approach to identify operational factors at busy airports that may predate go-around maneuvers. Using four years of data from San Francisco International Airport, we begin our investigation with a statistical approach to investigate which features of airborne, ground operations (e.g., nu...
[ { "created": "Tue, 8 Feb 2011 04:36:07 GMT", "version": "v1" } ]
2011-02-09
[ [ "Gariel", "Maxime", "" ], [ "Spieser", "Kevin", "" ], [ "Frazzoli", "Emilio", "" ] ]
This paper takes an empirical approach to identify operational factors at busy airports that may predate go-around maneuvers. Using four years of data from San Francisco International Airport, we begin our investigation with a statistical approach to investigate which features of airborne, ground operations (e.g., numb...
2404.12813
Musbah Shaat
Husnain Shahid, Miguel Angel Vazquez, Laurent Reynaud, Fanny Parzysz, Musbah Shaat
Open Datasets for AI-Enabled Radio Resource Control in Non-Terrestrial Networks
In the proceedings of IEEE Future Networks World Forum 13_15 November 2023, Baltimore, MD, USA
null
null
null
cs.NI eess.SP
http://creativecommons.org/licenses/by-nc-nd/4.0/
By effectively implementing the strategies for resource allocation, the capabilities, and reliability of non-terrestrial networks (NTN) can be enhanced. This leads to enhance spectrum utilization performance while minimizing the unmet system capacity, meeting quality of service (QoS) requirements and overall system o...
[ { "created": "Fri, 19 Apr 2024 11:48:54 GMT", "version": "v1" } ]
2024-04-22
[ [ "Shahid", "Husnain", "" ], [ "Vazquez", "Miguel Angel", "" ], [ "Reynaud", "Laurent", "" ], [ "Parzysz", "Fanny", "" ], [ "Shaat", "Musbah", "" ] ]
By effectively implementing the strategies for resource allocation, the capabilities, and reliability of non-terrestrial networks (NTN) can be enhanced. This leads to enhance spectrum utilization performance while minimizing the unmet system capacity, meeting quality of service (QoS) requirements and overall system opt...
1905.06105
Corey Lammie
Corey Lammie, Wei Xiang, and Mostafa Rahimi Azghadi
Accelerating Deterministic and Stochastic Binarized Neural Networks on FPGAs Using OpenCL
4 pages, 3 figures, 1 table
2019 IEEE International Midwest Symposium on Circuits and Systems (MWSCAS)
10.1109/MWSCAS.2019.8884910
null
cs.LG stat.ML
http://creativecommons.org/licenses/by-nc-sa/4.0/
Recent technological advances have proliferated the available computing power, memory, and speed of modern Central Processing Units (CPUs), Graphics Processing Units (GPUs), and Field Programmable Gate Arrays (FPGAs). Consequently, the performance and complexity of Artificial Neural Networks (ANNs) is burgeoning. Whi...
[ { "created": "Wed, 15 May 2019 12:04:36 GMT", "version": "v1" } ]
2021-02-18
[ [ "Lammie", "Corey", "" ], [ "Xiang", "Wei", "" ], [ "Azghadi", "Mostafa Rahimi", "" ] ]
Recent technological advances have proliferated the available computing power, memory, and speed of modern Central Processing Units (CPUs), Graphics Processing Units (GPUs), and Field Programmable Gate Arrays (FPGAs). Consequently, the performance and complexity of Artificial Neural Networks (ANNs) is burgeoning. While...
1903.07395
Nicholas Cummins Dr
Thomas Wiest, Nicholas Cummins, Alice Baird, Simone Hantke, Judith Dineley, Bj\"orn Schuller
Voice command generation using Progressive Wavegans
7 pages, 2 figures
null
null
null
cs.CL cs.LG cs.SD eess.AS stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Generative Adversarial Networks (GANs) have become exceedingly popular in a wide range of data-driven research fields, due in part to their success in image generation. Their ability to generate new samples, often from only a small amount of input data, makes them an exciting research tool in areas with limited data ...
[ { "created": "Wed, 13 Mar 2019 18:43:31 GMT", "version": "v1" } ]
2019-03-19
[ [ "Wiest", "Thomas", "" ], [ "Cummins", "Nicholas", "" ], [ "Baird", "Alice", "" ], [ "Hantke", "Simone", "" ], [ "Dineley", "Judith", "" ], [ "Schuller", "Björn", "" ] ]
Generative Adversarial Networks (GANs) have become exceedingly popular in a wide range of data-driven research fields, due in part to their success in image generation. Their ability to generate new samples, often from only a small amount of input data, makes them an exciting research tool in areas with limited data re...
1402.4867
Anke van Zuylen
Anke van Zuylen, James Bieron, Frans Schalekamp, Gexin Yu
An Upper Bound on the Number of Circular Transpositions to Sort a Permutation
null
null
null
null
cs.DM math.CO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We consider the problem of upper bounding the number of circular transpositions needed to sort a permutation. It is well known that any permutation can be sorted using at most $n(n-1)/2$ adjacent transpositions. We show that, if we allow all adjacent transpositions, as well as the transposition that interchanges the ...
[ { "created": "Thu, 20 Feb 2014 02:26:28 GMT", "version": "v1" } ]
2014-02-21
[ [ "van Zuylen", "Anke", "" ], [ "Bieron", "James", "" ], [ "Schalekamp", "Frans", "" ], [ "Yu", "Gexin", "" ] ]
We consider the problem of upper bounding the number of circular transpositions needed to sort a permutation. It is well known that any permutation can be sorted using at most $n(n-1)/2$ adjacent transpositions. We show that, if we allow all adjacent transpositions, as well as the transposition that interchanges the el...
2402.05546
Jost Tobias Springenberg
Jost Tobias Springenberg, Abbas Abdolmaleki, Jingwei Zhang, Oliver Groth, Michael Bloesch, Thomas Lampe, Philemon Brakel, Sarah Bechtle, Steven Kapturowski, Roland Hafner, Nicolas Heess, Martin Riedmiller
Offline Actor-Critic Reinforcement Learning Scales to Large Models
null
null
null
null
cs.LG cs.AI cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We show that offline actor-critic reinforcement learning can scale to large models - such as transformers - and follows similar scaling laws as supervised learning. We find that offline actor-critic algorithms can outperform strong, supervised, behavioral cloning baselines for multi-task training on a large dataset c...
[ { "created": "Thu, 8 Feb 2024 10:29:46 GMT", "version": "v1" } ]
2024-02-09
[ [ "Springenberg", "Jost Tobias", "" ], [ "Abdolmaleki", "Abbas", "" ], [ "Zhang", "Jingwei", "" ], [ "Groth", "Oliver", "" ], [ "Bloesch", "Michael", "" ], [ "Lampe", "Thomas", "" ], [ "Brakel", "Philemon", "...
We show that offline actor-critic reinforcement learning can scale to large models - such as transformers - and follows similar scaling laws as supervised learning. We find that offline actor-critic algorithms can outperform strong, supervised, behavioral cloning baselines for multi-task training on a large dataset con...
1906.06357
Ekram Hossain
Tao Zhang, Kun Zhu, and Ekram Hossain
Data-Driven Machine Learning Techniques for Self-healing in Cellular Wireless Networks: Challenges and Solutions
null
null
null
null
cs.NI cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
For enabling automatic deployment and management of cellular networks, the concept of self-organizing network (SON) was introduced. SON capabilities can enhance network performance, improve service quality, and reduce operational and capital expenditure (OPEX/CAPEX). As an important component in SON, self-healing is ...
[ { "created": "Fri, 14 Jun 2019 18:16:21 GMT", "version": "v1" } ]
2019-06-18
[ [ "Zhang", "Tao", "" ], [ "Zhu", "Kun", "" ], [ "Hossain", "Ekram", "" ] ]
For enabling automatic deployment and management of cellular networks, the concept of self-organizing network (SON) was introduced. SON capabilities can enhance network performance, improve service quality, and reduce operational and capital expenditure (OPEX/CAPEX). As an important component in SON, self-healing is de...
1911.02996
Elijah Bolluyt
Elijah D. Bolluyt, Cristina Comaniciu
Collapse Resistant Deep Convolutional GAN for Multi-Object Image Generation
Accepted to IEEE International Conference on Machine Learning and Applications 2019
null
null
null
cs.LG cs.CV eess.IV stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This work introduces a novel system for the generation of images that contain multiple classes of objects. Recent work in Generative Adversarial Networks have produced high quality images, but many focus on generating images of a single object or set of objects. Our system addresses the task of image generation condi...
[ { "created": "Fri, 8 Nov 2019 02:27:23 GMT", "version": "v1" } ]
2019-11-11
[ [ "Bolluyt", "Elijah D.", "" ], [ "Comaniciu", "Cristina", "" ] ]
This work introduces a novel system for the generation of images that contain multiple classes of objects. Recent work in Generative Adversarial Networks have produced high quality images, but many focus on generating images of a single object or set of objects. Our system addresses the task of image generation conditi...
2002.00717
Xinze Zhang
Xinze Zhang, Kun He, Yukun Bao
Error-feedback stochastic modeling strategy for time series forecasting with convolutional neural networks
null
Neurocomputing 459 (2021): 234-248
10.1016/j.neucom.2021.06.051
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Despite the superiority of convolutional neural networks demonstrated in time series modeling and forecasting, it has not been fully explored on the design of the neural network architecture and the tuning of the hyper-parameters. Inspired by the incremental construction strategy for building a random multilayer perc...
[ { "created": "Mon, 3 Feb 2020 13:30:29 GMT", "version": "v1" }, { "created": "Fri, 11 Feb 2022 14:02:34 GMT", "version": "v2" } ]
2022-02-14
[ [ "Zhang", "Xinze", "" ], [ "He", "Kun", "" ], [ "Bao", "Yukun", "" ] ]
Despite the superiority of convolutional neural networks demonstrated in time series modeling and forecasting, it has not been fully explored on the design of the neural network architecture and the tuning of the hyper-parameters. Inspired by the incremental construction strategy for building a random multilayer percep...
2109.14528
Chen Wang
Sepehr Assadi, Chen Wang
Sublinear Time and Space Algorithms for Correlation Clustering via Sparse-Dense Decompositions
null
null
null
null
cs.DS cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present a new approach for solving (minimum disagreement) correlation clustering that results in sublinear algorithms with highly efficient time and space complexity for this problem. In particular, we obtain the following algorithms for $n$-vertex $(+/-)$-labeled graphs $G$: -- A sublinear-time algorithm that w...
[ { "created": "Wed, 29 Sep 2021 16:25:02 GMT", "version": "v1" } ]
2021-09-30
[ [ "Assadi", "Sepehr", "" ], [ "Wang", "Chen", "" ] ]
We present a new approach for solving (minimum disagreement) correlation clustering that results in sublinear algorithms with highly efficient time and space complexity for this problem. In particular, we obtain the following algorithms for $n$-vertex $(+/-)$-labeled graphs $G$: -- A sublinear-time algorithm that with ...
2101.00371
Yue Dong
Yue Dong, Chandra Bhagavatula, Ximing Lu, Jena D. Hwang, Antoine Bosselut, Jackie Chi Kit Cheung, Yejin Choi
On-the-Fly Attention Modulation for Neural Generation
10 pages, 3 figures
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
Despite considerable advancements with deep neural language models (LMs), neural text generation still suffers from degeneration: the generated text is repetitive, generic, self-contradictory, and often lacks commonsense. Our analyses on sentence-level attention patterns in LMs reveal that neural degeneration may be ...
[ { "created": "Sat, 2 Jan 2021 05:16:46 GMT", "version": "v1" }, { "created": "Wed, 13 Oct 2021 19:22:36 GMT", "version": "v2" } ]
2021-10-15
[ [ "Dong", "Yue", "" ], [ "Bhagavatula", "Chandra", "" ], [ "Lu", "Ximing", "" ], [ "Hwang", "Jena D.", "" ], [ "Bosselut", "Antoine", "" ], [ "Cheung", "Jackie Chi Kit", "" ], [ "Choi", "Yejin", "" ] ]
Despite considerable advancements with deep neural language models (LMs), neural text generation still suffers from degeneration: the generated text is repetitive, generic, self-contradictory, and often lacks commonsense. Our analyses on sentence-level attention patterns in LMs reveal that neural degeneration may be as...
1507.05284
Kumar Sankar Ray
Kingshuk Chatterjee, Kumar Sankar Ray
Deterministic parallel communicating Watson-Crick automata systems
null
null
null
null
cs.FL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we have introduced the deterministic variant of parallel communicating Watson-Crick automata systems. We show that similar to the non-deterministic version, the deterministic version can also recognise some non-regular uniletter languages. We further establish that strongly deterministic Watson-Crick a...
[ { "created": "Sun, 19 Jul 2015 13:03:36 GMT", "version": "v1" } ]
2015-07-21
[ [ "Chatterjee", "Kingshuk", "" ], [ "Ray", "Kumar Sankar", "" ] ]
In this paper, we have introduced the deterministic variant of parallel communicating Watson-Crick automata systems. We show that similar to the non-deterministic version, the deterministic version can also recognise some non-regular uniletter languages. We further establish that strongly deterministic Watson-Crick aut...
2306.14848
Daniele De Martini
Luke Robinson, Daniele De Martini, Matthew Gadd, Paul Newman
Visual Servoing on Wheels: Robust Robot Orientation Estimation in Remote Viewpoint Control
Accepted at IROS 2023
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This work proposes a fast deployment pipeline for visually-servoed robots which does not assume anything about either the robot - e.g. sizes, colour or the presence of markers - or the deployment environment. In this, accurate estimation of robot orientation is crucial for successful navigation in complex environment...
