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2311.11230
Herve Kabamba
Herve Mbikayi Kabamba, Matthew Khouzam, Michel Dagenais
Advanced Strategies for Precise and Transparent Debugging of Performance Issues in In-Memory Data Store-Based Microservices
null
null
null
null
cs.DC
http://creativecommons.org/licenses/by-nc-nd/4.0/
The rise of microservice architectures has revolutionized application design, fostering adaptability and resilience. These architectures facilitate scaling and encourage collaborative efforts among specialized teams, streamlining deployment and maintenance. Critical to this ecosystem is the demand for low latency, pr...
[ { "created": "Sun, 19 Nov 2023 05:10:22 GMT", "version": "v1" } ]
2023-11-21
[ [ "Kabamba", "Herve Mbikayi", "" ], [ "Khouzam", "Matthew", "" ], [ "Dagenais", "Michel", "" ] ]
The rise of microservice architectures has revolutionized application design, fostering adaptability and resilience. These architectures facilitate scaling and encourage collaborative efforts among specialized teams, streamlining deployment and maintenance. Critical to this ecosystem is the demand for low latency, prom...
2402.02933
Vinitra Swamy
Vinitra Swamy, Syrielle Montariol, Julian Blackwell, Jibril Frej, Martin Jaggi, Tanja K\"aser
InterpretCC: Intrinsic User-Centric Interpretability through Global Mixture of Experts
null
null
null
null
cs.LG cs.CY cs.HC
http://creativecommons.org/licenses/by/4.0/
Interpretability for neural networks is a trade-off between three key requirements: 1) faithfulness of the explanation (i.e., how perfectly it explains the prediction), 2) understandability of the explanation by humans, and 3) model performance. Most existing methods compromise one or more of these requirements; e.g....
[ { "created": "Mon, 5 Feb 2024 11:55:50 GMT", "version": "v1" }, { "created": "Tue, 28 May 2024 14:58:26 GMT", "version": "v2" }, { "created": "Wed, 29 May 2024 12:03:40 GMT", "version": "v3" } ]
2024-05-30
[ [ "Swamy", "Vinitra", "" ], [ "Montariol", "Syrielle", "" ], [ "Blackwell", "Julian", "" ], [ "Frej", "Jibril", "" ], [ "Jaggi", "Martin", "" ], [ "Käser", "Tanja", "" ] ]
Interpretability for neural networks is a trade-off between three key requirements: 1) faithfulness of the explanation (i.e., how perfectly it explains the prediction), 2) understandability of the explanation by humans, and 3) model performance. Most existing methods compromise one or more of these requirements; e.g., ...
2207.01076
Mingzhe Guo
Mingzhe Guo, Zhipeng Zhang, Heng Fan, Liping Jing
Divert More Attention to Vision-Language Tracking
18 pages, 7 figures
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Relying on Transformer for complex visual feature learning, object tracking has witnessed the new standard for state-of-the-arts (SOTAs). However, this advancement accompanies by larger training data and longer training period, making tracking increasingly expensive. In this paper, we demonstrate that the Transformer...
[ { "created": "Sun, 3 Jul 2022 16:38:24 GMT", "version": "v1" } ]
2022-07-05
[ [ "Guo", "Mingzhe", "" ], [ "Zhang", "Zhipeng", "" ], [ "Fan", "Heng", "" ], [ "Jing", "Liping", "" ] ]
Relying on Transformer for complex visual feature learning, object tracking has witnessed the new standard for state-of-the-arts (SOTAs). However, this advancement accompanies by larger training data and longer training period, making tracking increasingly expensive. In this paper, we demonstrate that the Transformer-r...
2305.07988
Haochen Tan
Haochen Tan, Han Wu, Wei Shao, Xinyun Zhang, Mingjie Zhan, Zhaohui Hou, Ding Liang, Linqi Song
Reconstruct Before Summarize: An Efficient Two-Step Framework for Condensing and Summarizing Meeting Transcripts
Accepted to EMNLP 2023 main conference
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Meetings typically involve multiple participants and lengthy conversations, resulting in redundant and trivial content. To overcome these challenges, we propose a two-step framework, Reconstruct before Summarize (RbS), for effective and efficient meeting summarization. RbS first leverages a self-supervised paradigm t...
[ { "created": "Sat, 13 May 2023 19:54:46 GMT", "version": "v1" }, { "created": "Sun, 22 Oct 2023 17:42:44 GMT", "version": "v2" } ]
2023-10-24
[ [ "Tan", "Haochen", "" ], [ "Wu", "Han", "" ], [ "Shao", "Wei", "" ], [ "Zhang", "Xinyun", "" ], [ "Zhan", "Mingjie", "" ], [ "Hou", "Zhaohui", "" ], [ "Liang", "Ding", "" ], [ "Song", "Linqi", ...
Meetings typically involve multiple participants and lengthy conversations, resulting in redundant and trivial content. To overcome these challenges, we propose a two-step framework, Reconstruct before Summarize (RbS), for effective and efficient meeting summarization. RbS first leverages a self-supervised paradigm to ...
1909.00392
Tae Ha Park
Tae Ha Park, Sumant Sharma, Simone D'Amico
Towards Robust Learning-Based Pose Estimation of Noncooperative Spacecraft
Presented at 2019 AAS/AIAA Astrodynamics Specialist Conference
null
null
AAS 19-840
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This work presents a novel Convolutional Neural Network (CNN) architecture and a training procedure to enable robust and accurate pose estimation of a noncooperative spacecraft. First, a new CNN architecture is introduced that has scored a fourth place in the recent Pose Estimation Challenge hosted by Stanford's Spac...
[ { "created": "Sun, 1 Sep 2019 13:22:19 GMT", "version": "v1" } ]
2019-09-04
[ [ "Park", "Tae Ha", "" ], [ "Sharma", "Sumant", "" ], [ "D'Amico", "Simone", "" ] ]
This work presents a novel Convolutional Neural Network (CNN) architecture and a training procedure to enable robust and accurate pose estimation of a noncooperative spacecraft. First, a new CNN architecture is introduced that has scored a fourth place in the recent Pose Estimation Challenge hosted by Stanford's Space ...
2402.07945
Runliang Niu
Runliang Niu, Jindong Li, Shiqi Wang, Yali Fu, Xiyu Hu, Xueyuan Leng, He Kong, Yi Chang, Qi Wang
ScreenAgent: A Vision Language Model-driven Computer Control Agent
null
null
null
null
cs.HC cs.AI cs.CV
http://creativecommons.org/licenses/by/4.0/
Existing Large Language Models (LLM) can invoke a variety of tools and APIs to complete complex tasks. The computer, as the most powerful and universal tool, could potentially be controlled directly by a trained LLM agent. Powered by the computer, we can hopefully build a more generalized agent to assist humans in va...
[ { "created": "Fri, 9 Feb 2024 02:33:45 GMT", "version": "v1" } ]
2024-02-14
[ [ "Niu", "Runliang", "" ], [ "Li", "Jindong", "" ], [ "Wang", "Shiqi", "" ], [ "Fu", "Yali", "" ], [ "Hu", "Xiyu", "" ], [ "Leng", "Xueyuan", "" ], [ "Kong", "He", "" ], [ "Chang", "Yi", "" ...
Existing Large Language Models (LLM) can invoke a variety of tools and APIs to complete complex tasks. The computer, as the most powerful and universal tool, could potentially be controlled directly by a trained LLM agent. Powered by the computer, we can hopefully build a more generalized agent to assist humans in vari...
1706.09927
Cedomir Stefanovic
Federico Clazzer, Enrico Paolini, Iacopo Mambelli, Cedomir Stefanovic
Irregular Repetition Slotted ALOHA over the Rayleigh Block Fading Channel with Capture
Presented at ICC 2017
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Random access protocols relying on the transmission of packet replicas in multiple slots and exploiting interference cancellation at the receiver have been shown to achieve per- formance competitive with that of orthogonal schemes. So far the optimization of the repetition degree profile, defining the probability for...
[ { "created": "Thu, 29 Jun 2017 19:05:01 GMT", "version": "v1" } ]
2017-07-03
[ [ "Clazzer", "Federico", "" ], [ "Paolini", "Enrico", "" ], [ "Mambelli", "Iacopo", "" ], [ "Stefanovic", "Cedomir", "" ] ]
Random access protocols relying on the transmission of packet replicas in multiple slots and exploiting interference cancellation at the receiver have been shown to achieve per- formance competitive with that of orthogonal schemes. So far the optimization of the repetition degree profile, defining the probability for a...
0911.1972
Neal Patwari
Neal Patwari and Joey Wilson
People-Sensing Spatial Characteristics of RF Sensor Networks
null
null
null
null
cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
An "RF sensor" network can monitor RSS values on links in the network and perform device-free localization, i.e., locating a person or object moving in the area in which the network is deployed. This paper provides a statistical model for the RSS variance as a function of the person's position w.r.t. the transmitter ...
[ { "created": "Tue, 10 Nov 2009 19:31:07 GMT", "version": "v1" } ]
2009-11-11
[ [ "Patwari", "Neal", "" ], [ "Wilson", "Joey", "" ] ]
An "RF sensor" network can monitor RSS values on links in the network and perform device-free localization, i.e., locating a person or object moving in the area in which the network is deployed. This paper provides a statistical model for the RSS variance as a function of the person's position w.r.t. the transmitter (T...
1309.6036
Shamgar Gurevich
Alexander Fish and Shamgar Gurevich
Almost Linear Complexity Methods for Delay-Doppler Channel Estimation
4 double column pages. arXiv admin note: substantial text overlap with arXiv:1309.3720
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A fundamental task in wireless communication is channel estimation: Compute the channel parameters a signal undergoes while traveling from a transmitter to a receiver. In the case of delay-Doppler channel, i.e., a signal undergoes only delay and Doppler shifts, a widely used method to compute delay-Doppler parameters...
[ { "created": "Tue, 24 Sep 2013 03:30:27 GMT", "version": "v1" } ]
2013-09-25
[ [ "Fish", "Alexander", "" ], [ "Gurevich", "Shamgar", "" ] ]
A fundamental task in wireless communication is channel estimation: Compute the channel parameters a signal undergoes while traveling from a transmitter to a receiver. In the case of delay-Doppler channel, i.e., a signal undergoes only delay and Doppler shifts, a widely used method to compute delay-Doppler parameters i...
2110.09170
Jordan J. Bird
Jordan J. Bird
Continuation of Famous Art with AI: A Conditional Adversarial Network Inpainting Approach
null
null
null
null
cs.CV cs.GR
http://creativecommons.org/licenses/by-nc-sa/4.0/
Much of the state-of-the-art in image synthesis inspired by real artwork are either entirely generative by filtered random noise or inspired by the transfer of style. This work explores the application of image inpainting to continue famous artworks and produce generative art with a Conditional GAN. During the traini...
[ { "created": "Mon, 18 Oct 2021 10:39:32 GMT", "version": "v1" }, { "created": "Tue, 26 Oct 2021 18:23:51 GMT", "version": "v2" }, { "created": "Tue, 1 Feb 2022 14:13:18 GMT", "version": "v3" } ]
2022-02-02
[ [ "Bird", "Jordan J.", "" ] ]
Much of the state-of-the-art in image synthesis inspired by real artwork are either entirely generative by filtered random noise or inspired by the transfer of style. This work explores the application of image inpainting to continue famous artworks and produce generative art with a Conditional GAN. During the training...
2211.13737
Dongdong Lin
Dongdong Lin, Benedetta Tondi, Bin Li, Mauro Barni
CycleGANWM: A CycleGAN watermarking method for ownership verification
There is an crucial error in Figure 1, where the "watermark" should be modified
null
null
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Due to the proliferation and widespread use of deep neural networks (DNN), their Intellectual Property Rights (IPR) protection has become increasingly important. This paper presents a novel model watermarking method for an unsupervised image-to-image translation (I2IT) networks, named CycleGAN, which leverage the ima...
[ { "created": "Thu, 24 Nov 2022 17:56:45 GMT", "version": "v1" }, { "created": "Fri, 9 Dec 2022 15:27:56 GMT", "version": "v2" } ]
2022-12-12
[ [ "Lin", "Dongdong", "" ], [ "Tondi", "Benedetta", "" ], [ "Li", "Bin", "" ], [ "Barni", "Mauro", "" ] ]
Due to the proliferation and widespread use of deep neural networks (DNN), their Intellectual Property Rights (IPR) protection has become increasingly important. This paper presents a novel model watermarking method for an unsupervised image-to-image translation (I2IT) networks, named CycleGAN, which leverage the image...
2104.10357
Qian Chen
Qian Chen, Wen Wang, Qinglin Zhang
Pre-training for Spoken Language Understanding with Joint Textual and Phonetic Representation Learning
Accepted by INTERSPEECH 2021
Proc. Interspeech 2021
10.21437/Interspeech.2021-234
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In the traditional cascading architecture for spoken language understanding (SLU), it has been observed that automatic speech recognition errors could be detrimental to the performance of natural language understanding. End-to-end (E2E) SLU models have been proposed to directly map speech input to desired semantic fr...
[ { "created": "Wed, 21 Apr 2021 05:19:13 GMT", "version": "v1" }, { "created": "Fri, 18 Jun 2021 07:45:52 GMT", "version": "v2" }, { "created": "Wed, 1 Sep 2021 05:55:00 GMT", "version": "v3" } ]
2021-09-02
[ [ "Chen", "Qian", "" ], [ "Wang", "Wen", "" ], [ "Zhang", "Qinglin", "" ] ]
In the traditional cascading architecture for spoken language understanding (SLU), it has been observed that automatic speech recognition errors could be detrimental to the performance of natural language understanding. End-to-end (E2E) SLU models have been proposed to directly map speech input to desired semantic fram...
2204.10945
Jaskaran Grover
Jaskaran Grover, Nishant Mohanty, Wenhao Luo, Changliu Liu, Katia Sycara
Noncooperative Herding With Control Barrier Functions: Theory and Experiments
null
null
null
null
cs.RO math.OC
http://creativecommons.org/licenses/by/4.0/
In this paper, we consider the problem of protecting a high-value unit from inadvertent attack by a group of agents using defending robots. Specifically, we develop a control strategy for the defending agents that we call "dog robots" to prevent a flock of "sheep agents" from breaching a protected zone. We take recou...
[ { "created": "Fri, 22 Apr 2022 22:14:03 GMT", "version": "v1" } ]
2022-04-26
[ [ "Grover", "Jaskaran", "" ], [ "Mohanty", "Nishant", "" ], [ "Luo", "Wenhao", "" ], [ "Liu", "Changliu", "" ], [ "Sycara", "Katia", "" ] ]
In this paper, we consider the problem of protecting a high-value unit from inadvertent attack by a group of agents using defending robots. Specifically, we develop a control strategy for the defending agents that we call "dog robots" to prevent a flock of "sheep agents" from breaching a protected zone. We take recours...
2408.00981
Junhao Zheng
Junhao Zheng, Haibin Chen, Qianli Ma
Cross-domain Named Entity Recognition via Graph Matching
Findings of ACL; available at Findings 2022 https://aclanthology.org/2022.findings-acl.210/; Improve presentation
null
10.18653/v1/2022.findings-acl.210
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
Cross-domain NER is a practical yet challenging problem since the data scarcity in the real-world scenario. A common practice is first to learn a NER model in a rich-resource general domain and then adapt the model to specific domains. Due to the mismatch problem between entity types across domains, the wide knowledg...
[ { "created": "Fri, 2 Aug 2024 02:31:54 GMT", "version": "v1" }, { "created": "Thu, 8 Aug 2024 02:15:53 GMT", "version": "v2" } ]
2024-08-09
[ [ "Zheng", "Junhao", "" ], [ "Chen", "Haibin", "" ], [ "Ma", "Qianli", "" ] ]
Cross-domain NER is a practical yet challenging problem since the data scarcity in the real-world scenario. A common practice is first to learn a NER model in a rich-resource general domain and then adapt the model to specific domains. Due to the mismatch problem between entity types across domains, the wide knowledge ...
0802.0251
Fabrice Rossi
Fabrice Rossi (INRIA Rocquencourt / INRIA Sophia Antipolis, CEREMADE), Brieuc Conan-Guez (INRIA Rocquencourt / INRIA Sophia Antipolis, LITA)
Multi-Layer Perceptrons and Symbolic Data
null
Symbolic Data Analysis and the SODAS Software Wiley (Ed.) (2008) 373-391
null
null
cs.NE
null
In some real world situations, linear models are not sufficient to represent accurately complex relations between input variables and output variables of a studied system. Multilayer Perceptrons are one of the most successful non-linear regression tool but they are unfortunately restricted to inputs and outputs that ...
[ { "created": "Sat, 2 Feb 2008 15:09:42 GMT", "version": "v1" } ]
2008-02-05
[ [ "Rossi", "Fabrice", "", "INRIA Rocquencourt / INRIA Sophia Antipolis, CEREMADE" ], [ "Conan-Guez", "Brieuc", "", "INRIA Rocquencourt / INRIA Sophia Antipolis, LITA" ] ]
In some real world situations, linear models are not sufficient to represent accurately complex relations between input variables and output variables of a studied system. Multilayer Perceptrons are one of the most successful non-linear regression tool but they are unfortunately restricted to inputs and outputs that be...
2303.17508
Tyler Malloy
Tyler Malloy, Miao Liu, Matthew D. Riemer, Tim Klinger, Gerald Tesauro, Chris R. Sims
Learning in Factored Domains with Information-Constrained Visual Representations
null
null
null
null
cs.AI cs.CV cs.HC q-bio.NC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Humans learn quickly even in tasks that contain complex visual information. This is due in part to the efficient formation of compressed representations of visual information, allowing for better generalization and robustness. However, compressed representations alone are insufficient for explaining the high speed of...
[ { "created": "Thu, 30 Mar 2023 16:22:10 GMT", "version": "v1" } ]
2023-03-31
[ [ "Malloy", "Tyler", "" ], [ "Liu", "Miao", "" ], [ "Riemer", "Matthew D.", "" ], [ "Klinger", "Tim", "" ], [ "Tesauro", "Gerald", "" ], [ "Sims", "Chris R.", "" ] ]
Humans learn quickly even in tasks that contain complex visual information. This is due in part to the efficient formation of compressed representations of visual information, allowing for better generalization and robustness. However, compressed representations alone are insufficient for explaining the high speed of h...
2105.00674
Heiko Paulheim
Michael Matthias Voit and Heiko Paulheim
Bias in Knowledge Graphs -- an Empirical Study with Movie Recommendation and Different Language Editions of DBpedia
Accepted for publication at 3rd Conference on Language, Data and Knowledge (LDK 2021)
null
null
null
cs.IR cs.AI
http://creativecommons.org/licenses/by/4.0/
Public knowledge graphs such as DBpedia and Wikidata have been recognized as interesting sources of background knowledge to build content-based recommender systems. They can be used to add information about the items to be recommended and links between those. While quite a few approaches for exploiting knowledge grap...
[ { "created": "Mon, 3 May 2021 08:07:30 GMT", "version": "v1" } ]
2021-05-04
[ [ "Voit", "Michael Matthias", "" ], [ "Paulheim", "Heiko", "" ] ]
Public knowledge graphs such as DBpedia and Wikidata have been recognized as interesting sources of background knowledge to build content-based recommender systems. They can be used to add information about the items to be recommended and links between those. While quite a few approaches for exploiting knowledge graphs...
2301.09347
Alexander Bentkamp
Alexander Bentkamp, Ramon Fern\'andez Mir, Jeremy Avigad
Verified reductions for optimization
null
null
null
null
cs.LO math.OC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Numerical and symbolic methods for optimization are used extensively in engineering, industry, and finance. Various methods are used to reduce problems of interest to ones that are amenable to solution by such software. We develop a framework for designing and applying such reductions, using the Lean programming lang...
[ { "created": "Mon, 23 Jan 2023 10:25:48 GMT", "version": "v1" }, { "created": "Tue, 24 Jan 2023 16:38:03 GMT", "version": "v2" }, { "created": "Wed, 22 Feb 2023 15:37:56 GMT", "version": "v3" } ]
2023-02-23
[ [ "Bentkamp", "Alexander", "" ], [ "Mir", "Ramon Fernández", "" ], [ "Avigad", "Jeremy", "" ] ]
Numerical and symbolic methods for optimization are used extensively in engineering, industry, and finance. Various methods are used to reduce problems of interest to ones that are amenable to solution by such software. We develop a framework for designing and applying such reductions, using the Lean programming langua...
2404.08330
Hyesong Choi
Hyesong Choi, Hunsang Lee, Seyoung Joung, Hyejin Park, Jiyeong Kim, Dongbo Min
Emerging Property of Masked Token for Effective Pre-training
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Driven by the success of Masked Language Modeling (MLM), the realm of self-supervised learning for computer vision has been invigorated by the central role of Masked Image Modeling (MIM) in driving recent breakthroughs. Notwithstanding the achievements of MIM across various downstream tasks, its overall efficiency is...
[ { "created": "Fri, 12 Apr 2024 08:46:53 GMT", "version": "v1" } ]
2024-04-15
[ [ "Choi", "Hyesong", "" ], [ "Lee", "Hunsang", "" ], [ "Joung", "Seyoung", "" ], [ "Park", "Hyejin", "" ], [ "Kim", "Jiyeong", "" ], [ "Min", "Dongbo", "" ] ]
Driven by the success of Masked Language Modeling (MLM), the realm of self-supervised learning for computer vision has been invigorated by the central role of Masked Image Modeling (MIM) in driving recent breakthroughs. Notwithstanding the achievements of MIM across various downstream tasks, its overall efficiency is o...
1509.09235
Malte Probst
Malte Probst
Generative Adversarial Networks in Estimation of Distribution Algorithms for Combinatorial Optimization
null
null
null
null
cs.NE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Estimation of Distribution Algorithms (EDAs) require flexible probability models that can be efficiently learned and sampled. Generative Adversarial Networks (GAN) are generative neural networks which can be trained to implicitly model the probability distribution of given data, and it is possible to sample this dist...
[ { "created": "Wed, 30 Sep 2015 16:02:59 GMT", "version": "v1" }, { "created": "Mon, 8 Aug 2016 13:01:39 GMT", "version": "v2" } ]
2016-08-09
[ [ "Probst", "Malte", "" ] ]
Estimation of Distribution Algorithms (EDAs) require flexible probability models that can be efficiently learned and sampled. Generative Adversarial Networks (GAN) are generative neural networks which can be trained to implicitly model the probability distribution of given data, and it is possible to sample this distri...
1904.08631
Junbao Zhuo
Junbao Zhuo, Shuhui Wang, Shuhao Cui and Qingming Huang
Unsupervised Open Domain Recognition by Semantic Discrepancy Minimization
Accepted to CVPR 2019, 10 pages, 4 figures
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We address the unsupervised open domain recognition (UODR) problem, where categories in labeled source domain S is only a subset of those in unlabeled target domain T. The task is to correctly classify all samples in T including known and unknown categories. UODR is challenging due to the domain discrepancy, which be...
[ { "created": "Thu, 18 Apr 2019 08:13:54 GMT", "version": "v1" } ]
2019-04-19
[ [ "Zhuo", "Junbao", "" ], [ "Wang", "Shuhui", "" ], [ "Cui", "Shuhao", "" ], [ "Huang", "Qingming", "" ] ]
We address the unsupervised open domain recognition (UODR) problem, where categories in labeled source domain S is only a subset of those in unlabeled target domain T. The task is to correctly classify all samples in T including known and unknown categories. UODR is challenging due to the domain discrepancy, which beco...
2407.11676
Remi Flamary
Yanis Lalou, Th\'eo Gnassounou, Antoine Collas, Antoine de Mathelin, Oleksii Kachaiev, Ambroise Odonnat, Alexandre Gramfort, Thomas Moreau, R\'emi Flamary
SKADA-Bench: Benchmarking Unsupervised Domain Adaptation Methods with Realistic Validation
null
null
null
null
cs.LG cs.AI stat.ME stat.ML
http://creativecommons.org/licenses/by/4.0/
Unsupervised Domain Adaptation (DA) consists of adapting a model trained on a labeled source domain to perform well on an unlabeled target domain with some data distribution shift. While many methods have been proposed in the literature, fair and realistic evaluation remains an open question, particularly due to meth...
[ { "created": "Tue, 16 Jul 2024 12:52:29 GMT", "version": "v1" } ]
2024-07-17
[ [ "Lalou", "Yanis", "" ], [ "Gnassounou", "Théo", "" ], [ "Collas", "Antoine", "" ], [ "de Mathelin", "Antoine", "" ], [ "Kachaiev", "Oleksii", "" ], [ "Odonnat", "Ambroise", "" ], [ "Gramfort", "Alexandre", ...
Unsupervised Domain Adaptation (DA) consists of adapting a model trained on a labeled source domain to perform well on an unlabeled target domain with some data distribution shift. While many methods have been proposed in the literature, fair and realistic evaluation remains an open question, particularly due to method...
2107.02025
Jim Samuel
Jim Samuel, Ratnakar Palle and Eduardo Correa Soares
Textual Data Distributions: Kullback Leibler Textual Distributions Contrasts on GPT-2 Generated Texts, with Supervised, Unsupervised Learning on Vaccine & Market Topics & Sentiment
null
null
null
null
cs.CL cs.LG cs.SI
http://creativecommons.org/licenses/by-nc-sa/4.0/
Efficient textual data distributions (TDD) alignment and generation are open research problems in textual analytics and NLP. It is presently difficult to parsimoniously and methodologically confirm that two or more natural language datasets belong to similar distributions, and to identify the extent to which textual ...
[ { "created": "Tue, 15 Jun 2021 21:30:46 GMT", "version": "v1" } ]
2021-07-06
[ [ "Samuel", "Jim", "" ], [ "Palle", "Ratnakar", "" ], [ "Soares", "Eduardo Correa", "" ] ]
Efficient textual data distributions (TDD) alignment and generation are open research problems in textual analytics and NLP. It is presently difficult to parsimoniously and methodologically confirm that two or more natural language datasets belong to similar distributions, and to identify the extent to which textual da...
2301.05012
Sophie Noiret
Sophie Noiret, Siddharth Ravi, Martin Kampel, Francisco Florez-Revuelta
Fairly Private: Investigating The Fairness of Visual Privacy Preservation Algorithms
Camera-ready version for the PPAI-23 workshop of the AAAI23
null
null
null
cs.CV cs.CR cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
As the privacy risks posed by camera surveillance and facial recognition have grown, so has the research into privacy preservation algorithms. Among these, visual privacy preservation algorithms attempt to impart bodily privacy to subjects in visuals by obfuscating privacy-sensitive areas. While disparate performance...
[ { "created": "Thu, 12 Jan 2023 13:40:38 GMT", "version": "v1" } ]
2023-01-13
[ [ "Noiret", "Sophie", "" ], [ "Ravi", "Siddharth", "" ], [ "Kampel", "Martin", "" ], [ "Florez-Revuelta", "Francisco", "" ] ]
As the privacy risks posed by camera surveillance and facial recognition have grown, so has the research into privacy preservation algorithms. Among these, visual privacy preservation algorithms attempt to impart bodily privacy to subjects in visuals by obfuscating privacy-sensitive areas. While disparate performances ...