[ { "created": "Mon, 26 Jun 2023 17:00:09 GMT", "version": "v1" } ]
2023-06-27
[ [ "Robinson", "Luke", "" ], [ "De Martini", "Daniele", "" ], [ "Gadd", "Matthew", "" ], [ "Newman", "Paul", "" ] ]
This work proposes a fast deployment pipeline for visually-servoed robots which does not assume anything about either the robot - e.g. sizes, colour or the presence of markers - or the deployment environment. In this, accurate estimation of robot orientation is crucial for successful navigation in complex environments;...
1106.2429
Ohad Shamir
Nicol\`o Cesa-Bianchi and Ohad Shamir
Efficient Transductive Online Learning via Randomized Rounding
To appear in a Festschrift in honor of V.N. Vapnik. Preliminary version presented in NIPS 2011
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Most traditional online learning algorithms are based on variants of mirror descent or follow-the-leader. In this paper, we present an online algorithm based on a completely different approach, tailored for transductive settings, which combines "random playout" and randomized rounding of loss subgradients. As an appl...
[ { "created": "Mon, 13 Jun 2011 12:30:05 GMT", "version": "v1" }, { "created": "Tue, 18 Oct 2011 14:22:14 GMT", "version": "v2" }, { "created": "Thu, 24 Nov 2011 05:11:33 GMT", "version": "v3" }, { "created": "Wed, 11 Sep 2013 10:55:26 GMT", "version": "v4" } ]
2013-09-12
[ [ "Cesa-Bianchi", "Nicolò", "" ], [ "Shamir", "Ohad", "" ] ]
Most traditional online learning algorithms are based on variants of mirror descent or follow-the-leader. In this paper, we present an online algorithm based on a completely different approach, tailored for transductive settings, which combines "random playout" and randomized rounding of loss subgradients. As an applic...
2405.15932
Soumyabrata Kundu
Soumyabrata Kundu and Risi Kondor
Steerable Transformers
null
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
In this work we introduce Steerable Transformers, an extension of the Vision Transformer mechanism that maintains equivariance to the special Euclidean group $\mathrm{SE}(d)$. We propose an equivariant attention mechanism that operates on features extracted by steerable convolutions. Operating in Fourier space, our n...
[ { "created": "Fri, 24 May 2024 20:43:19 GMT", "version": "v1" } ]
2024-05-28
[ [ "Kundu", "Soumyabrata", "" ], [ "Kondor", "Risi", "" ] ]
In this work we introduce Steerable Transformers, an extension of the Vision Transformer mechanism that maintains equivariance to the special Euclidean group $\mathrm{SE}(d)$. We propose an equivariant attention mechanism that operates on features extracted by steerable convolutions. Operating in Fourier space, our net...
2206.13776
Sara Rouhani Dr.
Kimia Honari, Xiaotian Zhou, Sara Rouhani, Scott Dick, Hao Liang, James Miller Li, James Miller
A Scalable Blockchain-based Smart Contract Model for Decentralized Voltage Stability Using Sharding Technique
8 pages
null
null
null
cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Blockchain technologies are one possible avenue for increasing the resilience of the Smart Grid, by decentralizing the monitoring and control of system-level objectives such as voltage stability protection. They furthermore offer benefits in data immutability and traceability, as blockchains are cryptographically sec...
[ { "created": "Tue, 28 Jun 2022 06:06:56 GMT", "version": "v1" } ]
2022-06-29
[ [ "Honari", "Kimia", "" ], [ "Zhou", "Xiaotian", "" ], [ "Rouhani", "Sara", "" ], [ "Dick", "Scott", "" ], [ "Liang", "Hao", "" ], [ "Li", "James Miller", "" ], [ "Miller", "James", "" ] ]
Blockchain technologies are one possible avenue for increasing the resilience of the Smart Grid, by decentralizing the monitoring and control of system-level objectives such as voltage stability protection. They furthermore offer benefits in data immutability and traceability, as blockchains are cryptographically secur...
2106.12790
Parul Kapoor
Parul Kapoor, Rudrabha Mukhopadhyay, Sindhu B Hegde, Vinay Namboodiri, C V Jawahar
Towards Automatic Speech to Sign Language Generation
5 pages(including references), 5 figures, Accepted in Interspeech 2021
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We aim to solve the highly challenging task of generating continuous sign language videos solely from speech segments for the first time. Recent efforts in this space have focused on generating such videos from human-annotated text transcripts without considering other modalities. However, replacing speech with sign ...
[ { "created": "Thu, 24 Jun 2021 06:44:19 GMT", "version": "v1" } ]
2021-06-25
[ [ "Kapoor", "Parul", "" ], [ "Mukhopadhyay", "Rudrabha", "" ], [ "Hegde", "Sindhu B", "" ], [ "Namboodiri", "Vinay", "" ], [ "Jawahar", "C V", "" ] ]
We aim to solve the highly challenging task of generating continuous sign language videos solely from speech segments for the first time. Recent efforts in this space have focused on generating such videos from human-annotated text transcripts without considering other modalities. However, replacing speech with sign la...
2012.03197
Liangjian Chen
Liangjian Chen, Shih-Yao Lin, Yusheng Xie, Yen-Yu Lin, Wei Fan, and Xiaohui Xie
DGGAN: Depth-image Guided Generative Adversarial Networks for Disentangling RGB and Depth Images in 3D Hand Pose Estimation
null
2020 IEEE Winter Conference on Applications of Computer Vision (WACV)
null
null
cs.CV
http://creativecommons.org/publicdomain/zero/1.0/
Estimating3D hand poses from RGB images is essentialto a wide range of potential applications, but is challengingowing to substantial ambiguity in the inference of depth in-formation from RGB images. State-of-the-art estimators ad-dress this problem by regularizing3D hand pose estimationmodels during training to enfo...
[ { "created": "Sun, 6 Dec 2020 07:23:21 GMT", "version": "v1" } ]
2020-12-08
[ [ "Chen", "Liangjian", "" ], [ "Lin", "Shih-Yao", "" ], [ "Xie", "Yusheng", "" ], [ "Lin", "Yen-Yu", "" ], [ "Fan", "Wei", "" ], [ "Xie", "Xiaohui", "" ] ]
Estimating3D hand poses from RGB images is essentialto a wide range of potential applications, but is challengingowing to substantial ambiguity in the inference of depth in-formation from RGB images. State-of-the-art estimators ad-dress this problem by regularizing3D hand pose estimationmodels during training to enforc...
2212.07469
Kwangjun Ahn
Kwangjun Ahn, S\'ebastien Bubeck, Sinho Chewi, Yin Tat Lee, Felipe Suarez, Yi Zhang
Learning threshold neurons via the "edge of stability"
31 pages, 13 figures, Published at NeurIPS 2023
null
null
null
cs.LG cs.AI math.OC
http://creativecommons.org/licenses/by/4.0/
Existing analyses of neural network training often operate under the unrealistic assumption of an extremely small learning rate. This lies in stark contrast to practical wisdom and empirical studies, such as the work of J. Cohen et al. (ICLR 2021), which exhibit startling new phenomena (the "edge of stability" or "un...
[ { "created": "Wed, 14 Dec 2022 19:27:03 GMT", "version": "v1" }, { "created": "Thu, 19 Oct 2023 12:00:54 GMT", "version": "v2" } ]
2023-10-20
[ [ "Ahn", "Kwangjun", "" ], [ "Bubeck", "Sébastien", "" ], [ "Chewi", "Sinho", "" ], [ "Lee", "Yin Tat", "" ], [ "Suarez", "Felipe", "" ], [ "Zhang", "Yi", "" ] ]
Existing analyses of neural network training often operate under the unrealistic assumption of an extremely small learning rate. This lies in stark contrast to practical wisdom and empirical studies, such as the work of J. Cohen et al. (ICLR 2021), which exhibit startling new phenomena (the "edge of stability" or "unst...
1803.00804
Karl Bringmann
Karl Bringmann, Philip Wellnitz
Clique-Based Lower Bounds for Parsing Tree-Adjoining Grammars
Presented at CPM'17. 15 pages
null
10.4230/LIPIcs.CPM.2017.12
null
cs.CC cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Tree-adjoining grammars are a generalization of context-free grammars that are well suited to model human languages and are thus popular in computational linguistics. In the tree-adjoining grammar recognition problem, given a grammar $\Gamma$ and a string $s$ of length $n$, the task is to decide whether $s$ can be ob...
[ { "created": "Fri, 2 Mar 2018 10:56:49 GMT", "version": "v1" } ]
2018-03-05
[ [ "Bringmann", "Karl", "" ], [ "Wellnitz", "Philip", "" ] ]
Tree-adjoining grammars are a generalization of context-free grammars that are well suited to model human languages and are thus popular in computational linguistics. In the tree-adjoining grammar recognition problem, given a grammar $\Gamma$ and a string $s$ of length $n$, the task is to decide whether $s$ can be obta...
2002.02886
Francesco Locatello
Francesco Locatello, Ben Poole, Gunnar R\"atsch, Bernhard Sch\"olkopf, Olivier Bachem, Michael Tschannen
Weakly-Supervised Disentanglement Without Compromises
We updated the description of the generation of the dataset compared to the ICML version
ICML 2020
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Intelligent agents should be able to learn useful representations by observing changes in their environment. We model such observations as pairs of non-i.i.d. images sharing at least one of the underlying factors of variation. First, we theoretically show that only knowing how many factors have changed, but not which...
[ { "created": "Fri, 7 Feb 2020 16:39:31 GMT", "version": "v1" }, { "created": "Mon, 18 May 2020 20:58:49 GMT", "version": "v2" }, { "created": "Thu, 25 Jun 2020 15:24:40 GMT", "version": "v3" }, { "created": "Tue, 20 Oct 2020 15:22:16 GMT", "version": "v4" } ]
2020-10-21
[ [ "Locatello", "Francesco", "" ], [ "Poole", "Ben", "" ], [ "Rätsch", "Gunnar", "" ], [ "Schölkopf", "Bernhard", "" ], [ "Bachem", "Olivier", "" ], [ "Tschannen", "Michael", "" ] ]
Intelligent agents should be able to learn useful representations by observing changes in their environment. We model such observations as pairs of non-i.i.d. images sharing at least one of the underlying factors of variation. First, we theoretically show that only knowing how many factors have changed, but not which o...
2203.12117
Jonathan Balloch
Jonathan Balloch, Zhiyu Lin, Mustafa Hussain, Aarun Srinivas, Robert Wright, Xiangyu Peng, Julia Kim, Mark Riedl
NovGrid: A Flexible Grid World for Evaluating Agent Response to Novelty
7 pages, 4 figures, AAAI Spring Symposium 2022 on Designing Artificial Intelligence for Open Worlds (Long Oral)
null
null
null
cs.AI cs.LG
http://creativecommons.org/licenses/by/4.0/
A robust body of reinforcement learning techniques have been developed to solve complex sequential decision making problems. However, these methods assume that train and evaluation tasks come from similarly or identically distributed environments. This assumption does not hold in real life where small novel changes t...
[ { "created": "Wed, 23 Mar 2022 01:06:04 GMT", "version": "v1" } ]
2022-03-24
[ [ "Balloch", "Jonathan", "" ], [ "Lin", "Zhiyu", "" ], [ "Hussain", "Mustafa", "" ], [ "Srinivas", "Aarun", "" ], [ "Wright", "Robert", "" ], [ "Peng", "Xiangyu", "" ], [ "Kim", "Julia", "" ], [ "Ried...
A robust body of reinforcement learning techniques have been developed to solve complex sequential decision making problems. However, these methods assume that train and evaluation tasks come from similarly or identically distributed environments. This assumption does not hold in real life where small novel changes to ...
1910.05713
Jin-Yuan Wang
Jin-Yuan Wang, Yu Qiu, Sheng-Hong Lin, Jun-Bo Wang, Min Lin, Cheng Liu
On the Secrecy Performance of Random VLC Networks with Imperfect CSI and Protected Zone
Accepted by IEEE Systems Joutnal
null
10.1109/JSYST.2019.2947614
null
cs.IT cs.PF math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper investigates the physical-layer security for a random indoor visible light communication (VLC) network with imperfect channel state information (CSI) and a protected zone. The VLC network consists of three nodes, i.e., a transmitter (Alice), a legitimate receiver (Bob), and an eavesdropper (Eve). Alice is ...
[ { "created": "Sun, 13 Oct 2019 08:49:18 GMT", "version": "v1" } ]
2023-07-19
[ [ "Wang", "Jin-Yuan", "" ], [ "Qiu", "Yu", "" ], [ "Lin", "Sheng-Hong", "" ], [ "Wang", "Jun-Bo", "" ], [ "Lin", "Min", "" ], [ "Liu", "Cheng", "" ] ]
This paper investigates the physical-layer security for a random indoor visible light communication (VLC) network with imperfect channel state information (CSI) and a protected zone. The VLC network consists of three nodes, i.e., a transmitter (Alice), a legitimate receiver (Bob), and an eavesdropper (Eve). Alice is fi...
1001.2160
Serge Grigorieff
Serge Grigorieff and Pierre Valarcher
Evolving MultiAlgebras unify all usual sequential computation models
12 pages, Symposium on Theoretical Aspects of Computer Science
null
null
null
cs.FL cs.LO
http://creativecommons.org/licenses/by/3.0/
It is well-known that Abstract State Machines (ASMs) can simulate "step-by-step" any type of machines (Turing machines, RAMs, etc.). We aim to overcome two facts: 1) simulation is not identification, 2) the ASMs simulating machines of some type do not constitute a natural class among all ASMs. We modify Gurevich's no...
[ { "created": "Wed, 13 Jan 2010 13:35:20 GMT", "version": "v1" }, { "created": "Wed, 3 Feb 2010 11:53:47 GMT", "version": "v2" } ]
2010-03-26
[ [ "Grigorieff", "Serge", "" ], [ "Valarcher", "Pierre", "" ] ]
It is well-known that Abstract State Machines (ASMs) can simulate "step-by-step" any type of machines (Turing machines, RAMs, etc.). We aim to overcome two facts: 1) simulation is not identification, 2) the ASMs simulating machines of some type do not constitute a natural class among all ASMs. We modify Gurevich's noti...