2405.13413
Hee-Youl Kwak
Hee-Youl Kwak, Dae-Young Yun, Yongjune Kim, Sang-Hyo Kim, and Jong-Seon No
Boosted Neural Decoders: Achieving Extreme Reliability of LDPC Codes for 6G Networks
12 pages, 11 figures
null
null
null
cs.IT cs.LG eess.SP math.IT
http://creativecommons.org/licenses/by/4.0/
Ensuring extremely high reliability is essential for channel coding in 6G networks. The next-generation of ultra-reliable and low-latency communications (xURLLC) scenario within 6G networks requires a frame error rate (FER) below 10-9. However, low-density parity-check (LDPC) codes, the standard in 5G new radio (NR),...
[ { "created": "Wed, 22 May 2024 07:48:24 GMT", "version": "v1" } ]
2024-05-24
[ [ "Kwak", "Hee-Youl", "" ], [ "Yun", "Dae-Young", "" ], [ "Kim", "Yongjune", "" ], [ "Kim", "Sang-Hyo", "" ], [ "No", "Jong-Seon", "" ] ]
Ensuring extremely high reliability is essential for channel coding in 6G networks. The next-generation of ultra-reliable and low-latency communications (xURLLC) scenario within 6G networks requires a frame error rate (FER) below 10-9. However, low-density parity-check (LDPC) codes, the standard in 5G new radio (NR), e...
1710.02322
Diogo Luvizon
Diogo C. Luvizon, Hedi Tabia, David Picard
Human Pose Regression by Combining Indirect Part Detection and Contextual Information
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we propose an end-to-end trainable regression approach for human pose estimation from still images. We use the proposed Soft-argmax function to convert feature maps directly to joint coordinates, resulting in a fully differentiable framework. Our method is able to learn heat maps representations indire...
[ { "created": "Fri, 6 Oct 2017 09:27:44 GMT", "version": "v1" } ]
2017-10-09
[ [ "Luvizon", "Diogo C.", "" ], [ "Tabia", "Hedi", "" ], [ "Picard", "David", "" ] ]
In this paper, we propose an end-to-end trainable regression approach for human pose estimation from still images. We use the proposed Soft-argmax function to convert feature maps directly to joint coordinates, resulting in a fully differentiable framework. Our method is able to learn heat maps representations indirect...
1905.01468
Steven Kelk
Steven Kelk and Simone Linz
New reduction rules for the tree bisection and reconnection distance
Accepted for journal publication. This version contains extra figures. Keywords: fixed-parameter tractability, tree bisection and reconnection, generator, kernelization, agreement forest, phylogenetic network, phylogenetic tree, hybridization number
Annals of Combinatorics, 24:475-502, 2020
10.1007/s00026-020-00502-7
null
cs.DS q-bio.PE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recently it was shown that, if the subtree and chain reduction rules have been applied exhaustively to two unrooted phylogenetic trees, the reduced trees will have at most 15k-9 taxa where k is the TBR (Tree Bisection and Reconnection) distance between the two trees, and that this bound is tight. Here we propose five...
[ { "created": "Sat, 4 May 2019 10:00:09 GMT", "version": "v1" }, { "created": "Sun, 14 Jun 2020 06:51:19 GMT", "version": "v2" } ]
2021-04-13
[ [ "Kelk", "Steven", "" ], [ "Linz", "Simone", "" ] ]
Recently it was shown that, if the subtree and chain reduction rules have been applied exhaustively to two unrooted phylogenetic trees, the reduced trees will have at most 15k-9 taxa where k is the TBR (Tree Bisection and Reconnection) distance between the two trees, and that this bound is tight. Here we propose five n...
2212.13448
Ju-Bong Kim
Ju-Bong Kim, Ho-Bin Choi, Youn-Hee Han
Strangeness-driven Exploration in Multi-Agent Reinforcement Learning
9 pages, 7 figures
null
null
null
cs.LG cs.AI cs.MA
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Efficient exploration strategy is one of essential issues in cooperative multi-agent reinforcement learning (MARL) algorithms requiring complex coordination. In this study, we introduce a new exploration method with the strangeness that can be easily incorporated into any centralized training and decentralized execut...
[ { "created": "Tue, 27 Dec 2022 11:08:49 GMT", "version": "v1" } ]
2022-12-29
[ [ "Kim", "Ju-Bong", "" ], [ "Choi", "Ho-Bin", "" ], [ "Han", "Youn-Hee", "" ] ]
Efficient exploration strategy is one of essential issues in cooperative multi-agent reinforcement learning (MARL) algorithms requiring complex coordination. In this study, we introduce a new exploration method with the strangeness that can be easily incorporated into any centralized training and decentralized executio...
2404.18562
F\'atima Rodr\'iguez-Gal\'an
F\'atima Rodr\'iguez-Gal\'an, Ama Bandara, Elana Pereira de Santana, Peter Haring Bol\'ivar, Eduard Alarc\'on and Sergi Abadal
Time Reversal for Near-Field Communications on Multi-chip Wireless Networks
null
null
null
null
cs.AR
http://creativecommons.org/licenses/by/4.0/
Wireless Network-on-Chip (WNoC) has been proposed as a low-latency, versatile, and broadcast-capable complement to current interconnects in the quest for satisfying the ever-increasing communications needs of modern computing systems. However, to realize the promise of WNoC, multiple wireless links operating at sever...
[ { "created": "Mon, 29 Apr 2024 10:09:16 GMT", "version": "v1" }, { "created": "Tue, 30 Apr 2024 08:32:14 GMT", "version": "v2" } ]
2024-05-01
[ [ "Rodríguez-Galán", "Fátima", "" ], [ "Bandara", "Ama", "" ], [ "de Santana", "Elana Pereira", "" ], [ "Bolívar", "Peter Haring", "" ], [ "Alarcón", "Eduard", "" ], [ "Abadal", "Sergi", "" ] ]
Wireless Network-on-Chip (WNoC) has been proposed as a low-latency, versatile, and broadcast-capable complement to current interconnects in the quest for satisfying the ever-increasing communications needs of modern computing systems. However, to realize the promise of WNoC, multiple wireless links operating at several...
2302.13939
Rui-Jie Zhu
Rui-Jie Zhu, Qihang Zhao, Guoqi Li, Jason K. Eshraghian
SpikeGPT: Generative Pre-trained Language Model with Spiking Neural Networks
Accepted by TMLR
null
null
null
cs.CL cs.LG cs.NE
http://creativecommons.org/licenses/by-nc-sa/4.0/
As the size of large language models continue to scale, so does the computational resources required to run it. Spiking Neural Networks (SNNs) have emerged as an energy-efficient approach to deep learning that leverage sparse and event-driven activations to reduce the computational overhead associated with model infe...
[ { "created": "Mon, 27 Feb 2023 16:43:04 GMT", "version": "v1" }, { "created": "Tue, 28 Feb 2023 06:28:43 GMT", "version": "v2" }, { "created": "Mon, 26 Jun 2023 02:38:07 GMT", "version": "v3" }, { "created": "Tue, 27 Jun 2023 02:55:23 GMT", "version": "v4" }, { "c...
2024-07-12
[ [ "Zhu", "Rui-Jie", "" ], [ "Zhao", "Qihang", "" ], [ "Li", "Guoqi", "" ], [ "Eshraghian", "Jason K.", "" ] ]
As the size of large language models continue to scale, so does the computational resources required to run it. Spiking Neural Networks (SNNs) have emerged as an energy-efficient approach to deep learning that leverage sparse and event-driven activations to reduce the computational overhead associated with model infere...
2402.16871
Sascha Ossowski
Alberto Fern\'andez, Holger Billhardt, Sascha Ossowski, \'Oscar S\'anchez
Bike3S: A Tool for Bike Sharing Systems Simulation
null
Journal of Simulation 14(4), 2020
10.1080/17477778.2020.1718022
null
cs.MA cs.AI
http://creativecommons.org/licenses/by/4.0/
Vehicle sharing systems are becoming increasingly popular. The effectiveness of such systems depends, among other factors, on different strategic and operational management decisions and policies, like the dimension of the fleet or the distribution of vehicles. It is of foremost importance to be able to anticipate an...
[ { "created": "Wed, 24 Jan 2024 17:33:40 GMT", "version": "v1" } ]
2024-02-28
[ [ "Fernández", "Alberto", "" ], [ "Billhardt", "Holger", "" ], [ "Ossowski", "Sascha", "" ], [ "Sánchez", "Óscar", "" ] ]
Vehicle sharing systems are becoming increasingly popular. The effectiveness of such systems depends, among other factors, on different strategic and operational management decisions and policies, like the dimension of the fleet or the distribution of vehicles. It is of foremost importance to be able to anticipate and ...
1909.07745
Ali Ghadirzadeh
Xi Chen, Ali Ghadirzadeh, M{\aa}rten Bj\"orkman and Patric Jensfelt
Adversarial Feature Training for Generalizable Robotic Visuomotor Control
null
null
null
null
cs.RO cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Deep reinforcement learning (RL) has enabled training action-selection policies, end-to-end, by learning a function which maps image pixels to action outputs. However, it's application to visuomotor robotic policy training has been limited because of the challenge of large-scale data collection when working with phys...
[ { "created": "Tue, 17 Sep 2019 12:18:34 GMT", "version": "v1" } ]
2019-09-18
[ [ "Chen", "Xi", "" ], [ "Ghadirzadeh", "Ali", "" ], [ "Björkman", "Mårten", "" ], [ "Jensfelt", "Patric", "" ] ]
Deep reinforcement learning (RL) has enabled training action-selection policies, end-to-end, by learning a function which maps image pixels to action outputs. However, it's application to visuomotor robotic policy training has been limited because of the challenge of large-scale data collection when working with physic...
2406.07257
Hamed Babaei Giglou
Hamed Babaei Giglou, Tilahun Abedissa Taffa, Rana Abdullah, Aida Usmanova, Ricardo Usbeck, Jennifer D'Souza, S\"oren Auer
Scholarly Question Answering using Large Language Models in the NFDI4DataScience Gateway
13 pages main content, 16 pages overall, 3 Figures, accepted for publication at NSLP 2024 workshop at ESWC 2024
null
null
null
cs.CL cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper introduces a scholarly Question Answering (QA) system on top of the NFDI4DataScience Gateway, employing a Retrieval Augmented Generation-based (RAG) approach. The NFDI4DS Gateway, as a foundational framework, offers a unified and intuitive interface for querying various scientific databases using federated...
[ { "created": "Tue, 11 Jun 2024 13:36:19 GMT", "version": "v1" } ]
2024-06-12
[ [ "Giglou", "Hamed Babaei", "" ], [ "Taffa", "Tilahun Abedissa", "" ], [ "Abdullah", "Rana", "" ], [ "Usmanova", "Aida", "" ], [ "Usbeck", "Ricardo", "" ], [ "D'Souza", "Jennifer", "" ], [ "Auer", "Sören", ""...
This paper introduces a scholarly Question Answering (QA) system on top of the NFDI4DataScience Gateway, employing a Retrieval Augmented Generation-based (RAG) approach. The NFDI4DS Gateway, as a foundational framework, offers a unified and intuitive interface for querying various scientific databases using federated s...
2010.08012
Agnieszka Maria S{\l}owik
Alex Lamb, Anirudh Goyal, Agnieszka S{\l}owik, Michael Mozer, Philippe Beaudoin, Yoshua Bengio
Neural Function Modules with Sparse Arguments: A Dynamic Approach to Integrating Information across Layers
null
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Feed-forward neural networks consist of a sequence of layers, in which each layer performs some processing on the information from the previous layer. A downside to this approach is that each layer (or module, as multiple modules can operate in parallel) is tasked with processing the entire hidden state, rather than ...
[ { "created": "Thu, 15 Oct 2020 20:43:17 GMT", "version": "v1" } ]
2020-10-19
[ [ "Lamb", "Alex", "" ], [ "Goyal", "Anirudh", "" ], [ "Słowik", "Agnieszka", "" ], [ "Mozer", "Michael", "" ], [ "Beaudoin", "Philippe", "" ], [ "Bengio", "Yoshua", "" ] ]
Feed-forward neural networks consist of a sequence of layers, in which each layer performs some processing on the information from the previous layer. A downside to this approach is that each layer (or module, as multiple modules can operate in parallel) is tasked with processing the entire hidden state, rather than a ...
2407.00482
Barproda Halder
Barproda Halder, Faisal Hamman, Pasan Dissanayake, Qiuyi Zhang, Ilia Sucholutsky, Sanghamitra Dutta
Quantifying Spuriousness of Biased Datasets Using Partial Information Decomposition
Accepted at ICML 2024 Workshop on Data-centric Machine Learning Research (DMLR): Datasets for Foundation Models
null
null
null
cs.LG cs.AI cs.CV cs.CY cs.IT math.IT
http://creativecommons.org/licenses/by/4.0/
Spurious patterns refer to a mathematical association between two or more variables in a dataset that are not causally related. However, this notion of spuriousness, which is usually introduced due to sampling biases in the dataset, has classically lacked a formal definition. To address this gap, this work presents t...
[ { "created": "Sat, 29 Jun 2024 16:05:47 GMT", "version": "v1" } ]
2024-07-02
[ [ "Halder", "Barproda", "" ], [ "Hamman", "Faisal", "" ], [ "Dissanayake", "Pasan", "" ], [ "Zhang", "Qiuyi", "" ], [ "Sucholutsky", "Ilia", "" ], [ "Dutta", "Sanghamitra", "" ] ]
Spurious patterns refer to a mathematical association between two or more variables in a dataset that are not causally related. However, this notion of spuriousness, which is usually introduced due to sampling biases in the dataset, has classically lacked a formal definition. To address this gap, this work presents the...
2303.00076
Jan Vyb\'iral
Cornelia Schneider, Jan Vyb\'iral
A multivariate Riesz basis of ReLU neural networks
null
null
null
null
cs.IT math.FA math.IT
http://creativecommons.org/licenses/by/4.0/
We consider the trigonometric-like system of piecewise linear functions introduced recently by Daubechies, DeVore, Foucart, Hanin, and Petrova. We provide an alternative proof that this system forms a Riesz basis of $L_2([0,1])$ based on the Gershgorin theorem. We also generalize this system to higher dimensions $d>1...
[ { "created": "Tue, 28 Feb 2023 20:48:03 GMT", "version": "v1" } ]
2023-03-02
[ [ "Schneider", "Cornelia", "" ], [ "Vybíral", "Jan", "" ] ]
We consider the trigonometric-like system of piecewise linear functions introduced recently by Daubechies, DeVore, Foucart, Hanin, and Petrova. We provide an alternative proof that this system forms a Riesz basis of $L_2([0,1])$ based on the Gershgorin theorem. We also generalize this system to higher dimensions $d>1$ ...
1604.02610
Santiago Segarra
Santiago Segarra, Antonio G. Marques, Gonzalo Mateos, and Alejandro Ribeiro
Network Topology Identification from Spectral Templates
null
null
null
null
cs.SI physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Network topology inference is a cornerstone problem in statistical analyses of complex systems. In this context, the fresh look advocated here permeates benefits from convex optimization and graph signal processing, to identify the so-termed graph shift operator (encoding the network topology) given only the eigenvec...
[ { "created": "Sat, 9 Apr 2016 21:56:40 GMT", "version": "v1" } ]
2016-04-12
[ [ "Segarra", "Santiago", "" ], [ "Marques", "Antonio G.", "" ], [ "Mateos", "Gonzalo", "" ], [ "Ribeiro", "Alejandro", "" ] ]
Network topology inference is a cornerstone problem in statistical analyses of complex systems. In this context, the fresh look advocated here permeates benefits from convex optimization and graph signal processing, to identify the so-termed graph shift operator (encoding the network topology) given only the eigenvecto...
1710.01968
Sebastian Schlag
Robin Andre, Sebastian Schlag and Christian Schulz
Memetic Multilevel Hypergraph Partitioning
null
null
null
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Hypergraph partitioning has a wide range of important applications such as VLSI design or scientific computing. With focus on solution quality, we develop the first multilevel memetic algorithm to tackle the problem. Key components of our contribution are new effective multilevel recombination and mutation operations...
[ { "created": "Thu, 5 Oct 2017 11:20:45 GMT", "version": "v1" }, { "created": "Sat, 3 Feb 2018 12:37:55 GMT", "version": "v2" } ]
2018-02-06
[ [ "Andre", "Robin", "" ], [ "Schlag", "Sebastian", "" ], [ "Schulz", "Christian", "" ] ]
Hypergraph partitioning has a wide range of important applications such as VLSI design or scientific computing. With focus on solution quality, we develop the first multilevel memetic algorithm to tackle the problem. Key components of our contribution are new effective multilevel recombination and mutation operations t...
2201.07916
Lizhong Chen
Drew Penney, Bin Li, Jaroslaw Sydir, Lizhong Chen, Charlie Tai, Stefan Lee, Eoin Walsh, Thomas Long
PROMPT: Learning Dynamic Resource Allocation Policies for Network Applications
Accepted in Future Generation Computer Systems (FGCS)
null
10.1016/j.future.2023.03.016
null
cs.LG cs.SY eess.SY
http://creativecommons.org/licenses/by-nc-nd/4.0/
A growing number of service providers are exploring methods to improve server utilization and reduce power consumption by co-scheduling high-priority latency-critical workloads with best-effort workloads. This practice requires strict resource allocation between workloads to reduce contention and maintain Quality-of-...
[ { "created": "Wed, 19 Jan 2022 23:34:34 GMT", "version": "v1" }, { "created": "Sat, 25 Mar 2023 01:07:57 GMT", "version": "v2" } ]
2023-03-28
[ [ "Penney", "Drew", "" ], [ "Li", "Bin", "" ], [ "Sydir", "Jaroslaw", "" ], [ "Chen", "Lizhong", "" ], [ "Tai", "Charlie", "" ], [ "Lee", "Stefan", "" ], [ "Walsh", "Eoin", "" ], [ "Long", "Thomas...
A growing number of service providers are exploring methods to improve server utilization and reduce power consumption by co-scheduling high-priority latency-critical workloads with best-effort workloads. This practice requires strict resource allocation between workloads to reduce contention and maintain Quality-of-Se...
2205.04980
Shujian Zhang
Shujian Zhang, Chengyue Gong, Xingchao Liu, Pengcheng He, Weizhu Chen, Mingyuan Zhou
ALLSH: Active Learning Guided by Local Sensitivity and Hardness
NAACL 2022 (finding); Our code is publicly available at https://github.com/szhang42/allsh
null
null
null
cs.CL cs.AI cs.LG
http://creativecommons.org/licenses/by/4.0/
Active learning, which effectively collects informative unlabeled data for annotation, reduces the demand for labeled data. In this work, we propose to retrieve unlabeled samples with a local sensitivity and hardness-aware acquisition function. The proposed method generates data copies through local perturbations and...
[ { "created": "Tue, 10 May 2022 15:39:11 GMT", "version": "v1" }, { "created": "Fri, 23 Sep 2022 21:11:18 GMT", "version": "v2" } ]
2022-09-27
[ [ "Zhang", "Shujian", "" ], [ "Gong", "Chengyue", "" ], [ "Liu", "Xingchao", "" ], [ "He", "Pengcheng", "" ], [ "Chen", "Weizhu", "" ], [ "Zhou", "Mingyuan", "" ] ]
Active learning, which effectively collects informative unlabeled data for annotation, reduces the demand for labeled data. In this work, we propose to retrieve unlabeled samples with a local sensitivity and hardness-aware acquisition function. The proposed method generates data copies through local perturbations and s...
2105.01265
Adrian Dumitrescu
Adrian Dumitrescu
Finding Triangles or Independent Sets; and Other Dual Pair Approximations
13 pages, no figure
null
null
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We revisit the algorithmic problem of finding a triangle in a graph (\textsc{Triangle Detection}), and examine its relation to other problems such as \textsc{3Sum}, \textsc{Independent Set}, and \textsc{Graph Coloring}. We obtain several new algorithms: \smallskip (I) A simple randomized algorithm for finding a tri...
[ { "created": "Tue, 4 May 2021 03:11:37 GMT", "version": "v1" }, { "created": "Sat, 29 Jul 2023 01:53:58 GMT", "version": "v2" }, { "created": "Sun, 11 Feb 2024 14:44:10 GMT", "version": "v3" } ]
2024-02-13
[ [ "Dumitrescu", "Adrian", "" ] ]
We revisit the algorithmic problem of finding a triangle in a graph (\textsc{Triangle Detection}), and examine its relation to other problems such as \textsc{3Sum}, \textsc{Independent Set}, and \textsc{Graph Coloring}. We obtain several new algorithms: \smallskip (I) A simple randomized algorithm for finding a triangl...
2406.02612
Ou Wu
Ou Wu, Weiyao Zhu, Mengyang Li
Is Data Valuation Learnable and Interpretable?
null
null
null
null
cs.LG cs.AI
http://creativecommons.org/licenses/by-nc-sa/4.0/
Measuring the value of individual samples is critical for many data-driven tasks, e.g., the training of a deep learning model. Recent literature witnesses the substantial efforts in developing data valuation methods. The primary data valuation methodology is based on the Shapley value from game theory, and various me...
[ { "created": "Mon, 3 Jun 2024 08:13:47 GMT", "version": "v1" } ]
2024-06-06
[ [ "Wu", "Ou", "" ], [ "Zhu", "Weiyao", "" ], [ "Li", "Mengyang", "" ] ]
Measuring the value of individual samples is critical for many data-driven tasks, e.g., the training of a deep learning model. Recent literature witnesses the substantial efforts in developing data valuation methods. The primary data valuation methodology is based on the Shapley value from game theory, and various meth...
1805.02896
Ilya Verenich
Ilya Verenich, Marlon Dumas, Marcello La Rosa, Fabrizio Maggi, Irene Teinemaa
Survey and cross-benchmark comparison of remaining time prediction methods in business process monitoring
null
null
null
null
cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Predictive business process monitoring methods exploit historical process execution logs to generate predictions about running instances (called cases) of a business process, such as the prediction of the outcome, next activity or remaining cycle time of a given process case. These insights could be used to support o...
[ { "created": "Tue, 8 May 2018 08:38:58 GMT", "version": "v1" }, { "created": "Thu, 10 May 2018 21:56:51 GMT", "version": "v2" } ]
2018-05-14
[ [ "Verenich", "Ilya", "" ], [ "Dumas", "Marlon", "" ], [ "La Rosa", "Marcello", "" ], [ "Maggi", "Fabrizio", "" ], [ "Teinemaa", "Irene", "" ] ]
Predictive business process monitoring methods exploit historical process execution logs to generate predictions about running instances (called cases) of a business process, such as the prediction of the outcome, next activity or remaining cycle time of a given process case. These insights could be used to support ope...
2302.14421
Dimitrios Karoukis
Dimitrios Karoukis
Publicly verifiable delegative democracy with secret voting power
11 pages, 2 figures
null
null
null
cs.CR cs.DS cs.SI
http://creativecommons.org/licenses/by-nc-nd/4.0/
In a democratic setting, we introduce a commitment scheme which allows for transparent validation of transfers and reversible delegations of voting power between citizens without sacrificing their privacy. A unit of voting power is publicly represented by the Merkle root of a tree consisting of its latest owner's pub...
[ { "created": "Tue, 28 Feb 2023 08:54:07 GMT", "version": "v1" }, { "created": "Fri, 5 May 2023 11:48:41 GMT", "version": "v2" } ]
2023-05-08
[ [ "Karoukis", "Dimitrios", "" ] ]
In a democratic setting, we introduce a commitment scheme which allows for transparent validation of transfers and reversible delegations of voting power between citizens without sacrificing their privacy. A unit of voting power is publicly represented by the Merkle root of a tree consisting of its latest owner's publi...
2103.17028
Hassan Noura
Jean-Paul A. Yaacoub, Hassan N. Noura, Ola Salman and Ali Chehab
Digital Forensics vs. Anti-Digital Forensics: Techniques, Limitations and Recommendations
null
null
null
null
cs.CR
http://creativecommons.org/publicdomain/zero/1.0/
The number of cyber attacks has increased tremendously in the last few years. This resulted into both human and financial losses at the individual and organization levels. Recently, cyber-criminals are leveraging new skills and capabilities by employing anti-forensics activities, techniques and tools to cover their t...
[ { "created": "Wed, 31 Mar 2021 12:27:08 GMT", "version": "v1" } ]
2021-04-01
[ [ "Yaacoub", "Jean-Paul A.", "" ], [ "Noura", "Hassan N.", "" ], [ "Salman", "Ola", "" ], [ "Chehab", "Ali", "" ] ]
The number of cyber attacks has increased tremendously in the last few years. This resulted into both human and financial losses at the individual and organization levels. Recently, cyber-criminals are leveraging new skills and capabilities by employing anti-forensics activities, techniques and tools to cover their tra...
2107.10998
Dan Liu
Dan Liu, Xi Chen, Jie Fu, Chen Ma, Xue Liu
Pruning Ternary Quantization
Merged with Hyperspherical Quantization: Toward Smaller and More Accurate Models (arXiv:2212.12653.)
null
null
null
cs.CV cs.AI
http://creativecommons.org/licenses/by-nc-nd/4.0/
Inference time, model size, and accuracy are three key factors in deep model compression. Most of the existing work addresses these three key factors separately as it is difficult to optimize them all at the same time. For example, low-bit quantization aims at obtaining a faster model; weight sharing quantization aim...
[ { "created": "Fri, 23 Jul 2021 02:18:00 GMT", "version": "v1" }, { "created": "Wed, 26 Jan 2022 18:21:52 GMT", "version": "v2" }, { "created": "Sat, 24 Dec 2022 04:37:54 GMT", "version": "v3" }, { "created": "Thu, 2 Mar 2023 03:11:04 GMT", "version": "v4" }, { "cr...
2023-07-18
[ [ "Liu", "Dan", "" ], [ "Chen", "Xi", "" ], [ "Fu", "Jie", "" ], [ "Ma", "Chen", "" ], [ "Liu", "Xue", "" ] ]
Inference time, model size, and accuracy are three key factors in deep model compression. Most of the existing work addresses these three key factors separately as it is difficult to optimize them all at the same time. For example, low-bit quantization aims at obtaining a faster model; weight sharing quantization aims ...
1604.07160
Naoya Takahashi
Naoya Takahashi, Michael Gygli, Beat Pfister, Luc Van Gool
Deep Convolutional Neural Networks and Data Augmentation for Acoustic Event Detection
Presented in INTERSPEECH 2016
null
null
null
cs.SD cs.MM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We propose a novel method for Acoustic Event Detection (AED). In contrast to speech, sounds coming from acoustic events may be produced by a wide variety of sources. Furthermore, distinguishing them often requires analyzing an extended time period due to the lack of a clear sub-word unit. In order to incorporate the ...
[ { "created": "Mon, 25 Apr 2016 08:25:03 GMT", "version": "v1" }, { "created": "Thu, 8 Dec 2016 04:28:16 GMT", "version": "v2" } ]
2016-12-09
[ [ "Takahashi", "Naoya", "" ], [ "Gygli", "Michael", "" ], [ "Pfister", "Beat", "" ], [ "Van Gool", "Luc", "" ] ]
We propose a novel method for Acoustic Event Detection (AED). In contrast to speech, sounds coming from acoustic events may be produced by a wide variety of sources. Furthermore, distinguishing them often requires analyzing an extended time period due to the lack of a clear sub-word unit. In order to incorporate the lo...