2207.01577
Nitinder Mohan
Giovanni Bartolomeo, Mehdi Yosofie, Simon B\"aurle, Oliver Haluszczynski, Nitinder Mohan and J\"org Ott
Oakestra white paper: An Orchestrator for Edge Computing
null
null
null
null
cs.DC cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Edge computing seeks to enable applications with strict latency requirements by utilizing compute resources deployed closer to the users. The diverse, dynamic, and constrained nature of edge infrastructures necessitates a flexible orchestration framework that dynamically supports application QoS requirements. However...
[ { "created": "Mon, 4 Jul 2022 16:56:42 GMT", "version": "v1" } ]
2022-07-05
[ [ "Bartolomeo", "Giovanni", "" ], [ "Yosofie", "Mehdi", "" ], [ "Bäurle", "Simon", "" ], [ "Haluszczynski", "Oliver", "" ], [ "Mohan", "Nitinder", "" ], [ "Ott", "Jörg", "" ] ]
Edge computing seeks to enable applications with strict latency requirements by utilizing compute resources deployed closer to the users. The diverse, dynamic, and constrained nature of edge infrastructures necessitates a flexible orchestration framework that dynamically supports application QoS requirements. However, ...
1802.01810
Amaury Pouly
Ehud Hrushovski, Jo\"el Ouaknine, Amaury Pouly, James Worrell
Polynomial Invariants for Affine Programs
null
null
null
null
cs.LO cs.DM math.AG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We exhibit an algorithm to compute the strongest polynomial (or algebraic) invariants that hold at each location of a given affine program (i.e., a program having only non-deterministic (as opposed to conditional) branching and all of whose assignments are given by affine expressions). Our main tool is an algebraic r...
[ { "created": "Tue, 6 Feb 2018 06:14:19 GMT", "version": "v1" }, { "created": "Wed, 2 May 2018 10:05:06 GMT", "version": "v2" } ]
2018-05-03
[ [ "Hrushovski", "Ehud", "" ], [ "Ouaknine", "Joël", "" ], [ "Pouly", "Amaury", "" ], [ "Worrell", "James", "" ] ]
We exhibit an algorithm to compute the strongest polynomial (or algebraic) invariants that hold at each location of a given affine program (i.e., a program having only non-deterministic (as opposed to conditional) branching and all of whose assignments are given by affine expressions). Our main tool is an algebraic res...
2207.11880
Huaxiong Li
Kaiyi Luo, Chao Zhang, Huaxiong Li, Xiuyi Jia, Chunlin Chen
Adaptive Marginalized Semantic Hashing for Unpaired Cross-Modal Retrieval
null
null
10.1109/TMM.2023.3245400
null
cs.MM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In recent years, Cross-Modal Hashing (CMH) has aroused much attention due to its fast query speed and efficient storage. Previous literatures have achieved promising results for Cross-Modal Retrieval (CMR) by discovering discriminative hash codes and modality-specific hash functions. Nonetheless, most existing CMR wo...
[ { "created": "Mon, 25 Jul 2022 02:50:20 GMT", "version": "v1" } ]
2023-10-06
[ [ "Luo", "Kaiyi", "" ], [ "Zhang", "Chao", "" ], [ "Li", "Huaxiong", "" ], [ "Jia", "Xiuyi", "" ], [ "Chen", "Chunlin", "" ] ]
In recent years, Cross-Modal Hashing (CMH) has aroused much attention due to its fast query speed and efficient storage. Previous literatures have achieved promising results for Cross-Modal Retrieval (CMR) by discovering discriminative hash codes and modality-specific hash functions. Nonetheless, most existing CMR work...
2003.02834
Chaochao Chen
Chaochao Chen, Jun Zhou, Bingzhe Wu, Wenjin Fang, Li Wang, Yuan Qi, Xiaolin Zheng
Practical Privacy Preserving POI Recommendation
Accepted by ACM TIST
null
null
null
cs.CR cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Point-of-Interest (POI) recommendation has been extensively studied and successfully applied in industry recently. However, most existing approaches build centralized models on the basis of collecting users' data. Both private data and models are held by the recommender, which causes serious privacy concerns. In this...
[ { "created": "Thu, 5 Mar 2020 06:06:40 GMT", "version": "v1" }, { "created": "Mon, 27 Apr 2020 06:11:26 GMT", "version": "v2" } ]
2020-04-28
[ [ "Chen", "Chaochao", "" ], [ "Zhou", "Jun", "" ], [ "Wu", "Bingzhe", "" ], [ "Fang", "Wenjin", "" ], [ "Wang", "Li", "" ], [ "Qi", "Yuan", "" ], [ "Zheng", "Xiaolin", "" ] ]
Point-of-Interest (POI) recommendation has been extensively studied and successfully applied in industry recently. However, most existing approaches build centralized models on the basis of collecting users' data. Both private data and models are held by the recommender, which causes serious privacy concerns. In this p...
2106.01632
Farhan Sadique
Farhan Sadique, Ignacio Astaburuaga, Raghav Kaul, Shamik Sengupta, Shahriar Badsha, James Schnebly, Adam Cassell, Jeff Springer, Nancy Latourrette and Sergiu M. Dascalu
Cybersecurity Information Exchange with Privacy (CYBEX-P) and TAHOE -- A Cyberthreat Language
null
null
null
null
cs.CR cs.LG
http://creativecommons.org/licenses/by-nc-nd/4.0/
Cybersecurity information sharing (CIS) is envisioned to protect organizations more effectively from advanced cyber attacks. However, a completely automated CIS platform is not widely adopted. The major challenges are: (1) the absence of a robust cyber threat language (CTL) and (2) the concerns over data privacy. Thi...
[ { "created": "Thu, 3 Jun 2021 07:10:16 GMT", "version": "v1" } ]
2021-06-04
[ [ "Sadique", "Farhan", "" ], [ "Astaburuaga", "Ignacio", "" ], [ "Kaul", "Raghav", "" ], [ "Sengupta", "Shamik", "" ], [ "Badsha", "Shahriar", "" ], [ "Schnebly", "James", "" ], [ "Cassell", "Adam", "" ], ...
Cybersecurity information sharing (CIS) is envisioned to protect organizations more effectively from advanced cyber attacks. However, a completely automated CIS platform is not widely adopted. The major challenges are: (1) the absence of a robust cyber threat language (CTL) and (2) the concerns over data privacy. This ...
1907.00338
Simon Lynen
Simon Lynen, Bernhard Zeisl, Dror Aiger, Michael Bosse, Joel Hesch, Marc Pollefeys, Roland Siegwart, Torsten Sattler
Large-scale, real-time visual-inertial localization revisited
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The overarching goals in image-based localization are scale, robustness and speed. In recent years, approaches based on local features and sparse 3D point-cloud models have both dominated the benchmarks and seen successful realworld deployment. They enable applications ranging from robot navigation, autonomous drivin...
[ { "created": "Sun, 30 Jun 2019 08:45:58 GMT", "version": "v1" } ]
2019-07-02
[ [ "Lynen", "Simon", "" ], [ "Zeisl", "Bernhard", "" ], [ "Aiger", "Dror", "" ], [ "Bosse", "Michael", "" ], [ "Hesch", "Joel", "" ], [ "Pollefeys", "Marc", "" ], [ "Siegwart", "Roland", "" ], [ "Sattl...
The overarching goals in image-based localization are scale, robustness and speed. In recent years, approaches based on local features and sparse 3D point-cloud models have both dominated the benchmarks and seen successful realworld deployment. They enable applications ranging from robot navigation, autonomous driving,...
1105.2988
James P. Crutchfield
Ryan G. James, Christopher J. Ellison, and James P. Crutchfield
Anatomy of a Bit: Information in a Time Series Observation
15 pages, 12 figures, 2 tables; http://cse.ucdavis.edu/~cmg/compmech/pubs/anatomy.htm
null
10.1063/1.3637494
null
cs.IT cond-mat.stat-mech math.IT math.ST nlin.AO stat.TH
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Appealing to several multivariate information measures---some familiar, some new here---we analyze the information embedded in discrete-valued stochastic time series. We dissect the uncertainty of a single observation to demonstrate how the measures' asymptotic behavior sheds structural and semantic light on the gene...
[ { "created": "Mon, 16 May 2011 01:26:04 GMT", "version": "v1" } ]
2015-05-28
[ [ "James", "Ryan G.", "" ], [ "Ellison", "Christopher J.", "" ], [ "Crutchfield", "James P.", "" ] ]
Appealing to several multivariate information measures---some familiar, some new here---we analyze the information embedded in discrete-valued stochastic time series. We dissect the uncertainty of a single observation to demonstrate how the measures' asymptotic behavior sheds structural and semantic light on the genera...
2108.05851
Zike Yan
Zike Yan, Yuxin Tian, Xuesong Shi, Ping Guo, Peng Wang, Hongbin Zha
Continual Neural Mapping: Learning An Implicit Scene Representation from Sequential Observations
ICCV 2021
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Recent advances have enabled a single neural network to serve as an implicit scene representation, establishing the mapping function between spatial coordinates and scene properties. In this paper, we make a further step towards continual learning of the implicit scene representation directly from sequential observat...
[ { "created": "Thu, 12 Aug 2021 16:57:29 GMT", "version": "v1" } ]
2021-10-05
[ [ "Yan", "Zike", "" ], [ "Tian", "Yuxin", "" ], [ "Shi", "Xuesong", "" ], [ "Guo", "Ping", "" ], [ "Wang", "Peng", "" ], [ "Zha", "Hongbin", "" ] ]
Recent advances have enabled a single neural network to serve as an implicit scene representation, establishing the mapping function between spatial coordinates and scene properties. In this paper, we make a further step towards continual learning of the implicit scene representation directly from sequential observatio...
1407.1890
Michael Smith
Michael R. Smith, Logan Mitchell, Christophe Giraud-Carrier, Tony Martinez
Recommending Learning Algorithms and Their Associated Hyperparameters
Short paper--2 pages, 2 tables
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The success of machine learning on a given task dependson, among other things, which learning algorithm is selected and its associated hyperparameters. Selecting an appropriate learning algorithm and setting its hyperparameters for a given data set can be a challenging task, especially for users who are not experts i...
[ { "created": "Mon, 7 Jul 2014 21:23:42 GMT", "version": "v1" } ]
2014-07-09
[ [ "Smith", "Michael R.", "" ], [ "Mitchell", "Logan", "" ], [ "Giraud-Carrier", "Christophe", "" ], [ "Martinez", "Tony", "" ] ]
The success of machine learning on a given task dependson, among other things, which learning algorithm is selected and its associated hyperparameters. Selecting an appropriate learning algorithm and setting its hyperparameters for a given data set can be a challenging task, especially for users who are not experts in ...
1812.00054
Zeming Lin
Gabriel Synnaeve, Zeming Lin, Jonas Gehring, Dan Gant, Vegard Mella, Vasil Khalidov, Nicolas Carion, Nicolas Usunier
Forward Modeling for Partial Observation Strategy Games - A StarCraft Defogger
null
Advances in Neural Information Processing Systems 31 (2018) 10759-10770
null
null
cs.LG cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We formulate the problem of defogging as state estimation and future state prediction from previous, partial observations in the context of real-time strategy games. We propose to employ encoder-decoder neural networks for this task, and introduce proxy tasks and baselines for evaluation to assess their ability of ca...
[ { "created": "Fri, 30 Nov 2018 20:48:31 GMT", "version": "v1" } ]
2018-12-04
[ [ "Synnaeve", "Gabriel", "" ], [ "Lin", "Zeming", "" ], [ "Gehring", "Jonas", "" ], [ "Gant", "Dan", "" ], [ "Mella", "Vegard", "" ], [ "Khalidov", "Vasil", "" ], [ "Carion", "Nicolas", "" ], [ "Usuni...
We formulate the problem of defogging as state estimation and future state prediction from previous, partial observations in the context of real-time strategy games. We propose to employ encoder-decoder neural networks for this task, and introduce proxy tasks and baselines for evaluation to assess their ability of capt...
2405.00860
Randy Connolly
Randy Connolly
Public Computing Intellectuals in the Age of AI Crisis
28 pages, 2 tables
null
null
null
cs.CY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The belief that AI technology is on the cusp of causing a generalized social crisis became a popular one in 2023. While there was no doubt an element of hype and exaggeration to some of these accounts, they do reflect the fact that there are troubling ramifications to this technology stack. This conjunction of shared...
[ { "created": "Wed, 1 May 2024 20:48:34 GMT", "version": "v1" }, { "created": "Wed, 19 Jun 2024 20:13:37 GMT", "version": "v2" } ]
2024-06-21
[ [ "Connolly", "Randy", "" ] ]
The belief that AI technology is on the cusp of causing a generalized social crisis became a popular one in 2023. While there was no doubt an element of hype and exaggeration to some of these accounts, they do reflect the fact that there are troubling ramifications to this technology stack. This conjunction of shared c...
1802.05380
Sheng-Jun Huang
Sheng-Jun Huang, Miao Xu, Ming-Kun Xie, Masashi Sugiyama, Gang Niu and Songcan Chen
Active Feature Acquisition with Supervised Matrix Completion
9 pages, 8 figures
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Feature missing is a serious problem in many applications, which may lead to low quality of training data and further significantly degrade the learning performance. While feature acquisition usually involves special devices or complex process, it is expensive to acquire all feature values for the whole dataset. On t...