1008.2824
S Geetha
S. Geetha and N. Kamaraj
Optimized Image Steganalysis through Feature Selection using MBEGA
15 pages, IEEE NetCom 2009 Conference, IJCNC Journal
International Journal of Computer Networks & Communications 2.4 (2010) 161-175
null
null
cs.CR cs.MM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Feature based steganalysis, an emerging branch in information forensics, aims at identifying the presence of a covert communication by employing the statistical features of the cover and stego image as clues/evidences. Due to the large volumes of security audit data as well as complex and dynamic properties of stegan...
[ { "created": "Tue, 17 Aug 2010 05:57:36 GMT", "version": "v1" } ]
2010-08-18
[ [ "Geetha", "S.", "" ], [ "Kamaraj", "N.", "" ] ]
Feature based steganalysis, an emerging branch in information forensics, aims at identifying the presence of a covert communication by employing the statistical features of the cover and stego image as clues/evidences. Due to the large volumes of security audit data as well as complex and dynamic properties of steganog...
0907.5165
Oliver Johnson
Oliver Johnson, Matthew Aldridge, Robert Piechocki
Interference alignment-based sum capacity bounds for random dense Gaussian interference networks
23 pages
IEEE Transactions on Information Theory, 57:1, 282-290, 2011
10.1109/TIT.2010.2090242
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We consider a dense $K$ user Gaussian interference network formed by paired transmitters and receivers placed independently at random in a fixed spatial region. Under natural conditions on the node position distributions and signal attenuation, we prove convergence in probability of the average per-user capacity $\cs...
[ { "created": "Wed, 29 Jul 2009 15:47:48 GMT", "version": "v1" } ]
2011-09-12
[ [ "Johnson", "Oliver", "" ], [ "Aldridge", "Matthew", "" ], [ "Piechocki", "Robert", "" ] ]
We consider a dense $K$ user Gaussian interference network formed by paired transmitters and receivers placed independently at random in a fixed spatial region. Under natural conditions on the node position distributions and signal attenuation, we prove convergence in probability of the average per-user capacity $\csum...
1410.5055
Jun Fang
Jun Fang, Yanning Shen, Fuwei Li, and Hongbin Li
Prior Support Knowledge-Aided Sparse Bayesian Learning with Partly Erroneous Support Information
null
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
It has been shown both experimentally and theoretically that sparse signal recovery can be significantly improved given that part of the signal's support is known \emph{a priori}. In practice, however, such prior knowledge is usually inaccurate and contains errors. Using such knowledge may result in severe performanc...
[ { "created": "Sun, 19 Oct 2014 10:47:21 GMT", "version": "v1" } ]
2014-10-21
[ [ "Fang", "Jun", "" ], [ "Shen", "Yanning", "" ], [ "Li", "Fuwei", "" ], [ "Li", "Hongbin", "" ] ]
It has been shown both experimentally and theoretically that sparse signal recovery can be significantly improved given that part of the signal's support is known \emph{a priori}. In practice, however, such prior knowledge is usually inaccurate and contains errors. Using such knowledge may result in severe performance ...
2310.12419
Huanyao Rong
Huanyao Rong, Wei You, Xiaofeng Wang, Tianhao Mao
Toward Unbiased Multiple-Target Fuzzing with Path Diversity
null
null
null
null
cs.CR
http://creativecommons.org/licenses/by/4.0/
In this paper, we propose a novel directed fuzzing solution named AFLRun, which features target path-diversity metric and unbiased energy assignment. Firstly, we develop a new coverage metric by maintaining extra virgin map for each covered target to track the coverage status of seeds that hit the target. This approa...
[ { "created": "Thu, 19 Oct 2023 02:12:43 GMT", "version": "v1" }, { "created": "Thu, 6 Jun 2024 06:46:00 GMT", "version": "v2" } ]
2024-06-07
[ [ "Rong", "Huanyao", "" ], [ "You", "Wei", "" ], [ "Wang", "Xiaofeng", "" ], [ "Mao", "Tianhao", "" ] ]
In this paper, we propose a novel directed fuzzing solution named AFLRun, which features target path-diversity metric and unbiased energy assignment. Firstly, we develop a new coverage metric by maintaining extra virgin map for each covered target to track the coverage status of seeds that hit the target. This approach...
2312.05311
Jalees Nehvi
Jalees Nehvi, Berna Kabadayi, Julien Valentin, Justus Thies
360{\deg} Volumetric Portrait Avatar
Project page: https://jalees018.github.io/3VP-Avatar/
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We propose 360{\deg} Volumetric Portrait (3VP) Avatar, a novel method for reconstructing 360{\deg} photo-realistic portrait avatars of human subjects solely based on monocular video inputs. State-of-the-art monocular avatar reconstruction methods rely on stable facial performance capturing. However, the common usage ...
[ { "created": "Fri, 8 Dec 2023 19:00:03 GMT", "version": "v1" } ]
2023-12-12
[ [ "Nehvi", "Jalees", "" ], [ "Kabadayi", "Berna", "" ], [ "Valentin", "Julien", "" ], [ "Thies", "Justus", "" ] ]
We propose 360{\deg} Volumetric Portrait (3VP) Avatar, a novel method for reconstructing 360{\deg} photo-realistic portrait avatars of human subjects solely based on monocular video inputs. State-of-the-art monocular avatar reconstruction methods rely on stable facial performance capturing. However, the common usage of...
2011.03252
Matteo Iovino
Matteo Iovino, Jonathan Styrud, Pietro Falco and Christian Smith
Learning Behavior Trees with Genetic Programming in Unpredictable Environments
null
null
null
null
cs.RO cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Modern industrial applications require robots to be able to operate in unpredictable environments, and programs to be created with a minimal effort, as there may be frequent changes to the task. In this paper, we show that genetic programming can be effectively used to learn the structure of a behavior tree (BT) to s...
[ { "created": "Fri, 6 Nov 2020 09:28:23 GMT", "version": "v1" } ]
2020-11-09
[ [ "Iovino", "Matteo", "" ], [ "Styrud", "Jonathan", "" ], [ "Falco", "Pietro", "" ], [ "Smith", "Christian", "" ] ]
Modern industrial applications require robots to be able to operate in unpredictable environments, and programs to be created with a minimal effort, as there may be frequent changes to the task. In this paper, we show that genetic programming can be effectively used to learn the structure of a behavior tree (BT) to sol...
2203.13551
Miguel Romero
Miguel Romero, Oscar Ram\'irez, Jorge Finke, Camilo Rocha
Feature extraction using Spectral Clustering for Gene Function Prediction using Hierarchical Multi-label Classification
null
null
null
null
cs.LG
http://creativecommons.org/licenses/by/4.0/
Gene annotation addresses the problem of predicting unknown associations between gene and functions (e.g., biological processes) of a specific organism. Despite recent advances, the cost and time demanded by annotation procedures that rely largely on in vivo biological experiments remain prohibitively high. This pape...
[ { "created": "Fri, 25 Mar 2022 10:17:36 GMT", "version": "v1" }, { "created": "Thu, 28 Apr 2022 21:19:33 GMT", "version": "v2" } ]
2022-05-02
[ [ "Romero", "Miguel", "" ], [ "Ramírez", "Oscar", "" ], [ "Finke", "Jorge", "" ], [ "Rocha", "Camilo", "" ] ]
Gene annotation addresses the problem of predicting unknown associations between gene and functions (e.g., biological processes) of a specific organism. Despite recent advances, the cost and time demanded by annotation procedures that rely largely on in vivo biological experiments remain prohibitively high. This paper ...
1708.05868
Shuping Dang
Shuping Dang and Justin P. Coon and Gaojie Chen and David E. Simmons
Outage Performance Analysis of Multicarrier Relay Selection for Cooperative Networks
null
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we analyze the outage performance of two multicarrier relay selection schemes, i.e. bulk and per-subcarrier selections, for two-hop orthogonal frequency-division multiplexing (OFDM) systems. To provide a comprehensive analysis, three forwarding protocols: decode-and-forward (DF), fixed-gain (FG) amplif...
[ { "created": "Sat, 19 Aug 2017 16:03:29 GMT", "version": "v1" } ]
2017-08-22
[ [ "Dang", "Shuping", "" ], [ "Coon", "Justin P.", "" ], [ "Chen", "Gaojie", "" ], [ "Simmons", "David E.", "" ] ]
In this paper, we analyze the outage performance of two multicarrier relay selection schemes, i.e. bulk and per-subcarrier selections, for two-hop orthogonal frequency-division multiplexing (OFDM) systems. To provide a comprehensive analysis, three forwarding protocols: decode-and-forward (DF), fixed-gain (FG) amplify-...
2306.13285
Vasileios Magoulianitis
Vasileios Magoulianitis, Athanasios Psaltis
Learning Scene Flow With Skeleton Guidance For 3D Action Recognition
18 pages, 3 figures, 3 tables, conference
null
null
null
cs.CV eess.IV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Among the existing modalities for 3D action recognition, 3D flow has been poorly examined, although conveying rich motion information cues for human actions. Presumably, its susceptibility to noise renders it intractable, thus challenging the learning process within deep models. This work demonstrates the use of 3D f...
[ { "created": "Fri, 23 Jun 2023 04:14:25 GMT", "version": "v1" } ]
2023-06-26
[ [ "Magoulianitis", "Vasileios", "" ], [ "Psaltis", "Athanasios", "" ] ]
Among the existing modalities for 3D action recognition, 3D flow has been poorly examined, although conveying rich motion information cues for human actions. Presumably, its susceptibility to noise renders it intractable, thus challenging the learning process within deep models. This work demonstrates the use of 3D flo...
1411.0281
Remi Chou
Remi A. Chou and Matthieu R. Bloch
Polar Coding for the Broadcast Channel with Confidential Messages: A Random Binning Analogy
20 pages, two-column, 6 figures, accepted to IEEE Transactions on Information Theory; parts of the results were presented at the 2015 IEEE Information Theory Workshop; minor change in title
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We develop a low-complexity polar coding scheme for the discrete memoryless broadcast channel with confidential messages under strong secrecy and randomness constraints. Our scheme extends previous work by using an optimal rate of uniform randomness in the stochastic encoder, and avoiding assumptions regarding the sy...
[ { "created": "Sun, 2 Nov 2014 17:19:12 GMT", "version": "v1" }, { "created": "Sat, 5 Mar 2016 04:08:11 GMT", "version": "v2" } ]
2016-03-08
[ [ "Chou", "Remi A.", "" ], [ "Bloch", "Matthieu R.", "" ] ]
We develop a low-complexity polar coding scheme for the discrete memoryless broadcast channel with confidential messages under strong secrecy and randomness constraints. Our scheme extends previous work by using an optimal rate of uniform randomness in the stochastic encoder, and avoiding assumptions regarding the symm...
1702.03246
Christos Mousas
Christos Mousas
Towards Developing an Easy-To-Use Scripting Environment for Animating Virtual Characters
null
null
null
null
cs.GR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper presents the three scripting commands and main functionalities of a novel character animation environment called CHASE. CHASE was developed for enabling inexperienced programmers, animators, artists, and students to animate in meaningful ways virtual reality characters. This is achieved by scripting simple...
[ { "created": "Fri, 10 Feb 2017 16:37:55 GMT", "version": "v1" } ]
2017-02-13
[ [ "Mousas", "Christos", "" ] ]
This paper presents the three scripting commands and main functionalities of a novel character animation environment called CHASE. CHASE was developed for enabling inexperienced programmers, animators, artists, and students to animate in meaningful ways virtual reality characters. This is achieved by scripting simple c...
2007.13687
Minghua Xia
Zongze Li, Minghua Xia, Miaowen Wen, and Yik-Chung Wu
Massive Access in Secure NOMA under Imperfect CSI: Security Guaranteed Sum-Rate Maximization with First-Order Algorithm
17 pages, 6 figures, accepted for publication in IEEE Journal on Selected Areas in Communications
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Non-orthogonal multiple access (NOMA) is a promising solution for secure transmission under massive access. However, in addition to the uncertain channel state information (CSI) of the eavesdroppers due to their passive nature, the CSI of the legitimate users may also be imperfect at the base station due to the limit...
[ { "created": "Mon, 27 Jul 2020 17:01:18 GMT", "version": "v1" } ]
2020-07-28
[ [ "Li", "Zongze", "" ], [ "Xia", "Minghua", "" ], [ "Wen", "Miaowen", "" ], [ "Wu", "Yik-Chung", "" ] ]
Non-orthogonal multiple access (NOMA) is a promising solution for secure transmission under massive access. However, in addition to the uncertain channel state information (CSI) of the eavesdroppers due to their passive nature, the CSI of the legitimate users may also be imperfect at the base station due to the limited...
1912.11720
Qing Ping
Qing Ping, Chaomei Chen
Convolutional Quantum-Like Language Model with Mutual-Attention for Product Rating Prediction
Accepted at MAISON workshop at ICTIR 19'
null
null
null
cs.IR cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recommender systems are designed to help mitigate information overload users experience during online shopping. Recent work explores neural language models to learn user and item representations from user reviews and combines such representations with rating information. Most existing convolutional-based neural model...
[ { "created": "Wed, 25 Dec 2019 22:01:59 GMT", "version": "v1" } ]
2019-12-30
[ [ "Ping", "Qing", "" ], [ "Chen", "Chaomei", "" ] ]
Recommender systems are designed to help mitigate information overload users experience during online shopping. Recent work explores neural language models to learn user and item representations from user reviews and combines such representations with rating information. Most existing convolutional-based neural models ...
1803.07639
Srinivasan Parthasarathy
Srinivasan Parthasarathy
Adaptive Greedy Algorithms for Stochastic Set Cover Problems
null
null
null
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We study adaptive greedy algorithms for the problems of stochastic set cover with perfect and imperfect coverages. In stochastic set cover with perfect coverage, we are given a set of items and a ground set B. Evaluating an item reveals its state which is a random subset of B drawn from the state distribution of the ...
[ { "created": "Tue, 20 Mar 2018 20:30:55 GMT", "version": "v1" }, { "created": "Thu, 22 Mar 2018 11:55:59 GMT", "version": "v2" }, { "created": "Tue, 27 Mar 2018 04:47:14 GMT", "version": "v3" }, { "created": "Thu, 29 Mar 2018 12:17:17 GMT", "version": "v4" }, { "c...
2018-06-19
[ [ "Parthasarathy", "Srinivasan", "" ] ]
We study adaptive greedy algorithms for the problems of stochastic set cover with perfect and imperfect coverages. In stochastic set cover with perfect coverage, we are given a set of items and a ground set B. Evaluating an item reveals its state which is a random subset of B drawn from the state distribution of the it...
2403.15943
Zhenglin Li
Zhenglin Li, Yangchen Huang, Mengran Zhu, Jingyu Zhang, JingHao Chang, Houze Liu
Advanced Feature Manipulation for Enhanced Change Detection Leveraging Natural Language Models
This version is not our full version based on our new progress, related data, and methodology we are dealing with, and based on the rules and the laws, we are adjusting our current version
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Change detection is a fundamental task in computer vision that processes a bi-temporal image pair to differentiate between semantically altered and unaltered regions. Large language models (LLMs) have been utilized in various domains for their exceptional feature extraction capabilities and have shown promise in nume...
[ { "created": "Sat, 23 Mar 2024 22:07:32 GMT", "version": "v1" }, { "created": "Thu, 13 Jun 2024 15:30:02 GMT", "version": "v2" } ]
2024-06-14
[ [ "Li", "Zhenglin", "" ], [ "Huang", "Yangchen", "" ], [ "Zhu", "Mengran", "" ], [ "Zhang", "Jingyu", "" ], [ "Chang", "JingHao", "" ], [ "Liu", "Houze", "" ] ]
Change detection is a fundamental task in computer vision that processes a bi-temporal image pair to differentiate between semantically altered and unaltered regions. Large language models (LLMs) have been utilized in various domains for their exceptional feature extraction capabilities and have shown promise in numero...
2407.19365
Chuxu Song
Chuxu Song, Zining Fan, Hao Wang, Richard Martin
Seamless Website Fingerprinting in Multiple Environments
16 pages
null
null
null
cs.CR
http://creativecommons.org/licenses/by/4.0/
Website fingerprinting (WF) attacks identify the websites visited over anonymized connections by analyzing patterns in network traffic flows, such as packet sizes, directions, or interval times using a machine learning classifier. Previous studies showed WF attacks achieve high classification accuracy. However, sever...
[ { "created": "Sun, 28 Jul 2024 02:18:30 GMT", "version": "v1" } ]
2024-07-30
[ [ "Song", "Chuxu", "" ], [ "Fan", "Zining", "" ], [ "Wang", "Hao", "" ], [ "Martin", "Richard", "" ] ]
Website fingerprinting (WF) attacks identify the websites visited over anonymized connections by analyzing patterns in network traffic flows, such as packet sizes, directions, or interval times using a machine learning classifier. Previous studies showed WF attacks achieve high classification accuracy. However, several...
1601.04908
Martha Lewis
Desislava Bankova, Bob Coecke, Martha Lewis, Daniel Marsden
Graded Entailment for Compositional Distributional Semantics
null
null
null
null
cs.CL cs.AI cs.LO math.CT quant-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The categorical compositional distributional model of natural language provides a conceptually motivated procedure to compute the meaning of sentences, given grammatical structure and the meanings of its words. This approach has outperformed other models in mainstream empirical language processing tasks. However, unt...
[ { "created": "Tue, 19 Jan 2016 13:13:25 GMT", "version": "v1" }, { "created": "Mon, 25 Jan 2016 20:10:27 GMT", "version": "v2" } ]
2016-01-26
[ [ "Bankova", "Desislava", "" ], [ "Coecke", "Bob", "" ], [ "Lewis", "Martha", "" ], [ "Marsden", "Daniel", "" ] ]
The categorical compositional distributional model of natural language provides a conceptually motivated procedure to compute the meaning of sentences, given grammatical structure and the meanings of its words. This approach has outperformed other models in mainstream empirical language processing tasks. However, until...
2108.09757
Tserwa Bakasa
Tseriwa Bakasa and Ayanda Pekane
The Decision Criteria Used by Large Enterprises in South Africa for the Adoption of Cloud Computing
In proceedings of the 1st Virtual Conference on Implications of Information and Digital Technologies for Development, 2021
null
null
null
cs.CY
http://creativecommons.org/licenses/by-nc-sa/4.0/
Cloud computing is a technology that has become increasingly popular over the past decade within several enterprises. This popularity can be attributed to its benefits, including lower operating costs, improved computational capabilities, increased flexibility and on-demand storage space. As a result, many enterprise...
[ { "created": "Sun, 22 Aug 2021 15:33:55 GMT", "version": "v1" } ]
2021-08-24
[ [ "Bakasa", "Tseriwa", "" ], [ "Pekane", "Ayanda", "" ] ]
Cloud computing is a technology that has become increasingly popular over the past decade within several enterprises. This popularity can be attributed to its benefits, including lower operating costs, improved computational capabilities, increased flexibility and on-demand storage space. As a result, many enterprises ...
1909.05615
Prabhat Kumar
Nikhil Singh, Prabhat Kumar, and Anupam Saxena
On Topology optimization with elliptical masks and honeycomb tessellation with explicit length scale constraints
36 pages, 24 figures
Structural and Multidisciplinary Optimization, 2020
10.1007/s00158-020-02548-w
null
cs.CE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Topology optimization using gradient search with negative and positive elliptical masks and honeycomb tessellation is presented. Through a novel skeletonization algorithm for topologies defined using filled and void hexagonal cells/elements, explicit minimum and maximum length scales are imposed on solid states in th...
[ { "created": "Thu, 12 Sep 2019 13:07:34 GMT", "version": "v1" }, { "created": "Fri, 9 Oct 2020 21:26:31 GMT", "version": "v2" } ]
2020-10-13
[ [ "Singh", "Nikhil", "" ], [ "Kumar", "Prabhat", "" ], [ "Saxena", "Anupam", "" ] ]
Topology optimization using gradient search with negative and positive elliptical masks and honeycomb tessellation is presented. Through a novel skeletonization algorithm for topologies defined using filled and void hexagonal cells/elements, explicit minimum and maximum length scales are imposed on solid states in the ...
1701.02831
Tamir Bendory
Tamir Bendory, Pavel Sidorenko and Yonina C. Eldar
On the Uniqueness of FROG Methods
null
null
10.1109/LSP.2017.2690358
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The problem of recovering a signal from its power spectrum, called phase retrieval, arises in many scientific fields. One of many examples is ultra-short laser pulse characterization in which the electromagnetic field is oscillating with ~10^15 Hz and phase information cannot be measured directly due to limitations o...
[ { "created": "Wed, 11 Jan 2017 02:47:44 GMT", "version": "v1" }, { "created": "Sun, 19 Mar 2017 17:35:14 GMT", "version": "v2" }, { "created": "Sat, 1 Apr 2017 18:48:14 GMT", "version": "v3" } ]
2017-04-26
[ [ "Bendory", "Tamir", "" ], [ "Sidorenko", "Pavel", "" ], [ "Eldar", "Yonina C.", "" ] ]
The problem of recovering a signal from its power spectrum, called phase retrieval, arises in many scientific fields. One of many examples is ultra-short laser pulse characterization in which the electromagnetic field is oscillating with ~10^15 Hz and phase information cannot be measured directly due to limitations of ...
2108.13696
Chathura Gamage
Cheng Xue, Vimukthini Pinto, Chathura Gamage, Ekaterina Nikonova, Peng Zhang, Jochen Renz
Phy-Q as a measure for physical reasoning intelligence
For the associated website, see https://github.com/phy-q/benchmark
null
null
null
cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Humans are well-versed in reasoning about the behaviors of physical objects and choosing actions accordingly to accomplish tasks, while it remains a major challenge for AI. To facilitate research addressing this problem, we propose a new testbed that requires an agent to reason about physical scenarios and take an ac...
[ { "created": "Tue, 31 Aug 2021 09:11:27 GMT", "version": "v1" }, { "created": "Wed, 18 May 2022 03:39:05 GMT", "version": "v2" }, { "created": "Fri, 27 Jan 2023 01:52:45 GMT", "version": "v3" } ]
2023-01-30
[ [ "Xue", "Cheng", "" ], [ "Pinto", "Vimukthini", "" ], [ "Gamage", "Chathura", "" ], [ "Nikonova", "Ekaterina", "" ], [ "Zhang", "Peng", "" ], [ "Renz", "Jochen", "" ] ]
Humans are well-versed in reasoning about the behaviors of physical objects and choosing actions accordingly to accomplish tasks, while it remains a major challenge for AI. To facilitate research addressing this problem, we propose a new testbed that requires an agent to reason about physical scenarios and take an acti...
2111.08498
Yi Heng Lim
Yi Heng Lim, Muhammad Firmansyah Kasim
Reducing the Long Tail Losses in Scientific Emulations with Active Learning
8 pages, 4 figures
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Deep-learning-based models are increasingly used to emulate scientific simulations to accelerate scientific research. However, accurate, supervised deep learning models require huge amount of labelled data, and that often becomes the bottleneck in employing neural networks. In this work, we leveraged an active learni...
[ { "created": "Mon, 15 Nov 2021 09:02:00 GMT", "version": "v1" }, { "created": "Sun, 9 Jan 2022 15:05:48 GMT", "version": "v2" } ]
2022-01-11
[ [ "Lim", "Yi Heng", "" ], [ "Kasim", "Muhammad Firmansyah", "" ] ]
Deep-learning-based models are increasingly used to emulate scientific simulations to accelerate scientific research. However, accurate, supervised deep learning models require huge amount of labelled data, and that often becomes the bottleneck in employing neural networks. In this work, we leveraged an active learning...
2106.00083
Maurice Herlihy
Daniel Engel, Maurice Herlihy
Composing Networks of Automated Market Makers
null
null
10.1145/3479722.3480987
null
cs.DC cs.MA
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Automated market makers (AMMs) are automata that trade electronic assets at rates set by mathematical formulas. AMMs are usually implemented by smart contracts on blockchains. In practice, AMMs are often composed: and outputs from AMMs can be directed into other compatible AMMs. This paper proposes a mathematical mod...
[ { "created": "Mon, 31 May 2021 20:09:26 GMT", "version": "v1" }, { "created": "Wed, 16 Jun 2021 17:53:07 GMT", "version": "v2" }, { "created": "Tue, 31 Aug 2021 13:32:32 GMT", "version": "v3" } ]
2021-09-01
[ [ "Engel", "Daniel", "" ], [ "Herlihy", "Maurice", "" ] ]
Automated market makers (AMMs) are automata that trade electronic assets at rates set by mathematical formulas. AMMs are usually implemented by smart contracts on blockchains. In practice, AMMs are often composed: and outputs from AMMs can be directed into other compatible AMMs. This paper proposes a mathematical model...
1806.10920
Matthew England Dr
M. England
Machine Learning for Mathematical Software
To appear in Proc. ICMS 2018
In: J.H. Davenport, M. Kauers, G. Labahn and J. Urban, eds. Mathematical Software - ICMS 2018, pp. 165-174. (Lecture Notes in Computer Science 10931). Springer, 2018
10.1007/978-3-319-96418-8_20
null
cs.SC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
While there has been some discussion on how Symbolic Computation could be used for AI there is little literature on applications in the other direction. However, recent results for quantifier elimination suggest that, given enough example problems, there is scope for machine learning tools like Support Vector Machine...
[ { "created": "Thu, 28 Jun 2018 12:35:47 GMT", "version": "v1" } ]
2018-11-01
[ [ "England", "M.", "" ] ]
While there has been some discussion on how Symbolic Computation could be used for AI there is little literature on applications in the other direction. However, recent results for quantifier elimination suggest that, given enough example problems, there is scope for machine learning tools like Support Vector Machines ...
2403.17933
Daniel Dauner
Kashyap Chitta, Daniel Dauner, Andreas Geiger
SLEDGE: Synthesizing Driving Environments with Generative Models and Rule-Based Traffic
ECCV 2024
null
null
null
cs.RO cs.AI cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
SLEDGE is the first generative simulator for vehicle motion planning trained on real-world driving logs. Its core component is a learned model that is able to generate agent bounding boxes and lane graphs. The model's outputs serve as an initial state for rule-based traffic simulation. The unique properties of the en...
[ { "created": "Tue, 26 Mar 2024 17:58:29 GMT", "version": "v1" }, { "created": "Thu, 11 Jul 2024 17:27:49 GMT", "version": "v2" } ]
2024-07-12
[ [ "Chitta", "Kashyap", "" ], [ "Dauner", "Daniel", "" ], [ "Geiger", "Andreas", "" ] ]
SLEDGE is the first generative simulator for vehicle motion planning trained on real-world driving logs. Its core component is a learned model that is able to generate agent bounding boxes and lane graphs. The model's outputs serve as an initial state for rule-based traffic simulation. The unique properties of the enti...