[ { "created": "Thu, 15 Feb 2018 01:46:59 GMT", "version": "v1" }, { "created": "Tue, 5 Jun 2018 02:02:01 GMT", "version": "v2" } ]
2018-06-06
[ [ "Huang", "Sheng-Jun", "" ], [ "Xu", "Miao", "" ], [ "Xie", "Ming-Kun", "" ], [ "Sugiyama", "Masashi", "" ], [ "Niu", "Gang", "" ], [ "Chen", "Songcan", "" ] ]
Feature missing is a serious problem in many applications, which may lead to low quality of training data and further significantly degrade the learning performance. While feature acquisition usually involves special devices or complex process, it is expensive to acquire all feature values for the whole dataset. On the...
2311.15453
Sergio Naval Marimont
Sergio Naval Marimont and Matthew Baugh and Vasilis Siomos and Christos Tzelepis and Bernhard Kainz and Giacomo Tarroni
DISYRE: Diffusion-Inspired SYnthetic REstoration for Unsupervised Anomaly Detection
5 pages, 3 figures. Accepted for publication in ISBI 2024
null
null
null
cs.CV eess.IV
http://creativecommons.org/licenses/by/4.0/
Unsupervised Anomaly Detection (UAD) techniques aim to identify and localize anomalies without relying on annotations, only leveraging a model trained on a dataset known to be free of anomalies. Diffusion models learn to modify inputs $x$ to increase the probability of it belonging to a desired distribution, i.e., th...
[ { "created": "Sun, 26 Nov 2023 23:07:19 GMT", "version": "v1" }, { "created": "Tue, 5 Mar 2024 08:59:25 GMT", "version": "v2" } ]
2024-03-06
[ [ "Marimont", "Sergio Naval", "" ], [ "Baugh", "Matthew", "" ], [ "Siomos", "Vasilis", "" ], [ "Tzelepis", "Christos", "" ], [ "Kainz", "Bernhard", "" ], [ "Tarroni", "Giacomo", "" ] ]
Unsupervised Anomaly Detection (UAD) techniques aim to identify and localize anomalies without relying on annotations, only leveraging a model trained on a dataset known to be free of anomalies. Diffusion models learn to modify inputs $x$ to increase the probability of it belonging to a desired distribution, i.e., they...
1312.1822
Brijender Kahanwal Dr.
Brijender Kahanwal, Tejinder Pal Singh
Towards the Framework of the File Systems Performance Evaluation Techniques and the Taxonomy of Replay Traces
7 pages
International Journal of Advanced Research in Computer Science, 2(6) pp. 224-229, 2011
null
null
cs.OS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This is the era of High Performance Computing (HPC). There is a great demand of the best performance evaluation techniques for the file and storage systems. The task of evaluation is both necessary and hard. It gives in depth analysis of the target system and that becomes the decision points for the users. That is al...
[ { "created": "Fri, 6 Dec 2013 10:20:38 GMT", "version": "v1" } ]
2013-12-09
[ [ "Kahanwal", "Brijender", "" ], [ "Singh", "Tejinder Pal", "" ] ]
This is the era of High Performance Computing (HPC). There is a great demand of the best performance evaluation techniques for the file and storage systems. The task of evaluation is both necessary and hard. It gives in depth analysis of the target system and that becomes the decision points for the users. That is also...
2003.12419
Vlad-Florin Dr\u{a}goi
Vlad-Florin Dr\u{a}goi and Simon R. Cowell and Valeriu Beiu
Tight Bounds on the Coeffcients of Consecutive $k$-out-of-$n$:$F$ Systems
10 pages, 3 figures, accepted for presentation at the International Conference on Computers Communications and Control (ICCCC), May 2020
Intelligent Methods in Computing, Communications and Control. ICCCC 2020
10.1007/978-3-030-53651-0_3
null
cs.DM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper we compute the coefficients of the reliability polynomial of a consecutive-$k$-out-of-$n$:$F$ system, in Bernstein basis, using the generalized Pascal coefficients. Based on well-known combinatorial properties of the generalized Pascal triangle we determine simple closed formulae for the reliability pol...
[ { "created": "Fri, 27 Mar 2020 13:57:20 GMT", "version": "v1" } ]
2021-12-14
[ [ "Drăgoi", "Vlad-Florin", "" ], [ "Cowell", "Simon R.", "" ], [ "Beiu", "Valeriu", "" ] ]
In this paper we compute the coefficients of the reliability polynomial of a consecutive-$k$-out-of-$n$:$F$ system, in Bernstein basis, using the generalized Pascal coefficients. Based on well-known combinatorial properties of the generalized Pascal triangle we determine simple closed formulae for the reliability polyn...
1707.08262
Siddharth Biswal
Siddharth Biswal, Joshua Kulas, Haoqi Sun, Balaji Goparaju, M Brandon Westover, Matt T Bianchi, Jimeng Sun
SLEEPNET: Automated Sleep Staging System via Deep Learning
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Sleep disorders, such as sleep apnea, parasomnias, and hypersomnia, affect 50-70 million adults in the United States (Hillman et al., 2006). Overnight polysomnography (PSG), including brain monitoring using electroencephalography (EEG), is a central component of the diagnostic evaluation for sleep disorders. While PS...
[ { "created": "Wed, 26 Jul 2017 00:39:59 GMT", "version": "v1" } ]
2017-07-27
[ [ "Biswal", "Siddharth", "" ], [ "Kulas", "Joshua", "" ], [ "Sun", "Haoqi", "" ], [ "Goparaju", "Balaji", "" ], [ "Westover", "M Brandon", "" ], [ "Bianchi", "Matt T", "" ], [ "Sun", "Jimeng", "" ] ]
Sleep disorders, such as sleep apnea, parasomnias, and hypersomnia, affect 50-70 million adults in the United States (Hillman et al., 2006). Overnight polysomnography (PSG), including brain monitoring using electroencephalography (EEG), is a central component of the diagnostic evaluation for sleep disorders. While PSG ...
1810.04873
Yucheng Wang
Yucheng Wang and Jialiang Shen and Jian Zhang
Deep Bi-Dense Networks for Image Super-Resolution
DICTA 2018
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper proposes Deep Bi-Dense Networks (DBDN) for single image super-resolution. Our approach extends previous intra-block dense connection approaches by including novel inter-block dense connections. In this way, feature information propagates from a single dense block to all subsequent blocks, instead of to a s...
[ { "created": "Thu, 11 Oct 2018 07:34:39 GMT", "version": "v1" } ]
2018-10-12
[ [ "Wang", "Yucheng", "" ], [ "Shen", "Jialiang", "" ], [ "Zhang", "Jian", "" ] ]
This paper proposes Deep Bi-Dense Networks (DBDN) for single image super-resolution. Our approach extends previous intra-block dense connection approaches by including novel inter-block dense connections. In this way, feature information propagates from a single dense block to all subsequent blocks, instead of to a sin...
1803.09080
Lei Sang
Lei Sang and Min Xu and Shengsheng Qian and Xindong Wu
AAANE: Attention-based Adversarial Autoencoder for Multi-scale Network Embedding
8 pages, 5 figures
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Network embedding represents nodes in a continuous vector space and preserves structure information from the Network. Existing methods usually adopt a "one-size-fits-all" approach when concerning multi-scale structure information, such as first- and second-order proximity of nodes, ignoring the fact that different sc...
[ { "created": "Sat, 24 Mar 2018 09:15:05 GMT", "version": "v1" } ]
2018-03-28
[ [ "Sang", "Lei", "" ], [ "Xu", "Min", "" ], [ "Qian", "Shengsheng", "" ], [ "Wu", "Xindong", "" ] ]
Network embedding represents nodes in a continuous vector space and preserves structure information from the Network. Existing methods usually adopt a "one-size-fits-all" approach when concerning multi-scale structure information, such as first- and second-order proximity of nodes, ignoring the fact that different scal...
1604.05048
Sandeep Kumar Singh
Sandeep Kumar Singh, Wolfgang Bziuk, and Admela Jukan
Balancing Data Security and Blocking Performance with Spectrum Randomization in Optical Networks
null
null
null
null
cs.NI
http://creativecommons.org/licenses/by-nc-sa/4.0/
Data randomization or scrambling has been effectively used in various applications to improve the data security. In this paper, we use the idea of data randomization to proactively randomize the spectrum (re)allocation to improve connections' security. As it is well-known that random (re)allocation fragments the spec...
[ { "created": "Mon, 18 Apr 2016 09:10:05 GMT", "version": "v1" } ]
2016-04-19
[ [ "Singh", "Sandeep Kumar", "" ], [ "Bziuk", "Wolfgang", "" ], [ "Jukan", "Admela", "" ] ]
Data randomization or scrambling has been effectively used in various applications to improve the data security. In this paper, we use the idea of data randomization to proactively randomize the spectrum (re)allocation to improve connections' security. As it is well-known that random (re)allocation fragments the spectr...
2101.06848
Isaac Sledge
Isaac J. Sledge and Jose C. Principe
Faster Convergence in Deep-Predictive-Coding Networks to Learn Deeper Representations
Submitted to the IEEE Transactions on Neural Networks and Learning Systems
null
10.1109/TNNLS.2021.3115698
null
cs.AI cs.CV cs.NE
http://creativecommons.org/licenses/by/4.0/
Deep-predictive-coding networks (DPCNs) are hierarchical, generative models. They rely on feed-forward and feed-back connections to modulate latent feature representations of stimuli in a dynamic and context-sensitive manner. A crucial element of DPCNs is a forward-backward inference procedure to uncover sparse, inva...
[ { "created": "Mon, 18 Jan 2021 02:30:13 GMT", "version": "v1" }, { "created": "Fri, 5 Feb 2021 07:03:20 GMT", "version": "v2" }, { "created": "Sat, 15 May 2021 21:52:47 GMT", "version": "v3" }, { "created": "Fri, 24 Sep 2021 03:50:09 GMT", "version": "v4" } ]
2021-09-27
[ [ "Sledge", "Isaac J.", "" ], [ "Principe", "Jose C.", "" ] ]
Deep-predictive-coding networks (DPCNs) are hierarchical, generative models. They rely on feed-forward and feed-back connections to modulate latent feature representations of stimuli in a dynamic and context-sensitive manner. A crucial element of DPCNs is a forward-backward inference procedure to uncover sparse, invari...
1703.06501
Juan-Manuel Torres-Moreno
Elvys Linhares Pontes, Thiago Gouveia da Silva, Andr\'ea Carneiro Linhares, Juan-Manuel Torres-Moreno, St\'ephane Huet
M\'etodos de Otimiza\c{c}\~ao Combinat\'oria Aplicados ao Problema de Compress\~ao MultiFrases
12 pages, 1 figure, 3 tables (paper in Portuguese), Preprint of XLVIII Simp\'osio Brasileiro de Pesquisa Operacional, 2016, Vit\'oria, ES, (Brazil)
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The Internet has led to a dramatic increase in the amount of available information. In this context, reading and understanding this flow of information have become costly tasks. In the last years, to assist people to understand textual data, various Natural Language Processing (NLP) applications based on Combinatoria...
[ { "created": "Sun, 19 Mar 2017 19:56:25 GMT", "version": "v1" } ]
2017-03-21
[ [ "Pontes", "Elvys Linhares", "" ], [ "da Silva", "Thiago Gouveia", "" ], [ "Linhares", "Andréa Carneiro", "" ], [ "Torres-Moreno", "Juan-Manuel", "" ], [ "Huet", "Stéphane", "" ] ]
The Internet has led to a dramatic increase in the amount of available information. In this context, reading and understanding this flow of information have become costly tasks. In the last years, to assist people to understand textual data, various Natural Language Processing (NLP) applications based on Combinatorial ...
2404.09585
Masahito Toba
Masahito Toba, Seiichi Uchida, Hideaki Hayashi
Pseudo-label Learning with Calibrated Confidence Using an Energy-based Model
8 pages, 8 figures, Accepted at IJCNN 2024
null
null
null
cs.CV
http://creativecommons.org/licenses/by-nc-nd/4.0/
In pseudo-labeling (PL), which is a type of semi-supervised learning, pseudo-labels are assigned based on the confidence scores provided by the classifier; therefore, accurate confidence is important for successful PL. In this study, we propose a PL algorithm based on an energy-based model (EBM), which is referred to...
[ { "created": "Mon, 15 Apr 2024 08:52:51 GMT", "version": "v1" } ]
2024-04-16
[ [ "Toba", "Masahito", "" ], [ "Uchida", "Seiichi", "" ], [ "Hayashi", "Hideaki", "" ] ]
In pseudo-labeling (PL), which is a type of semi-supervised learning, pseudo-labels are assigned based on the confidence scores provided by the classifier; therefore, accurate confidence is important for successful PL. In this study, we propose a PL algorithm based on an energy-based model (EBM), which is referred to a...
1802.02917
Fabrizio Montesi
Fabrizio Montesi
Classical Higher-Order Processes
null
null
null
null
cs.LO cs.PL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Classical Processes (CP) is a calculus where the proof theory of classical linear logic types communicating processes with mobile channels, a la pi-calculus. Its construction builds on a recent propositions as types correspondence between session types and propositions in linear logic. Desirable properties such as ty...
[ { "created": "Thu, 8 Feb 2018 15:21:22 GMT", "version": "v1" } ]
2018-02-09
[ [ "Montesi", "Fabrizio", "" ] ]
Classical Processes (CP) is a calculus where the proof theory of classical linear logic types communicating processes with mobile channels, a la pi-calculus. Its construction builds on a recent propositions as types correspondence between session types and propositions in linear logic. Desirable properties such as type...
1903.07588
Amr Amr
Amr Adel Helmy
A Multilingual Encoding Method for Text Classification and Dialect Identification Using Convolutional Neural Network
A dissertation submitted to the AASTMT on February 2019 in partial fulfillment of the requirements for the degree of Master of Science in Computer Science. arXiv admin note: text overlap with arXiv:1807.10854 by other authors without attribution
null
null
null
cs.CL cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This thesis presents a language-independent text classification model by introduced two new encoding methods "BUNOW" and "BUNOC" used for feeding the raw text data into a new CNN spatial architecture with vertical and horizontal convolutional process instead of commonly used methods like one hot vector or word repres...