1804.10985
Anton\'in Ku\v{c}era
Tom\'a\v{s} Br\'azdil, Krishnendu Chatterjee, Anton\'in Ku\v{c}era, Petr Novotn\'y, Dominik Velan, Florian Zuleger
Efficient Algorithms for Asymptotic Bounds on Termination Time in VASS
arXiv admin note: text overlap with arXiv:1708.09253
null
null
null
cs.LO
http://creativecommons.org/licenses/by/4.0/
Vector Addition Systems with States (VASS) provide a well-known and fundamental model for the analysis of concurrent processes, parameterized systems, and are also used as abstract models of programs in resource bound analysis. In this paper we study the problem of obtaining asymptotic bounds on the termination time ...
[ { "created": "Sun, 29 Apr 2018 20:01:00 GMT", "version": "v1" } ]
2018-05-01
[ [ "Brázdil", "Tomáš", "" ], [ "Chatterjee", "Krishnendu", "" ], [ "Kučera", "Antonín", "" ], [ "Novotný", "Petr", "" ], [ "Velan", "Dominik", "" ], [ "Zuleger", "Florian", "" ] ]
Vector Addition Systems with States (VASS) provide a well-known and fundamental model for the analysis of concurrent processes, parameterized systems, and are also used as abstract models of programs in resource bound analysis. In this paper we study the problem of obtaining asymptotic bounds on the termination time of...
1906.10886
Peng Gao
Zibin Zhou, Fei Wang, Wenjuan Xi, Huaying Chen, Peng Gao, Chengkang He
Joint Multi-frame Detection and Segmentation for Multi-cell Tracking
Accepted by International Conference on Image and Graphics (ICIG 2019)
null
null
null
cs.CV cs.GR eess.IV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Tracking living cells in video sequence is difficult, because of cell morphology and high similarities between cells. Tracking-by-detection methods are widely used in multi-cell tracking. We perform multi-cell tracking based on the cell centroid detection, and the performance of the detector has high impact on tracki...
[ { "created": "Wed, 26 Jun 2019 07:41:11 GMT", "version": "v1" } ]
2019-06-27
[ [ "Zhou", "Zibin", "" ], [ "Wang", "Fei", "" ], [ "Xi", "Wenjuan", "" ], [ "Chen", "Huaying", "" ], [ "Gao", "Peng", "" ], [ "He", "Chengkang", "" ] ]
Tracking living cells in video sequence is difficult, because of cell morphology and high similarities between cells. Tracking-by-detection methods are widely used in multi-cell tracking. We perform multi-cell tracking based on the cell centroid detection, and the performance of the detector has high impact on tracking...
1812.01404
Zhan Yang
Zhan Yang, Osolo Ian Raymond, Wuqing Sun, Jun Long
Deep Attention-guided Hashing
Accepted to IEEE ACCESS
null
10.1109/ACCESS.2019.2891894
null
cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
With the rapid growth of multimedia data (e.g., image, audio and video etc.) on the web, learning-based hashing techniques such as Deep Supervised Hashing (DSH) have proven to be very efficient for large-scale multimedia search. The recent successes seen in Learning-based hashing methods are largely due to the succes...
[ { "created": "Tue, 4 Dec 2018 13:36:35 GMT", "version": "v1" }, { "created": "Tue, 8 Jan 2019 01:48:15 GMT", "version": "v2" } ]
2019-01-09
[ [ "Yang", "Zhan", "" ], [ "Raymond", "Osolo Ian", "" ], [ "Sun", "Wuqing", "" ], [ "Long", "Jun", "" ] ]
With the rapid growth of multimedia data (e.g., image, audio and video etc.) on the web, learning-based hashing techniques such as Deep Supervised Hashing (DSH) have proven to be very efficient for large-scale multimedia search. The recent successes seen in Learning-based hashing methods are largely due to the success ...
2112.08787
Yue Yu
Yue Yu, Lingkai Kong, Jieyu Zhang, Rongzhi Zhang, Chao Zhang
AcTune: Uncertainty-aware Active Self-Training for Semi-Supervised Active Learning with Pretrained Language Models
NAACL 2022 Main Conference (Code: https://github.com/yueyu1030/actune)
NAACL 2022
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
While pre-trained language model (PLM) fine-tuning has achieved strong performance in many NLP tasks, the fine-tuning stage can be still demanding in labeled data. Recent works have resorted to active fine-tuning to improve the label efficiency of PLM fine-tuning, but none of them investigate the potential of unlabel...
[ { "created": "Thu, 16 Dec 2021 11:09:48 GMT", "version": "v1" }, { "created": "Tue, 3 May 2022 04:42:55 GMT", "version": "v2" } ]
2022-05-04
[ [ "Yu", "Yue", "" ], [ "Kong", "Lingkai", "" ], [ "Zhang", "Jieyu", "" ], [ "Zhang", "Rongzhi", "" ], [ "Zhang", "Chao", "" ] ]
While pre-trained language model (PLM) fine-tuning has achieved strong performance in many NLP tasks, the fine-tuning stage can be still demanding in labeled data. Recent works have resorted to active fine-tuning to improve the label efficiency of PLM fine-tuning, but none of them investigate the potential of unlabeled...
1812.08861
Aliaksandr Siarohin
Aliaksandr Siarohin, St\'ephane Lathuili\`ere, Sergey Tulyakov, Elisa Ricci and Nicu Sebe
Animating Arbitrary Objects via Deep Motion Transfer
CVPR-2019 (oral)
null
null
null
cs.GR cs.CV cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper introduces a novel deep learning framework for image animation. Given an input image with a target object and a driving video sequence depicting a moving object, our framework generates a video in which the target object is animated according to the driving sequence. This is achieved through a deep archite...
[ { "created": "Thu, 20 Dec 2018 21:45:56 GMT", "version": "v1" }, { "created": "Mon, 24 Dec 2018 08:01:58 GMT", "version": "v2" }, { "created": "Fri, 30 Aug 2019 23:48:13 GMT", "version": "v3" } ]
2019-09-04
[ [ "Siarohin", "Aliaksandr", "" ], [ "Lathuilière", "Stéphane", "" ], [ "Tulyakov", "Sergey", "" ], [ "Ricci", "Elisa", "" ], [ "Sebe", "Nicu", "" ] ]
This paper introduces a novel deep learning framework for image animation. Given an input image with a target object and a driving video sequence depicting a moving object, our framework generates a video in which the target object is animated according to the driving sequence. This is achieved through a deep architect...
2001.06891
Zhu Zhang
Zhu Zhang, Zhou Zhao, Yang Zhao, Qi Wang, Huasheng Liu, Lianli Gao
Where Does It Exist: Spatio-Temporal Video Grounding for Multi-Form Sentences
The camera ready version for CVPR 2020
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we consider a novel task, Spatio-Temporal Video Grounding for Multi-Form Sentences (STVG). Given an untrimmed video and a declarative/interrogative sentence depicting an object, STVG aims to localize the spatio-temporal tube of the queried object. STVG has two challenging settings: (1) We need to local...
[ { "created": "Sun, 19 Jan 2020 19:53:22 GMT", "version": "v1" }, { "created": "Tue, 25 Feb 2020 13:46:00 GMT", "version": "v2" }, { "created": "Tue, 24 Mar 2020 21:34:44 GMT", "version": "v3" } ]
2020-03-26
[ [ "Zhang", "Zhu", "" ], [ "Zhao", "Zhou", "" ], [ "Zhao", "Yang", "" ], [ "Wang", "Qi", "" ], [ "Liu", "Huasheng", "" ], [ "Gao", "Lianli", "" ] ]
In this paper, we consider a novel task, Spatio-Temporal Video Grounding for Multi-Form Sentences (STVG). Given an untrimmed video and a declarative/interrogative sentence depicting an object, STVG aims to localize the spatio-temporal tube of the queried object. STVG has two challenging settings: (1) We need to localiz...
2306.03906
Kenjiro Tadakuma
Josephine Galipon, Shoya Shimizu, Kenjiro Tadakuma
Biological Organisms as End Effectors
13 pages, 9 figures, 1 graphical abstract
null
null
null
cs.RO
http://creativecommons.org/licenses/by/4.0/
In robotics, an end effector is a device at the end of a robotic arm that is designed to physically interact with objects in the environment or with the environment itself. Effectively, it serves as the hand of the robot, carrying out tasks on behalf of humans. But could we turn this concept on its head and consider ...
[ { "created": "Tue, 6 Jun 2023 17:59:29 GMT", "version": "v1" }, { "created": "Mon, 12 Jun 2023 15:22:02 GMT", "version": "v2" } ]
2023-06-13
[ [ "Galipon", "Josephine", "" ], [ "Shimizu", "Shoya", "" ], [ "Tadakuma", "Kenjiro", "" ] ]
In robotics, an end effector is a device at the end of a robotic arm that is designed to physically interact with objects in the environment or with the environment itself. Effectively, it serves as the hand of the robot, carrying out tasks on behalf of humans. But could we turn this concept on its head and consider us...
2211.09064
Gecheng Chen
Gecheng Chen, Yu Zhou, Xudong Zhang, Rui Tuo
Renewing Iterative Self-labeling Domain Adaptation with Application to the Spine Motion Prediction
null
null
null
null
cs.LG stat.AP
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The area of transfer learning comprises supervised machine learning methods that cope with the issue when the training and testing data have different input feature spaces or distributions. In this work, we propose a novel transfer learning algorithm called Renewing Iterative Self-labeling Domain Adaptation (Re-ISDA)...
[ { "created": "Mon, 14 Nov 2022 21:06:02 GMT", "version": "v1" } ]
2022-11-17
[ [ "Chen", "Gecheng", "" ], [ "Zhou", "Yu", "" ], [ "Zhang", "Xudong", "" ], [ "Tuo", "Rui", "" ] ]
The area of transfer learning comprises supervised machine learning methods that cope with the issue when the training and testing data have different input feature spaces or distributions. In this work, we propose a novel transfer learning algorithm called Renewing Iterative Self-labeling Domain Adaptation (Re-ISDA). ...
2210.11787
Prafulla Kumar Choubey
Prafulla Kumar Choubey and Ruihong Huang
Modeling Document-level Temporal Structures for Building Temporal Dependency Graphs
AACL 2022
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
We propose to leverage news discourse profiling to model document-level temporal structures for building temporal dependency graphs. Our key observation is that the functional roles of sentences used for profiling news discourse signify different time frames relevant to a news story and can, therefore, help to recove...
[ { "created": "Fri, 21 Oct 2022 07:45:17 GMT", "version": "v1" } ]
2022-10-24
[ [ "Choubey", "Prafulla Kumar", "" ], [ "Huang", "Ruihong", "" ] ]
We propose to leverage news discourse profiling to model document-level temporal structures for building temporal dependency graphs. Our key observation is that the functional roles of sentences used for profiling news discourse signify different time frames relevant to a news story and can, therefore, help to recover ...
2403.19432
Song Wang
Song Wang, Yiliang Zhou, Ziqiang Han, Cui Tao, Yunyu Xiao, Ying Ding, Joydeep Ghosh, Yifan Peng
Uncovering Misattributed Suicide Causes through Annotation Inconsistency Detection in Death Investigation Notes
19 pages, 6 figures
null
null
null
cs.CL cs.AI
http://creativecommons.org/licenses/by/4.0/
Data accuracy is essential for scientific research and policy development. The National Violent Death Reporting System (NVDRS) data is widely used for discovering the patterns and causes of death. Recent studies suggested the annotation inconsistencies within the NVDRS and the potential impact on erroneous suicide-ca...
[ { "created": "Thu, 28 Mar 2024 14:03:12 GMT", "version": "v1" }, { "created": "Fri, 29 Mar 2024 17:21:02 GMT", "version": "v2" } ]
2024-04-01
[ [ "Wang", "Song", "" ], [ "Zhou", "Yiliang", "" ], [ "Han", "Ziqiang", "" ], [ "Tao", "Cui", "" ], [ "Xiao", "Yunyu", "" ], [ "Ding", "Ying", "" ], [ "Ghosh", "Joydeep", "" ], [ "Peng", "Yifan", ...
Data accuracy is essential for scientific research and policy development. The National Violent Death Reporting System (NVDRS) data is widely used for discovering the patterns and causes of death. Recent studies suggested the annotation inconsistencies within the NVDRS and the potential impact on erroneous suicide-caus...
2010.04927
Qiansheng Wang
Qiansheng Wang, Yuxin Liu, Chengguo Lv, Zhen Wang and Guohong Fu
Cue-word Driven Neural Response Generation with a Shrinking Vocabulary
null
null
null
null
cs.CL cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Open-domain response generation is the task of generating sensible and informative re-sponses to the source sentence. However, neural models tend to generate safe and mean-ingless responses. While cue-word introducing approaches encourage responses with concrete semantics and have shown tremendous potential, they sti...
[ { "created": "Sat, 10 Oct 2020 07:13:32 GMT", "version": "v1" } ]
2020-10-13
[ [ "Wang", "Qiansheng", "" ], [ "Liu", "Yuxin", "" ], [ "Lv", "Chengguo", "" ], [ "Wang", "Zhen", "" ], [ "Fu", "Guohong", "" ] ]
Open-domain response generation is the task of generating sensible and informative re-sponses to the source sentence. However, neural models tend to generate safe and mean-ingless responses. While cue-word introducing approaches encourage responses with concrete semantics and have shown tremendous potential, they still...
1304.7854
Leopoldo Bertossi
Leopoldo Bertossi and Jaffer Gardezi
On the Complexity of Query Answering under Matching Dependencies for Entity Resolution
To appear in Proc. of the Alberto Mendelzon International Workshop on Foundations of Data Management (AMW 2013)
null
null
null
cs.DB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Matching Dependencies (MDs) are a relatively recent proposal for declarative entity resolution. They are rules that specify, given the similarities satisfied by values in a database, what values should be considered duplicates, and have to be matched. On the basis of a chase-like procedure for MD enforcement, we can ...