[ { "created": "Mon, 18 Mar 2019 17:31:14 GMT", "version": "v1" } ]
2019-03-19
[ [ "Helmy", "Amr Adel", "" ] ]
This thesis presents a language-independent text classification model by introduced two new encoding methods "BUNOW" and "BUNOC" used for feeding the raw text data into a new CNN spatial architecture with vertical and horizontal convolutional process instead of commonly used methods like one hot vector or word represen...
2407.21231
Hena Ahmed
H. Ahmed, R. Shende, I. Perez, D. Crawl, S. Purawat, I. Altintas
Towards an Integrated Performance Framework for Fire Science and Management Workflows
null
null
null
null
cs.LG cs.PF
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Reliable performance metrics are necessary prerequisites to building large-scale end-to-end integrated workflows for collaborative scientific research, particularly within context of use-inspired decision making platforms with many concurrent users and when computing real-time and urgent results using large data. Thi...
[ { "created": "Tue, 30 Jul 2024 22:37:25 GMT", "version": "v1" } ]
2024-08-01
[ [ "Ahmed", "H.", "" ], [ "Shende", "R.", "" ], [ "Perez", "I.", "" ], [ "Crawl", "D.", "" ], [ "Purawat", "S.", "" ], [ "Altintas", "I.", "" ] ]
Reliable performance metrics are necessary prerequisites to building large-scale end-to-end integrated workflows for collaborative scientific research, particularly within context of use-inspired decision making platforms with many concurrent users and when computing real-time and urgent results using large data. This ...
1712.09619
Abdolah Sepahvand
Mohammadreza Razzazi, Abdolah Sepahvand
Finding Two Disjoint Simple Paths on Two Sets of Points is NP-Complete
null
scientiairanica.sharif.edu/article_4116.html 2017
10.24200/SCI.2017.4116
null
cs.CC cs.CG
http://creativecommons.org/publicdomain/zero/1.0/
Finding two disjoint simple paths on two given sets of points is a geometric problem introduced by Jeff Erickson. This problem has various applications in computational geometry, like robot motion planning, generating polygon etc. We will present a reduction from planar Hamiltonian path to this problem, and prove tha...
[ { "created": "Wed, 27 Dec 2017 16:36:50 GMT", "version": "v1" } ]
2017-12-29
[ [ "Razzazi", "Mohammadreza", "" ], [ "Sepahvand", "Abdolah", "" ] ]
Finding two disjoint simple paths on two given sets of points is a geometric problem introduced by Jeff Erickson. This problem has various applications in computational geometry, like robot motion planning, generating polygon etc. We will present a reduction from planar Hamiltonian path to this problem, and prove that ...
1408.6063
Leandro Montero
Marina Groshaus, Andr\'e Guedes, Leandro Montero
Almost every graph is divergent under the biclique operator
24 pages, 13 figures
null
null
null
cs.DM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A biclique of a graph $G$ is a maximal induced complete bipartite subgraph of $G$. The biclique graph of $G$ denoted by $KB(G)$, is the intersection graph of all the bicliques of $G$. The biclique graph can be thought as an operator between graphs. The iterated biclique graph of $G$ denoted by $KB^{k}(G)$, is the gra...
[ { "created": "Tue, 26 Aug 2014 10:01:49 GMT", "version": "v1" }, { "created": "Thu, 4 Sep 2014 15:26:35 GMT", "version": "v2" }, { "created": "Mon, 31 Aug 2015 10:17:56 GMT", "version": "v3" } ]
2015-09-01
[ [ "Groshaus", "Marina", "" ], [ "Guedes", "André", "" ], [ "Montero", "Leandro", "" ] ]
A biclique of a graph $G$ is a maximal induced complete bipartite subgraph of $G$. The biclique graph of $G$ denoted by $KB(G)$, is the intersection graph of all the bicliques of $G$. The biclique graph can be thought as an operator between graphs. The iterated biclique graph of $G$ denoted by $KB^{k}(G)$, is the graph...
2209.06415
Senthil Hariharan Arul
Senthil Hariharan Arul, Amrit Singh Bedi, Dinesh Manocha
DMCA: Dense Multi-agent Navigation using Attention and Communication
null
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In decentralized multi-robot navigation, ensuring safe and efficient movement with limited environmental awareness remains a challenge. While robots traditionally navigate based on local observations, this approach falters in complex environments. A possible solution is to enhance understanding of the world through i...
[ { "created": "Wed, 14 Sep 2022 04:58:03 GMT", "version": "v1" }, { "created": "Wed, 28 Sep 2022 20:30:32 GMT", "version": "v2" }, { "created": "Tue, 25 Jun 2024 18:22:21 GMT", "version": "v3" } ]
2024-06-27
[ [ "Arul", "Senthil Hariharan", "" ], [ "Bedi", "Amrit Singh", "" ], [ "Manocha", "Dinesh", "" ] ]
In decentralized multi-robot navigation, ensuring safe and efficient movement with limited environmental awareness remains a challenge. While robots traditionally navigate based on local observations, this approach falters in complex environments. A possible solution is to enhance understanding of the world through int...
1701.04301
Hengtao He
Hengtao He, Chao-Kai Wen, Shi Jin
Generalized Expectation Consistent Signal Recovery for Nonlinear Measurements
5 pages,3 figures,to be presented at ISIT 2017
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we propose a generalized expectation consistent signal recovery algorithm to estimate the signal $\mathbf{x}$ from the nonlinear measurements of a linear transform output $\mathbf{z}=\mathbf{A}\mathbf{x}$. This estimation problem has been encountered in many applications, such as communications with fr...
[ { "created": "Mon, 16 Jan 2017 14:26:34 GMT", "version": "v1" }, { "created": "Mon, 23 Jan 2017 01:38:05 GMT", "version": "v2" }, { "created": "Fri, 12 May 2017 01:19:05 GMT", "version": "v3" } ]
2017-05-15
[ [ "He", "Hengtao", "" ], [ "Wen", "Chao-Kai", "" ], [ "Jin", "Shi", "" ] ]
In this paper, we propose a generalized expectation consistent signal recovery algorithm to estimate the signal $\mathbf{x}$ from the nonlinear measurements of a linear transform output $\mathbf{z}=\mathbf{A}\mathbf{x}$. This estimation problem has been encountered in many applications, such as communications with fron...
1907.06857
Arnold Filtser
Arnold Filtser, Lee-Ad Gottlieb, Robert Krauthgamer
Labelings vs. Embeddings: On Distributed Representations of Distances
null
null
null
null
cs.DS cs.CG
http://creativecommons.org/licenses/by/4.0/
We investigate for which metric spaces the performance of distance labeling and of $\ell_\infty$-embeddings differ, and how significant can this difference be. Recall that a distance labeling is a distributed representation of distances in a metric space $(X,d)$, where each point $x\in X$ is assigned a succinct label...
[ { "created": "Tue, 16 Jul 2019 06:25:48 GMT", "version": "v1" }, { "created": "Wed, 20 Sep 2023 06:37:52 GMT", "version": "v2" } ]
2023-09-21
[ [ "Filtser", "Arnold", "" ], [ "Gottlieb", "Lee-Ad", "" ], [ "Krauthgamer", "Robert", "" ] ]
We investigate for which metric spaces the performance of distance labeling and of $\ell_\infty$-embeddings differ, and how significant can this difference be. Recall that a distance labeling is a distributed representation of distances in a metric space $(X,d)$, where each point $x\in X$ is assigned a succinct label, ...
2309.16653
Jiaxiang Tang
Jiaxiang Tang, Jiawei Ren, Hang Zhou, Ziwei Liu, Gang Zeng
DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creation
Camera-ready version. Project page: https://dreamgaussian.github.io/
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recent advances in 3D content creation mostly leverage optimization-based 3D generation via score distillation sampling (SDS). Though promising results have been exhibited, these methods often suffer from slow per-sample optimization, limiting their practical usage. In this paper, we propose DreamGaussian, a novel 3D...
[ { "created": "Thu, 28 Sep 2023 17:55:05 GMT", "version": "v1" }, { "created": "Fri, 29 Mar 2024 08:39:23 GMT", "version": "v2" } ]
2024-04-01
[ [ "Tang", "Jiaxiang", "" ], [ "Ren", "Jiawei", "" ], [ "Zhou", "Hang", "" ], [ "Liu", "Ziwei", "" ], [ "Zeng", "Gang", "" ] ]
Recent advances in 3D content creation mostly leverage optimization-based 3D generation via score distillation sampling (SDS). Though promising results have been exhibited, these methods often suffer from slow per-sample optimization, limiting their practical usage. In this paper, we propose DreamGaussian, a novel 3D c...
2011.13246
Dawood Al Chanti
Dawood Al Chanti, Vanessa Gonzalez Duque, Marion Crouzier, Antoine Nordez, Lilian Lacourpaille, and Diana Mateus
IFSS-Net: Interactive Few-Shot Siamese Network for Faster Muscle Segmentation and Propagation in Volumetric Ultrasound
14 pages, 18 figures, 10 Tables
null
10.1109/TMI.2021.3058303
null
cs.CV cs.AI cs.LG
http://creativecommons.org/licenses/by/4.0/
We present an accurate, fast and efficient method for segmentation and muscle mask propagation in 3D freehand ultrasound data, towards accurate volume quantification. A deep Siamese 3D Encoder-Decoder network that captures the evolution of the muscle appearance and shape for contiguous slices is deployed. We uses it ...
[ { "created": "Thu, 26 Nov 2020 11:37:25 GMT", "version": "v1" }, { "created": "Sat, 30 Jan 2021 11:40:48 GMT", "version": "v2" } ]
2021-02-09
[ [ "Chanti", "Dawood Al", "" ], [ "Duque", "Vanessa Gonzalez", "" ], [ "Crouzier", "Marion", "" ], [ "Nordez", "Antoine", "" ], [ "Lacourpaille", "Lilian", "" ], [ "Mateus", "Diana", "" ] ]
We present an accurate, fast and efficient method for segmentation and muscle mask propagation in 3D freehand ultrasound data, towards accurate volume quantification. A deep Siamese 3D Encoder-Decoder network that captures the evolution of the muscle appearance and shape for contiguous slices is deployed. We uses it to...
2306.13944
Xiao Zhang
Xiao Zhang, Hai Zhang, Hongtu Zhou, Chang Huang, Di Zhang, Chen Ye, Junqiao Zhao
Safe Reinforcement Learning with Dead-Ends Avoidance and Recovery
8 pages, 5 figures
null
null
null
cs.LG cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Safety is one of the main challenges in applying reinforcement learning to realistic environmental tasks. To ensure safety during and after training process, existing methods tend to adopt overly conservative policy to avoid unsafe situations. However, overly conservative policy severely hinders the exploration, and ...
[ { "created": "Sat, 24 Jun 2023 12:02:50 GMT", "version": "v1" } ]
2023-06-27
[ [ "Zhang", "Xiao", "" ], [ "Zhang", "Hai", "" ], [ "Zhou", "Hongtu", "" ], [ "Huang", "Chang", "" ], [ "Zhang", "Di", "" ], [ "Ye", "Chen", "" ], [ "Zhao", "Junqiao", "" ] ]
Safety is one of the main challenges in applying reinforcement learning to realistic environmental tasks. To ensure safety during and after training process, existing methods tend to adopt overly conservative policy to avoid unsafe situations. However, overly conservative policy severely hinders the exploration, and ma...
2110.14904
Vahid Janfaza
Vahid Janfaza, Kevin Weston, Moein Razavi, Shantanu Mandal, Farabi Mahmud, Alex Hilty, Abdullah Muzahid
MERCURY: Accelerating DNN Training By Exploiting Input Similarity
13 pages, 18 figures, 4 tables
null
null
null
cs.AR cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Deep Neural Networks (DNN) are computationally intensive to train. It consists of a large number of multidimensional dot products between many weights and input vectors. However, there can be significant similarity among input vectors. If one input vector is similar to another, its computations with the weights are s...
[ { "created": "Thu, 28 Oct 2021 06:08:43 GMT", "version": "v1" }, { "created": "Wed, 2 Nov 2022 22:17:35 GMT", "version": "v2" } ]
2022-11-04
[ [ "Janfaza", "Vahid", "" ], [ "Weston", "Kevin", "" ], [ "Razavi", "Moein", "" ], [ "Mandal", "Shantanu", "" ], [ "Mahmud", "Farabi", "" ], [ "Hilty", "Alex", "" ], [ "Muzahid", "Abdullah", "" ] ]
Deep Neural Networks (DNN) are computationally intensive to train. It consists of a large number of multidimensional dot products between many weights and input vectors. However, there can be significant similarity among input vectors. If one input vector is similar to another, its computations with the weights are sim...
2211.17171
Jing Yao
Jing Yao, Zheng Liu, Junhan Yang, Zhicheng Dou, Xing Xie, Ji-Rong Wen
CDSM: Cascaded Deep Semantic Matching on Textual Graphs Leveraging Ad-hoc Neighbor Selection
null
null
null
null
cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Deep semantic matching aims to discriminate the relationship between documents based on deep neural networks. In recent years, it becomes increasingly popular to organize documents with a graph structure, then leverage both the intrinsic document features and the extrinsic neighbor features to derive discrimination. ...
[ { "created": "Wed, 30 Nov 2022 17:09:07 GMT", "version": "v1" }, { "created": "Wed, 7 Dec 2022 04:01:22 GMT", "version": "v2" } ]
2022-12-08
[ [ "Yao", "Jing", "" ], [ "Liu", "Zheng", "" ], [ "Yang", "Junhan", "" ], [ "Dou", "Zhicheng", "" ], [ "Xie", "Xing", "" ], [ "Wen", "Ji-Rong", "" ] ]
Deep semantic matching aims to discriminate the relationship between documents based on deep neural networks. In recent years, it becomes increasingly popular to organize documents with a graph structure, then leverage both the intrinsic document features and the extrinsic neighbor features to derive discrimination. Mo...
2404.12509
Peihan Tu
Peihan Tu, Li-Yi Wei, Matthias Zwicker
Compositional Neural Textures
null
null
null
null
cs.GR cs.AI cs.CV cs.LG
http://creativecommons.org/licenses/by/4.0/
Texture plays a vital role in enhancing visual richness in both real photographs and computer-generated imagery. However, the process of editing textures often involves laborious and repetitive manual adjustments of textons, which are the small, recurring local patterns that define textures. In this work, we introduc...
[ { "created": "Thu, 18 Apr 2024 21:09:34 GMT", "version": "v1" } ]
2024-04-22
[ [ "Tu", "Peihan", "" ], [ "Wei", "Li-Yi", "" ], [ "Zwicker", "Matthias", "" ] ]
Texture plays a vital role in enhancing visual richness in both real photographs and computer-generated imagery. However, the process of editing textures often involves laborious and repetitive manual adjustments of textons, which are the small, recurring local patterns that define textures. In this work, we introduce ...
1802.04498
Gilad Kutiel
Gilad Kutiel
Hardness Results and Approximation Algorithms for the Minimum Dominating Tree Problem
null
null
null
null
cs.CC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Given an undirected graph $G = (V, E)$ and a weight function $w:E \to \mathbb{R}$, the \textsc{Minimum Dominating Tree} problem asks to find a minimum weight sub-tree of $G$, $T = (U, F)$, such that every $v \in V \setminus U$ is adjacent to at least one vertex in $U$. The special case when the weight function is uni...
[ { "created": "Tue, 13 Feb 2018 08:10:03 GMT", "version": "v1" } ]
2018-02-14
[ [ "Kutiel", "Gilad", "" ] ]
Given an undirected graph $G = (V, E)$ and a weight function $w:E \to \mathbb{R}$, the \textsc{Minimum Dominating Tree} problem asks to find a minimum weight sub-tree of $G$, $T = (U, F)$, such that every $v \in V \setminus U$ is adjacent to at least one vertex in $U$. The special case when the weight function is unifo...
1712.02016
Hu Xu
Hu Xu and Sihong Xie and Lei Shu and Philip S. Yu
Dual Attention Network for Product Compatibility and Function Satisfiability Analysis
null
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Product compatibility and their functionality are of utmost importance to customers when they purchase products, and to sellers and manufacturers when they sell products. Due to the huge number of products available online, it is infeasible to enumerate and test the compatibility and functionality of every product. I...
[ { "created": "Wed, 6 Dec 2017 03:11:51 GMT", "version": "v1" } ]
2017-12-07
[ [ "Xu", "Hu", "" ], [ "Xie", "Sihong", "" ], [ "Shu", "Lei", "" ], [ "Yu", "Philip S.", "" ] ]
Product compatibility and their functionality are of utmost importance to customers when they purchase products, and to sellers and manufacturers when they sell products. Due to the huge number of products available online, it is infeasible to enumerate and test the compatibility and functionality of every product. In ...
2102.06333
Charlie Hou
Charlie Hou, Kiran K. Thekumparampil, Giulia Fanti, Sewoong Oh
Efficient Algorithms for Federated Saddle Point Optimization
null
null
null
null
cs.LG cs.DC math.OC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We consider strongly convex-concave minimax problems in the federated setting, where the communication constraint is the main bottleneck. When clients are arbitrarily heterogeneous, a simple Minibatch Mirror-prox achieves the best performance. As the clients become more homogeneous, using multiple local gradient upda...
[ { "created": "Fri, 12 Feb 2021 02:55:36 GMT", "version": "v1" } ]
2021-02-15
[ [ "Hou", "Charlie", "" ], [ "Thekumparampil", "Kiran K.", "" ], [ "Fanti", "Giulia", "" ], [ "Oh", "Sewoong", "" ] ]
We consider strongly convex-concave minimax problems in the federated setting, where the communication constraint is the main bottleneck. When clients are arbitrarily heterogeneous, a simple Minibatch Mirror-prox achieves the best performance. As the clients become more homogeneous, using multiple local gradient update...
2401.09294
Junwon Lee
Yoonjin Chung, Junwon Lee, Juhan Nam
T-FOLEY: A Controllable Waveform-Domain Diffusion Model for Temporal-Event-Guided Foley Sound Synthesis
null
null
null
null
cs.SD cs.AI cs.LG eess.AS eess.SP
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Foley sound, audio content inserted synchronously with videos, plays a critical role in the user experience of multimedia content. Recently, there has been active research in Foley sound synthesis, leveraging the advancements in deep generative models. However, such works mainly focus on replicating a single sound cl...
[ { "created": "Wed, 17 Jan 2024 15:54:36 GMT", "version": "v1" } ]
2024-01-18
[ [ "Chung", "Yoonjin", "" ], [ "Lee", "Junwon", "" ], [ "Nam", "Juhan", "" ] ]
Foley sound, audio content inserted synchronously with videos, plays a critical role in the user experience of multimedia content. Recently, there has been active research in Foley sound synthesis, leveraging the advancements in deep generative models. However, such works mainly focus on replicating a single sound clas...
2007.04171
Jian Liang
Jian Liang and Dapeng Hu and Jiashi Feng
Domain Adaptation with Auxiliary Target Domain-Oriented Classifier
Fix typos after CVPR 2021. Code is available at https://github.com/tim-learn/ATDOC
null
null
null
cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Domain adaptation (DA) aims to transfer knowledge from a label-rich but heterogeneous domain to a label-scare domain, which alleviates the labeling efforts and attracts considerable attention. Different from previous methods focusing on learning domain-invariant feature representations, some recent methods present ge...
[ { "created": "Wed, 8 Jul 2020 15:01:35 GMT", "version": "v1" }, { "created": "Mon, 14 Dec 2020 03:27:55 GMT", "version": "v2" }, { "created": "Thu, 25 Mar 2021 13:52:35 GMT", "version": "v3" }, { "created": "Wed, 24 Nov 2021 02:01:44 GMT", "version": "v4" }, { "cr...
2021-12-17
[ [ "Liang", "Jian", "" ], [ "Hu", "Dapeng", "" ], [ "Feng", "Jiashi", "" ] ]
Domain adaptation (DA) aims to transfer knowledge from a label-rich but heterogeneous domain to a label-scare domain, which alleviates the labeling efforts and attracts considerable attention. Different from previous methods focusing on learning domain-invariant feature representations, some recent methods present gene...
2203.09430
Tian Ye
Tian Ye, Yun Liu, Yunchen Zhang, Sixiang Chen, Erkang Chen
Mutual Learning for Domain Adaptation: Self-distillation Image Dehazing Network with Sample-cycle
null
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Deep learning-based methods have made significant achievements for image dehazing. However, most of existing dehazing networks are concentrated on training models using simulated hazy images, resulting in generalization performance degradation when applied on real-world hazy images because of domain shift. In this pa...
[ { "created": "Thu, 17 Mar 2022 16:32:14 GMT", "version": "v1" } ]
2022-03-18
[ [ "Ye", "Tian", "" ], [ "Liu", "Yun", "" ], [ "Zhang", "Yunchen", "" ], [ "Chen", "Sixiang", "" ], [ "Chen", "Erkang", "" ] ]
Deep learning-based methods have made significant achievements for image dehazing. However, most of existing dehazing networks are concentrated on training models using simulated hazy images, resulting in generalization performance degradation when applied on real-world hazy images because of domain shift. In this pape...
2203.02824
Dhruv Rohatgi
Jonathan A. Kelner, Frederic Koehler, Raghu Meka, Dhruv Rohatgi
Distributional Hardness Against Preconditioned Lasso via Erasure-Robust Designs
39 pages
null
null
null
cs.DS cs.IT cs.LG math.IT math.ST stat.ML stat.TH
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Sparse linear regression with ill-conditioned Gaussian random designs is widely believed to exhibit a statistical/computational gap, but there is surprisingly little formal evidence for this belief, even in the form of examples that are hard for restricted classes of algorithms. Recent work has shown that, for certai...
[ { "created": "Sat, 5 Mar 2022 22:16:05 GMT", "version": "v1" } ]
2022-03-08
[ [ "Kelner", "Jonathan A.", "" ], [ "Koehler", "Frederic", "" ], [ "Meka", "Raghu", "" ], [ "Rohatgi", "Dhruv", "" ] ]
Sparse linear regression with ill-conditioned Gaussian random designs is widely believed to exhibit a statistical/computational gap, but there is surprisingly little formal evidence for this belief, even in the form of examples that are hard for restricted classes of algorithms. Recent work has shown that, for certain ...
0712.3348
Xin Li
Xin Li, Tian Liu
On Exponential Time Lower Bound of Knapsack under Backtracking
This paper supersedes the result of arXiv:cs/0606064
null
null
null
cs.CC
null
M.Aleknovich et al. have recently proposed a model of algorithms, called BT model, which generalizes both the priority model of Borodin, Nielson and Rackoff, as well as a simple dynamic programming model by Woeginger. BT model can be further divided into three kinds of fixed, adaptive and fully adaptive ones. They ha...
[ { "created": "Thu, 20 Dec 2007 09:15:17 GMT", "version": "v1" }, { "created": "Tue, 25 Dec 2007 13:46:53 GMT", "version": "v2" } ]
2007-12-25
[ [ "Li", "Xin", "" ], [ "Liu", "Tian", "" ] ]
M.Aleknovich et al. have recently proposed a model of algorithms, called BT model, which generalizes both the priority model of Borodin, Nielson and Rackoff, as well as a simple dynamic programming model by Woeginger. BT model can be further divided into three kinds of fixed, adaptive and fully adaptive ones. They have...
1902.03487
Mathew Halm
Mathew Halm, Michael Posa
A Quasi-static Model and Simulation Approach for Pushing, Grasping, and Jamming
WAFR 2018
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Quasi-static models of robotic motion with frictional contact provide a computationally efficient framework for analysis and have been widely used for planning and control of non-prehensile manipulation. In this work, we present a novel quasi-static model of planar manipulation that directly maps commanded manipulato...
[ { "created": "Sat, 9 Feb 2019 20:50:02 GMT", "version": "v1" } ]
2019-02-12
[ [ "Halm", "Mathew", "" ], [ "Posa", "Michael", "" ] ]
Quasi-static models of robotic motion with frictional contact provide a computationally efficient framework for analysis and have been widely used for planning and control of non-prehensile manipulation. In this work, we present a novel quasi-static model of planar manipulation that directly maps commanded manipulator ...
2205.13492
Andrea Cini
Andrea Cini, Daniele Zambon, Cesare Alippi
Sparse Graph Learning from Spatiotemporal Time Series
Accepted for publication in JMLR
Journal of Machine Learning Research 24 (2023) 1-36
null
null
cs.LG cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Outstanding achievements of graph neural networks for spatiotemporal time series analysis show that relational constraints introduce an effective inductive bias into neural forecasting architectures. Often, however, the relational information characterizing the underlying data-generating process is unavailable and th...
[ { "created": "Thu, 26 May 2022 17:02:43 GMT", "version": "v1" }, { "created": "Tue, 8 Nov 2022 10:31:52 GMT", "version": "v2" }, { "created": "Wed, 2 Aug 2023 11:02:52 GMT", "version": "v3" } ]
2023-08-03
[ [ "Cini", "Andrea", "" ], [ "Zambon", "Daniele", "" ], [ "Alippi", "Cesare", "" ] ]
Outstanding achievements of graph neural networks for spatiotemporal time series analysis show that relational constraints introduce an effective inductive bias into neural forecasting architectures. Often, however, the relational information characterizing the underlying data-generating process is unavailable and the ...
2301.00134
Rasha Kashef
Eleonora Achiluzzi, Menglu Li, Md Fahd Al Georgy, and Rasha Kashef
Exploring the Use of Data-Driven Approaches for Anomaly Detection in the Internet of Things (IoT) Environment
1 figure, 4 tables, and 8 pages
null
null
null
cs.LG
http://creativecommons.org/licenses/by-nc-nd/4.0/
The Internet of Things (IoT) is a system that connects physical computing devices, sensors, software, and other technologies. Data can be collected, transferred, and exchanged with other devices over the network without requiring human interactions. One challenge the development of IoT faces is the existence of anoma...
[ { "created": "Sat, 31 Dec 2022 06:28:58 GMT", "version": "v1" } ]
2023-01-03
[ [ "Achiluzzi", "Eleonora", "" ], [ "Li", "Menglu", "" ], [ "Georgy", "Md Fahd Al", "" ], [ "Kashef", "Rasha", "" ] ]
The Internet of Things (IoT) is a system that connects physical computing devices, sensors, software, and other technologies. Data can be collected, transferred, and exchanged with other devices over the network without requiring human interactions. One challenge the development of IoT faces is the existence of anomaly...
1812.10193
Aria Rezaei
Aria Rezaei, Chaowei Xiao, Jie Gao, Bo Li, Sirajum Munir
Application-driven Privacy-preserving Data Publishing with Correlated Attributes
12 pages
null
null
null
cs.LG cs.CR stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recent advances in computing have allowed for the possibility to collect large amounts of data on personal activities and private living spaces. To address the privacy concerns of users in this environment, we propose a novel framework called PR-GAN that offers privacy-preserving mechanism using generative adversaria...
[ { "created": "Wed, 26 Dec 2018 01:01:16 GMT", "version": "v1" }, { "created": "Tue, 5 Jan 2021 02:43:15 GMT", "version": "v2" } ]
2021-01-06
[ [ "Rezaei", "Aria", "" ], [ "Xiao", "Chaowei", "" ], [ "Gao", "Jie", "" ], [ "Li", "Bo", "" ], [ "Munir", "Sirajum", "" ] ]
Recent advances in computing have allowed for the possibility to collect large amounts of data on personal activities and private living spaces. To address the privacy concerns of users in this environment, we propose a novel framework called PR-GAN that offers privacy-preserving mechanism using generative adversarial ...
2407.21347
David Zagardo
David Zagardo
Differentially Private Block-wise Gradient Shuffle for Deep Learning
43 pages, 11 figures, 8 tables
null
null
null
cs.LG cs.AI cs.CR
http://creativecommons.org/licenses/by-nc-sa/4.0/
Traditional Differentially Private Stochastic Gradient Descent (DP-SGD) introduces statistical noise on top of gradients drawn from a Gaussian distribution to ensure privacy. This paper introduces the novel Differentially Private Block-wise Gradient Shuffle (DP-BloGS) algorithm for deep learning. BloGS builds off of ...
[ { "created": "Wed, 31 Jul 2024 05:32:37 GMT", "version": "v1" } ]
2024-08-01
[ [ "Zagardo", "David", "" ] ]
Traditional Differentially Private Stochastic Gradient Descent (DP-SGD) introduces statistical noise on top of gradients drawn from a Gaussian distribution to ensure privacy. This paper introduces the novel Differentially Private Block-wise Gradient Shuffle (DP-BloGS) algorithm for deep learning. BloGS builds off of ex...
2105.12392
Ming Shen
Ming Shen, Pratyay Banerjee, Chitta Baral
Unsupervised Pronoun Resolution via Masked Noun-Phrase Prediction
Accepted to ACL2021
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this work, we propose Masked Noun-Phrase Prediction (MNPP), a pre-training strategy to tackle pronoun resolution in a fully unsupervised setting. Firstly, We evaluate our pre-trained model on various pronoun resolution datasets without any finetuning. Our method outperforms all previous unsupervised methods on all...
[ { "created": "Wed, 26 May 2021 08:30:18 GMT", "version": "v1" }, { "created": "Fri, 28 May 2021 08:46:21 GMT", "version": "v2" } ]
2021-05-31
[ [ "Shen", "Ming", "" ], [ "Banerjee", "Pratyay", "" ], [ "Baral", "Chitta", "" ] ]
In this work, we propose Masked Noun-Phrase Prediction (MNPP), a pre-training strategy to tackle pronoun resolution in a fully unsupervised setting. Firstly, We evaluate our pre-trained model on various pronoun resolution datasets without any finetuning. Our method outperforms all previous unsupervised methods on all d...
2308.08230
Xue Xinghua
Xinghua Xue, Cheng Liu, Bo Liu, Haitong Huang, Ying Wang, Tao Luo, Lei Zhang, Huawei Li, Xiaowei Li
Exploring Winograd Convolution for Cost-effective Neural Network Fault Tolerance
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Winograd is generally utilized to optimize convolution performance and computational efficiency because of the reduced multiplication operations, but the reliability issues brought by winograd are usually overlooked. In this work, we observe the great potential of winograd convolution in improving neural network (NN)...
[ { "created": "Wed, 16 Aug 2023 09:03:13 GMT", "version": "v1" } ]
2023-08-17
[ [ "Xue", "Xinghua", "" ], [ "Liu", "Cheng", "" ], [ "Liu", "Bo", "" ], [ "Huang", "Haitong", "" ], [ "Wang", "Ying", "" ], [ "Luo", "Tao", "" ], [ "Zhang", "Lei", "" ], [ "Li", "Huawei", "" ...
Winograd is generally utilized to optimize convolution performance and computational efficiency because of the reduced multiplication operations, but the reliability issues brought by winograd are usually overlooked. In this work, we observe the great potential of winograd convolution in improving neural network (NN) f...
1809.10884
Nalin Asanka Gamagedara Arachchilage
Awanthika Senarath, Marthie Grobler and Nalin Asanka Gamagedara Arachchilage
A model for system developers to measure the privacy risk of data
10
The 52nd Hawaii International Conference on System Sciences (HICSS), 2019
null
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we propose a model that could be used by system developers to measure the privacy risk perceived by users when they disclose data into software systems. We first derive a model to measure the perceived privacy risk based on existing knowledge and then we test our model through a survey with 151 partici...
[ { "created": "Fri, 28 Sep 2018 07:11:37 GMT", "version": "v1" } ]
2018-10-01
[ [ "Senarath", "Awanthika", "" ], [ "Grobler", "Marthie", "" ], [ "Arachchilage", "Nalin Asanka Gamagedara", "" ] ]
In this paper, we propose a model that could be used by system developers to measure the privacy risk perceived by users when they disclose data into software systems. We first derive a model to measure the perceived privacy risk based on existing knowledge and then we test our model through a survey with 151 participa...
1703.08614
Charles Packer
Charles A. Packer, Lawrence B. Holder
GraphZip: Dictionary-based Compression for Mining Graph Streams
null
null
null
null
cs.SI cs.DB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A massive amount of data generated today on platforms such as social networks, telecommunication networks, and the internet in general can be represented as graph streams. Activity in a network's underlying graph generates a sequence of edges in the form of a stream; for example, a social network may generate a graph...
[ { "created": "Fri, 24 Mar 2017 22:08:00 GMT", "version": "v1" } ]
2017-03-28
[ [ "Packer", "Charles A.", "" ], [ "Holder", "Lawrence B.", "" ] ]
A massive amount of data generated today on platforms such as social networks, telecommunication networks, and the internet in general can be represented as graph streams. Activity in a network's underlying graph generates a sequence of edges in the form of a stream; for example, a social network may generate a graph s...
2006.07309
Fateme Bafghi
Fateme Bafghi, Bijan Shoushtarian
Multiple-Vehicle Tracking in the Highway Using Appearance Model and Visual Object Tracking
null
null
10.1109/MVIP49855.2020.9116905
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In recent decades, due to the groundbreaking improvements in machine vision, many daily tasks are performed by computers. One of these tasks is multiple-vehicle tracking, which is widely used in different areas such as video surveillance and traffic monitoring. This paper focuses on introducing an efficient novel app...
[ { "created": "Fri, 12 Jun 2020 16:46:12 GMT", "version": "v1" } ]
2020-07-07
[ [ "Bafghi", "Fateme", "" ], [ "Shoushtarian", "Bijan", "" ] ]
In recent decades, due to the groundbreaking improvements in machine vision, many daily tasks are performed by computers. One of these tasks is multiple-vehicle tracking, which is widely used in different areas such as video surveillance and traffic monitoring. This paper focuses on introducing an efficient novel appro...
1808.07851
Alexander Panchenko
Alexander Panchenko
Sentiment Index of the Russian Speaking Facebook
In Proceedings of the 20th International Conference on Computational Linguistics and Intellectual Technologies (Dialogue'2014). Moscow, Russia. RGGU
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
A sentiment index measures the average emotional level in a corpus. We introduce four such indexes and use them to gauge average "positiveness" of a population during some period based on posts in a social network. This article for the first time presents a text-, rather than word-based sentiment index. Furthermore, ...
[ { "created": "Thu, 23 Aug 2018 17:24:42 GMT", "version": "v1" } ]
2018-08-24
[ [ "Panchenko", "Alexander", "" ] ]
A sentiment index measures the average emotional level in a corpus. We introduce four such indexes and use them to gauge average "positiveness" of a population during some period based on posts in a social network. This article for the first time presents a text-, rather than word-based sentiment index. Furthermore, th...
2004.00116
Xuesu Xiao
Xuesu Xiao, Bo Liu, Garrett Warnell, Jonathan Fink, Peter Stone
APPLD: Adaptive Planner Parameter Learning from Demonstration
Accepted by Robotics and Automation Letters (RAL) and International Conference on Intelligent Robots and Systems (IROS) 2020
null
null
null
cs.RO cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Existing autonomous robot navigation systems allow robots to move from one point to another in a collision-free manner. However, when facing new environments, these systems generally require re-tuning by expert roboticists with a good understanding of the inner workings of the navigation system. In contrast, even use...
[ { "created": "Tue, 31 Mar 2020 21:15:16 GMT", "version": "v1" }, { "created": "Thu, 4 Jun 2020 02:35:37 GMT", "version": "v2" }, { "created": "Sat, 6 Jun 2020 03:22:45 GMT", "version": "v3" }, { "created": "Wed, 15 Jul 2020 18:35:10 GMT", "version": "v4" } ]
2020-07-17
[ [ "Xiao", "Xuesu", "" ], [ "Liu", "Bo", "" ], [ "Warnell", "Garrett", "" ], [ "Fink", "Jonathan", "" ], [ "Stone", "Peter", "" ] ]
Existing autonomous robot navigation systems allow robots to move from one point to another in a collision-free manner. However, when facing new environments, these systems generally require re-tuning by expert roboticists with a good understanding of the inner workings of the navigation system. In contrast, even users...
1607.06890
Wei Shi
Hao Jan Liu, Wei Shi, and Hao Zhu
Decentralized Dynamic Optimization for Power Network Voltage Control
null
null
null
null
cs.SY math.OC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Voltage control in power distribution networks has been greatly challenged by the increasing penetration of volatile and intermittent devices. These devices can also provide limited reactive power resources that can be used to regulate the network-wide voltage. A decentralized voltage control strategy can be designed...
[ { "created": "Sat, 23 Jul 2016 04:49:25 GMT", "version": "v1" } ]
2016-07-26
[ [ "Liu", "Hao Jan", "" ], [ "Shi", "Wei", "" ], [ "Zhu", "Hao", "" ] ]
Voltage control in power distribution networks has been greatly challenged by the increasing penetration of volatile and intermittent devices. These devices can also provide limited reactive power resources that can be used to regulate the network-wide voltage. A decentralized voltage control strategy can be designed b...
2108.12594
Jiwei Li
Chun Fan, Jiwei Li, Xiang Ao, Fei Wu, Yuxian Meng, Xiaofei Sun
Layer-wise Model Pruning based on Mutual Information
To appear at EMNLP2021
null
null
null
cs.CL cs.AI cs.LG
http://creativecommons.org/licenses/by/4.0/
The proposed pruning strategy offers merits over weight-based pruning techniques: (1) it avoids irregular memory access since representations and matrices can be squeezed into their smaller but dense counterparts, leading to greater speedup; (2) in a manner of top-down pruning, the proposed method operates from a mor...
[ { "created": "Sat, 28 Aug 2021 07:51:47 GMT", "version": "v1" } ]
2021-08-31
[ [ "Fan", "Chun", "" ], [ "Li", "Jiwei", "" ], [ "Ao", "Xiang", "" ], [ "Wu", "Fei", "" ], [ "Meng", "Yuxian", "" ], [ "Sun", "Xiaofei", "" ] ]
The proposed pruning strategy offers merits over weight-based pruning techniques: (1) it avoids irregular memory access since representations and matrices can be squeezed into their smaller but dense counterparts, leading to greater speedup; (2) in a manner of top-down pruning, the proposed method operates from a more ...
2101.06644
Theophile Sautory
Theophile Sautory, Nuri Cingillioglu, Alessandra Russo
HySTER: A Hybrid Spatio-Temporal Event Reasoner
Preprint accepted by the 35th AAAI Conference on Artificial Intelligence (AAAI-21) Workshop on Hybrid Artificial Intelligence (HAI)
null
null
null
cs.CV cs.AI cs.CL cs.LO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The task of Video Question Answering (VideoQA) consists in answering natural language questions about a video and serves as a proxy to evaluate the performance of a model in scene sequence understanding. Most methods designed for VideoQA up-to-date are end-to-end deep learning architectures which struggle at complex ...
[ { "created": "Sun, 17 Jan 2021 11:07:17 GMT", "version": "v1" } ]
2021-01-19
[ [ "Sautory", "Theophile", "" ], [ "Cingillioglu", "Nuri", "" ], [ "Russo", "Alessandra", "" ] ]
The task of Video Question Answering (VideoQA) consists in answering natural language questions about a video and serves as a proxy to evaluate the performance of a model in scene sequence understanding. Most methods designed for VideoQA up-to-date are end-to-end deep learning architectures which struggle at complex te...
1908.02121
Manny Rayner
Cathy Chua and Manny Rayner
What do the founders of online communities owe to their users?
6 pages. Paper based on talk at enetCollect WG3 & WG5 Meeting, Leiden 2018
CEUR Workshop Proceedings vol 2390, 2019. http://ceur-ws.org/Vol-2390/
null
null
cs.CY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We discuss the organisation of internet communities, focusing on what we call the principle of "bait and switch": founders of internet communities often find it advantageous to recruit members by promising inducements which are later not honoured. We look at some of the dilemmas and ways of attempting to resolve them...
[ { "created": "Tue, 30 Jul 2019 12:57:33 GMT", "version": "v1" } ]
2019-08-07
[ [ "Chua", "Cathy", "" ], [ "Rayner", "Manny", "" ] ]
We discuss the organisation of internet communities, focusing on what we call the principle of "bait and switch": founders of internet communities often find it advantageous to recruit members by promising inducements which are later not honoured. We look at some of the dilemmas and ways of attempting to resolve them t...
2002.07676
Claire Lazar Reich
Claire Lazar Reich and Suhas Vijaykumar
A Possibility in Algorithmic Fairness: Can Calibration and Equal Error Rates Be Reconciled?
2nd Symposium on Foundations of Responsible Computing (FORC 2021) https://drops.dagstuhl.de/opus/volltexte/2021/13872/
null
10.4230/LIPIcs.FORC.2021.4
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Decision makers increasingly rely on algorithmic risk scores to determine access to binary treatments including bail, loans, and medical interventions. In these settings, we reconcile two fairness criteria that were previously shown to be in conflict: calibration and error rate equality. In particular, we derive nece...
[ { "created": "Tue, 18 Feb 2020 16:03:09 GMT", "version": "v1" }, { "created": "Wed, 15 Jul 2020 15:09:40 GMT", "version": "v2" }, { "created": "Mon, 7 Jun 2021 20:41:16 GMT", "version": "v3" } ]
2021-06-09
[ [ "Reich", "Claire Lazar", "" ], [ "Vijaykumar", "Suhas", "" ] ]
Decision makers increasingly rely on algorithmic risk scores to determine access to binary treatments including bail, loans, and medical interventions. In these settings, we reconcile two fairness criteria that were previously shown to be in conflict: calibration and error rate equality. In particular, we derive necess...
2401.10580
Sigurd Schacht
Matthias Uhlig, Sigurd Schacht, Sudarshan Kamath Barkur
PHOENIX: Open-Source Language Adaption for Direct Preference Optimization
null
null
null
null
cs.CL
http://creativecommons.org/licenses/by-sa/4.0/
Large language models have gained immense importance in recent years and have demonstrated outstanding results in solving various tasks. However, despite these achievements, many questions remain unanswered in the context of large language models. Besides the optimal use of the models for inference and the alignment ...
[ { "created": "Fri, 19 Jan 2024 09:46:08 GMT", "version": "v1" } ]
2024-01-22
[ [ "Uhlig", "Matthias", "" ], [ "Schacht", "Sigurd", "" ], [ "Barkur", "Sudarshan Kamath", "" ] ]
Large language models have gained immense importance in recent years and have demonstrated outstanding results in solving various tasks. However, despite these achievements, many questions remain unanswered in the context of large language models. Besides the optimal use of the models for inference and the alignment of...
2106.07268
Young D. Kwon
Young D. Kwon, Jagmohan Chauhan, and Cecilia Mascolo
FastICARL: Fast Incremental Classifier and Representation Learning with Efficient Budget Allocation in Audio Sensing Applications
Accepted for publication at INTERSPEECH 2021
null
null
null
cs.SD cs.LG eess.AS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Various incremental learning (IL) approaches have been proposed to help deep learning models learn new tasks/classes continuously without forgetting what was learned previously (i.e., avoid catastrophic forgetting). With the growing number of deployed audio sensing applications that need to dynamically incorporate ne...
[ { "created": "Mon, 14 Jun 2021 09:42:58 GMT", "version": "v1" }, { "created": "Thu, 24 Jun 2021 19:32:30 GMT", "version": "v2" } ]
2021-06-28
[ [ "Kwon", "Young D.", "" ], [ "Chauhan", "Jagmohan", "" ], [ "Mascolo", "Cecilia", "" ] ]
Various incremental learning (IL) approaches have been proposed to help deep learning models learn new tasks/classes continuously without forgetting what was learned previously (i.e., avoid catastrophic forgetting). With the growing number of deployed audio sensing applications that need to dynamically incorporate new ...
2305.11870
Byungjun Kim
Byungjun Kim, Patrick Kwon, Kwangho Lee, Myunggi Lee, Sookwan Han, Daesik Kim, Hanbyul Joo
Chupa: Carving 3D Clothed Humans from Skinned Shape Priors using 2D Diffusion Probabilistic Models
Project Page: https://snuvclab.github.io/chupa/
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
We propose a 3D generation pipeline that uses diffusion models to generate realistic human digital avatars. Due to the wide variety of human identities, poses, and stochastic details, the generation of 3D human meshes has been a challenging problem. To address this, we decompose the problem into 2D normal map generat...
[ { "created": "Fri, 19 May 2023 17:59:18 GMT", "version": "v1" }, { "created": "Mon, 29 May 2023 07:38:33 GMT", "version": "v2" }, { "created": "Fri, 15 Sep 2023 12:23:21 GMT", "version": "v3" } ]
2023-09-18
[ [ "Kim", "Byungjun", "" ], [ "Kwon", "Patrick", "" ], [ "Lee", "Kwangho", "" ], [ "Lee", "Myunggi", "" ], [ "Han", "Sookwan", "" ], [ "Kim", "Daesik", "" ], [ "Joo", "Hanbyul", "" ] ]
We propose a 3D generation pipeline that uses diffusion models to generate realistic human digital avatars. Due to the wide variety of human identities, poses, and stochastic details, the generation of 3D human meshes has been a challenging problem. To address this, we decompose the problem into 2D normal map generatio...
1806.08238
Niranjan Saikumar
Linda Chen, Niranjan Saikumar and S. Hassan HosseinNia
Development of Robust Fractional-Order Reset Control
arXiv admin note: text overlap with arXiv:1805.10037
null
10.1109/TCST.2019.2913534
null
cs.SY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, a framework for the combination of robust fractional order CRONE control with non-linear reset is given for both first and second generation CRONE control. General design rules are derived and presented for these CRONE reset controllers. Within this framework, fractional order control allows for better...
[ { "created": "Wed, 20 Jun 2018 11:44:13 GMT", "version": "v1" }, { "created": "Mon, 24 Dec 2018 12:59:17 GMT", "version": "v2" }, { "created": "Tue, 1 Oct 2019 16:51:35 GMT", "version": "v3" } ]
2019-10-02
[ [ "Chen", "Linda", "" ], [ "Saikumar", "Niranjan", "" ], [ "HosseinNia", "S. Hassan", "" ] ]
In this paper, a framework for the combination of robust fractional order CRONE control with non-linear reset is given for both first and second generation CRONE control. General design rules are derived and presented for these CRONE reset controllers. Within this framework, fractional order control allows for better t...
2405.19449
Amy Koike
Amy Koike, Bengisu Cagiltay, Bilge Mutlu
Tangible Scenography as a Holistic Design Method for Human-Robot Interaction
null
null
10.1145/3643834.3661530
null
cs.HC
http://creativecommons.org/licenses/by-nc-nd/4.0/
Traditional approaches to human-robot interaction design typically examine robot behaviors in controlled environments and narrow tasks. These methods are impractical for designing robots that interact with diverse user groups in complex human environments. Drawing from the field of theater, we present the construct o...
[ { "created": "Wed, 29 May 2024 18:55:13 GMT", "version": "v1" }, { "created": "Sun, 2 Jun 2024 02:57:19 GMT", "version": "v2" } ]
2024-06-04
[ [ "Koike", "Amy", "" ], [ "Cagiltay", "Bengisu", "" ], [ "Mutlu", "Bilge", "" ] ]
Traditional approaches to human-robot interaction design typically examine robot behaviors in controlled environments and narrow tasks. These methods are impractical for designing robots that interact with diverse user groups in complex human environments. Drawing from the field of theater, we present the construct of ...
2202.06708
Florian Nelles
Stefan Kratsch, Florian Nelles, Alexandre Simon
On Triangle Counting Parameterized by Twin-Width
6 pages
null
null
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this report we present an algorithm solving Triangle Counting in time $O(d^2n+m)$, where n and m, respectively, denote the number of vertices and edges of a graph G and d denotes its twin-width, a recently introduced graph parameter. We assume that a compact representation of a d-contraction sequence of G is given...
[ { "created": "Mon, 14 Feb 2022 13:58:36 GMT", "version": "v1" } ]
2022-02-15
[ [ "Kratsch", "Stefan", "" ], [ "Nelles", "Florian", "" ], [ "Simon", "Alexandre", "" ] ]
In this report we present an algorithm solving Triangle Counting in time $O(d^2n+m)$, where n and m, respectively, denote the number of vertices and edges of a graph G and d denotes its twin-width, a recently introduced graph parameter. We assume that a compact representation of a d-contraction sequence of G is given.
2309.05678
Alvaro Arroyo
Haitz Saez de Ocariz Borde, Alvaro Arroyo, Ismael Morales, Ingmar Posner, Xiaowen Dong
Gromov-Hausdorff Distances for Comparing Product Manifolds of Model Spaces
arXiv admin note: substantial text overlap with arXiv:2309.04810
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recent studies propose enhancing machine learning models by aligning the geometric characteristics of the latent space with the underlying data structure. Instead of relying solely on Euclidean space, researchers have suggested using hyperbolic and spherical spaces with constant curvature, or their combinations (know...
[ { "created": "Sat, 9 Sep 2023 11:17:06 GMT", "version": "v1" } ]
2023-09-13
[ [ "Borde", "Haitz Saez de Ocariz", "" ], [ "Arroyo", "Alvaro", "" ], [ "Morales", "Ismael", "" ], [ "Posner", "Ingmar", "" ], [ "Dong", "Xiaowen", "" ] ]
Recent studies propose enhancing machine learning models by aligning the geometric characteristics of the latent space with the underlying data structure. Instead of relying solely on Euclidean space, researchers have suggested using hyperbolic and spherical spaces with constant curvature, or their combinations (known ...
2405.13062
Pavlos Bouzinis
Pavlos S. Bouzinis, Panagiotis Radoglou-Grammatikis, Ioannis Makris, Thomas Lagkas, Vasileios Argyriou, Georgios Th. Papadopoulos, Panagiotis Sarigiannidis, George K. Karagiannidis
StatAvg: Mitigating Data Heterogeneity in Federated Learning for Intrusion Detection Systems
10 pages, 8 figures
null
null
null
cs.CR cs.AI cs.DC cs.LG
http://creativecommons.org/licenses/by/4.0/
Federated learning (FL) is a decentralized learning technique that enables participating devices to collaboratively build a shared Machine Leaning (ML) or Deep Learning (DL) model without revealing their raw data to a third party. Due to its privacy-preserving nature, FL has sparked widespread attention for building ...
[ { "created": "Mon, 20 May 2024 14:41:59 GMT", "version": "v1" } ]
2024-05-24
[ [ "Bouzinis", "Pavlos S.", "" ], [ "Radoglou-Grammatikis", "Panagiotis", "" ], [ "Makris", "Ioannis", "" ], [ "Lagkas", "Thomas", "" ], [ "Argyriou", "Vasileios", "" ], [ "Papadopoulos", "Georgios Th.", "" ], [ "Sari...
Federated learning (FL) is a decentralized learning technique that enables participating devices to collaboratively build a shared Machine Leaning (ML) or Deep Learning (DL) model without revealing their raw data to a third party. Due to its privacy-preserving nature, FL has sparked widespread attention for building In...
0804.4565
Kees Middelburg
J. A. Bergstra, C. A. Middelburg
Data linkage algebra, data linkage dynamics, and priority rewriting
48 pages, typos corrected, phrasing improved, definition of services replaced; presentation improved; presentation improved and appendix added
Fundamenta Informaticae, 128(4):367--412, 2013
10.3233/FI-2013-950
PRG0806
cs.LO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We introduce an algebra of data linkages. Data linkages are intended for modelling the states of computations in which dynamic data structures are involved. We present a simple model of computation in which states of computations are modelled as data linkages and state changes take place by means of certain actions. ...
[ { "created": "Tue, 29 Apr 2008 09:55:33 GMT", "version": "v1" }, { "created": "Wed, 18 Jun 2008 05:48:10 GMT", "version": "v2" }, { "created": "Tue, 16 Oct 2012 11:31:42 GMT", "version": "v3" }, { "created": "Wed, 5 Jun 2013 09:46:25 GMT", "version": "v4" } ]
2013-11-18
[ [ "Bergstra", "J. A.", "" ], [ "Middelburg", "C. A.", "" ] ]
We introduce an algebra of data linkages. Data linkages are intended for modelling the states of computations in which dynamic data structures are involved. We present a simple model of computation in which states of computations are modelled as data linkages and state changes take place by means of certain actions. We...
2310.00706
Dareen Alharthi Safar
Dareen Alharthi, Roshan Sharma, Hira Dhamyal, Soumi Maiti, Bhiksha Raj, Rita Singh
Evaluating Speech Synthesis by Training Recognizers on Synthetic Speech
null
null
null
null
cs.CL cs.SD eess.AS
http://creativecommons.org/licenses/by/4.0/
Modern speech synthesis systems have improved significantly, with synthetic speech being indistinguishable from real speech. However, efficient and holistic evaluation of synthetic speech still remains a significant challenge. Human evaluation using Mean Opinion Score (MOS) is ideal, but inefficient due to high costs...
[ { "created": "Sun, 1 Oct 2023 15:52:48 GMT", "version": "v1" } ]
2023-10-03
[ [ "Alharthi", "Dareen", "" ], [ "Sharma", "Roshan", "" ], [ "Dhamyal", "Hira", "" ], [ "Maiti", "Soumi", "" ], [ "Raj", "Bhiksha", "" ], [ "Singh", "Rita", "" ] ]
Modern speech synthesis systems have improved significantly, with synthetic speech being indistinguishable from real speech. However, efficient and holistic evaluation of synthetic speech still remains a significant challenge. Human evaluation using Mean Opinion Score (MOS) is ideal, but inefficient due to high costs. ...
2305.13805
Zilong Wang
Zilong Wang, Jingbo Shang
Towards Zero-shot Relation Extraction in Web Mining: A Multimodal Approach with Relative XML Path
null
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
The rapid growth of web pages and the increasing complexity of their structure poses a challenge for web mining models. Web mining models are required to understand the semi-structured web pages, particularly when little is known about the subject or template of a new page. Current methods migrate language models to ...
[ { "created": "Tue, 23 May 2023 08:16:52 GMT", "version": "v1" } ]
2023-05-24
[ [ "Wang", "Zilong", "" ], [ "Shang", "Jingbo", "" ] ]
The rapid growth of web pages and the increasing complexity of their structure poses a challenge for web mining models. Web mining models are required to understand the semi-structured web pages, particularly when little is known about the subject or template of a new page. Current methods migrate language models to th...