[ { "created": "Tue, 30 Apr 2013 04:05:44 GMT", "version": "v1" }, { "created": "Sun, 26 May 2013 21:34:35 GMT", "version": "v2" } ]
2013-05-28
[ [ "Bertossi", "Leopoldo", "" ], [ "Gardezi", "Jaffer", "" ] ]
Matching Dependencies (MDs) are a relatively recent proposal for declarative entity resolution. They are rules that specify, given the similarities satisfied by values in a database, what values should be considered duplicates, and have to be matched. On the basis of a chase-like procedure for MD enforcement, we can ob...
1908.08005
No\"elie Cherrier
No\"elie Cherrier, Jean-Philippe Poli, Maxime Defurne and Franck Sabati\'e
Consistent Feature Construction with Constrained Genetic Programming for Experimental Physics
Accepted in this version to CEC 2019
Proceedings of 2019 IEEE Congress on Evolutionary Computation (CEC), Wellington, New Zealand, 2019, pp. 1650-1658
10.1109/CEC.2019.8789937
null
cs.NE cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A good feature representation is a determinant factor to achieve high performance for many machine learning algorithms in terms of classification. This is especially true for techniques that do not build complex internal representations of data (e.g. decision trees, in contrast to deep neural networks). To transform ...
[ { "created": "Sat, 17 Aug 2019 10:55:15 GMT", "version": "v1" } ]
2019-08-22
[ [ "Cherrier", "Noëlie", "" ], [ "Poli", "Jean-Philippe", "" ], [ "Defurne", "Maxime", "" ], [ "Sabatié", "Franck", "" ] ]
A good feature representation is a determinant factor to achieve high performance for many machine learning algorithms in terms of classification. This is especially true for techniques that do not build complex internal representations of data (e.g. decision trees, in contrast to deep neural networks). To transform th...
2102.05700
Johannes Knittel
Johannes Knittel, Steffen Koch, Thomas Ertl
ELSKE: Efficient Large-Scale Keyphrase Extraction
null
null
10.1145/3469096.3474930
null
cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Keyphrase extraction methods can provide insights into large collections of documents such as social media posts. Existing methods, however, are less suited for the real-time analysis of streaming data, because they are computationally too expensive or require restrictive constraints regarding the structure of keyphr...
[ { "created": "Wed, 10 Feb 2021 19:14:01 GMT", "version": "v1" } ]
2021-09-16
[ [ "Knittel", "Johannes", "" ], [ "Koch", "Steffen", "" ], [ "Ertl", "Thomas", "" ] ]
Keyphrase extraction methods can provide insights into large collections of documents such as social media posts. Existing methods, however, are less suited for the real-time analysis of streaming data, because they are computationally too expensive or require restrictive constraints regarding the structure of keyphras...
2002.07948
Alireza Fallah
Alireza Fallah, Aryan Mokhtari, Asuman Ozdaglar
Personalized Federated Learning: A Meta-Learning Approach
To appear in 34th Conference on Neural Information Processing Systems (NeurIPS 2020)
null
null
null
cs.LG math.OC stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In Federated Learning, we aim to train models across multiple computing units (users), while users can only communicate with a common central server, without exchanging their data samples. This mechanism exploits the computational power of all users and allows users to obtain a richer model as their models are traine...
[ { "created": "Wed, 19 Feb 2020 01:08:46 GMT", "version": "v1" }, { "created": "Tue, 23 Jun 2020 04:16:11 GMT", "version": "v2" }, { "created": "Sat, 27 Jun 2020 02:52:01 GMT", "version": "v3" }, { "created": "Fri, 23 Oct 2020 03:04:01 GMT", "version": "v4" } ]
2020-10-26
[ [ "Fallah", "Alireza", "" ], [ "Mokhtari", "Aryan", "" ], [ "Ozdaglar", "Asuman", "" ] ]
In Federated Learning, we aim to train models across multiple computing units (users), while users can only communicate with a common central server, without exchanging their data samples. This mechanism exploits the computational power of all users and allows users to obtain a richer model as their models are trained ...
1807.05127
Patrick Verga
Shikhar Murty*, Patrick Verga*, Luke Vilnis, Irena Radovanovic, Andrew McCallum
Hierarchical Losses and New Resources for Fine-grained Entity Typing and Linking
ACL 2018
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Extraction from raw text to a knowledge base of entities and fine-grained types is often cast as prediction into a flat set of entity and type labels, neglecting the rich hierarchies over types and entities contained in curated ontologies. Previous attempts to incorporate hierarchical structure have yielded little be...
[ { "created": "Fri, 13 Jul 2018 15:15:41 GMT", "version": "v1" } ]
2018-07-16
[ [ "Murty*", "Shikhar", "" ], [ "Verga*", "Patrick", "" ], [ "Vilnis", "Luke", "" ], [ "Radovanovic", "Irena", "" ], [ "McCallum", "Andrew", "" ] ]
Extraction from raw text to a knowledge base of entities and fine-grained types is often cast as prediction into a flat set of entity and type labels, neglecting the rich hierarchies over types and entities contained in curated ontologies. Previous attempts to incorporate hierarchical structure have yielded little bene...
1501.01327
Rama Krishna Bandi
Rama Krishna Bandi and Maheshanand Bhaintwal
Cyclic codes over $\mathbb{Z}_4+u\mathbb{Z}_4$
arXiv admin note: text overlap with arXiv:1412.3751
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we have studied cyclic codes over the ring $R=\mathbb{Z}_4+u\mathbb{Z}_4$, $u^2=0$. We have considered cyclic codes of odd lengths. A sufficient condition for a cyclic code over $R$ to be a $\mathbb{Z}_4$-free module is presented. We have provided the general form of the generators of a cyclic code ove...
[ { "created": "Tue, 6 Jan 2015 22:19:02 GMT", "version": "v1" } ]
2015-01-08
[ [ "Bandi", "Rama Krishna", "" ], [ "Bhaintwal", "Maheshanand", "" ] ]
In this paper, we have studied cyclic codes over the ring $R=\mathbb{Z}_4+u\mathbb{Z}_4$, $u^2=0$. We have considered cyclic codes of odd lengths. A sufficient condition for a cyclic code over $R$ to be a $\mathbb{Z}_4$-free module is presented. We have provided the general form of the generators of a cyclic code over ...
1709.08318
Ari Stern
Ari Stern and Alexander Tettenhorst
Hodge decomposition and the Shapley value of a cooperative game
21 pages; v2: rewrote Section 2.2 to be a more elementary introduction to the combinatorial Hodge decomposition, added Section 3.5 on explicit decomposition via discrete Green's functions, other minor edits
Games Econom. Behav., 113 (2019), 186-198
10.1016/j.geb.2018.09.006
null
cs.GT math.CO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We show that a cooperative game may be decomposed into a sum of component games, one for each player, using the combinatorial Hodge decomposition on a graph. This decomposition is shown to satisfy certain efficiency, null-player, symmetry, and linearity properties. Consequently, we obtain a new characterization of th...
[ { "created": "Mon, 25 Sep 2017 04:51:45 GMT", "version": "v1" }, { "created": "Tue, 18 Sep 2018 21:29:58 GMT", "version": "v2" } ]
2019-03-28
[ [ "Stern", "Ari", "" ], [ "Tettenhorst", "Alexander", "" ] ]
We show that a cooperative game may be decomposed into a sum of component games, one for each player, using the combinatorial Hodge decomposition on a graph. This decomposition is shown to satisfy certain efficiency, null-player, symmetry, and linearity properties. Consequently, we obtain a new characterization of the ...
2211.08371
Daniel Fried
Daniel Fried, Nicholas Tomlin, Jennifer Hu, Roma Patel, Aida Nematzadeh
Pragmatics in Language Grounding: Phenomena, Tasks, and Modeling Approaches
Findings of EMNLP 2023
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
People rely heavily on context to enrich meaning beyond what is literally said, enabling concise but effective communication. To interact successfully and naturally with people, user-facing artificial intelligence systems will require similar skills in pragmatics: relying on various types of context -- from shared li...
[ { "created": "Tue, 15 Nov 2022 18:21:46 GMT", "version": "v1" }, { "created": "Sun, 21 May 2023 23:34:39 GMT", "version": "v2" }, { "created": "Tue, 21 Nov 2023 23:04:53 GMT", "version": "v3" } ]
2023-11-23
[ [ "Fried", "Daniel", "" ], [ "Tomlin", "Nicholas", "" ], [ "Hu", "Jennifer", "" ], [ "Patel", "Roma", "" ], [ "Nematzadeh", "Aida", "" ] ]
People rely heavily on context to enrich meaning beyond what is literally said, enabling concise but effective communication. To interact successfully and naturally with people, user-facing artificial intelligence systems will require similar skills in pragmatics: relying on various types of context -- from shared ling...
2010.00970
Paul Ferm\'e
Siddharth Barman, Omar Fawzi, Paul Ferm\'e
Tight Approximation Guarantees for Concave Coverage Problems
33 pages. v3 minor corrections and added FPT hardness
null
10.4230/LIPIcs.STACS.2021.9
null
cs.DS cs.CC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In the maximum coverage problem, we are given subsets $T_1, \ldots, T_m$ of a universe $[n]$ along with an integer $k$ and the objective is to find a subset $S \subseteq [m]$ of size $k$ that maximizes $C(S) := \Big|\bigcup_{i \in S} T_i\Big|$. It is a classic result that the greedy algorithm for this problem achieve...
[ { "created": "Fri, 2 Oct 2020 13:03:04 GMT", "version": "v1" }, { "created": "Fri, 13 Nov 2020 13:19:35 GMT", "version": "v2" }, { "created": "Mon, 18 Jan 2021 10:36:21 GMT", "version": "v3" } ]
2021-05-04
[ [ "Barman", "Siddharth", "" ], [ "Fawzi", "Omar", "" ], [ "Fermé", "Paul", "" ] ]
In the maximum coverage problem, we are given subsets $T_1, \ldots, T_m$ of a universe $[n]$ along with an integer $k$ and the objective is to find a subset $S \subseteq [m]$ of size $k$ that maximizes $C(S) := \Big|\bigcup_{i \in S} T_i\Big|$. It is a classic result that the greedy algorithm for this problem achieves ...
2403.07691
Jiwoo Hong
Jiwoo Hong, Noah Lee, James Thorne
ORPO: Monolithic Preference Optimization without Reference Model
Preprint
null
null
null
cs.CL cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
While recent preference alignment algorithms for language models have demonstrated promising results, supervised fine-tuning (SFT) remains imperative for achieving successful convergence. In this paper, we study the crucial role of SFT within the context of preference alignment, emphasizing that a minor penalty for t...
[ { "created": "Tue, 12 Mar 2024 14:34:08 GMT", "version": "v1" }, { "created": "Thu, 14 Mar 2024 07:47:08 GMT", "version": "v2" } ]
2024-03-15
[ [ "Hong", "Jiwoo", "" ], [ "Lee", "Noah", "" ], [ "Thorne", "James", "" ] ]
While recent preference alignment algorithms for language models have demonstrated promising results, supervised fine-tuning (SFT) remains imperative for achieving successful convergence. In this paper, we study the crucial role of SFT within the context of preference alignment, emphasizing that a minor penalty for the...
2404.18533
Meng Li
Meng Li, Haoran Jin, Ruixuan Huang, Zhihao Xu, Defu Lian, Zijia Lin, Di Zhang, Xiting Wang
Evaluating Concept-based Explanations of Language Models: A Study on Faithfulness and Readability
null
null
null
null
cs.AI cs.HC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Despite the surprisingly high intelligence exhibited by Large Language Models (LLMs), we are somehow intimidated to fully deploy them into real-life applications considering their black-box nature. Concept-based explanations arise as a promising avenue for explaining what the LLMs have learned, making them more trans...
[ { "created": "Mon, 29 Apr 2024 09:20:25 GMT", "version": "v1" }, { "created": "Tue, 30 Apr 2024 03:31:51 GMT", "version": "v2" } ]
2024-05-01
[ [ "Li", "Meng", "" ], [ "Jin", "Haoran", "" ], [ "Huang", "Ruixuan", "" ], [ "Xu", "Zhihao", "" ], [ "Lian", "Defu", "" ], [ "Lin", "Zijia", "" ], [ "Zhang", "Di", "" ], [ "Wang", "Xiting", ""...
Despite the surprisingly high intelligence exhibited by Large Language Models (LLMs), we are somehow intimidated to fully deploy them into real-life applications considering their black-box nature. Concept-based explanations arise as a promising avenue for explaining what the LLMs have learned, making them more transpa...
1502.01220
Tarek Lahlou
Tarek A. Lahlou and Alan V. Oppenheim
Unveiling The Tree: A Convex Framework for Sparse Problems
null
null
10.1109/ICASSP.2015.7178687
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper presents a general framework for generating greedy algorithms for solving convex constraint satisfaction problems for sparse solutions by mapping the satisfaction problem into one of graph traversal on a rooted tree of unknown topology. For every pre-walk of the tree an initial set of generally dense feasi...
[ { "created": "Wed, 4 Feb 2015 14:54:37 GMT", "version": "v1" } ]
2015-09-16
[ [ "Lahlou", "Tarek A.", "" ], [ "Oppenheim", "Alan V.", "" ] ]
This paper presents a general framework for generating greedy algorithms for solving convex constraint satisfaction problems for sparse solutions by mapping the satisfaction problem into one of graph traversal on a rooted tree of unknown topology. For every pre-walk of the tree an initial set of generally dense feasibl...
1808.05500
Mostafa Mehdipour Ghazi
Mostafa Mehdipour Ghazi, Mads Nielsen, Akshay Pai, M. Jorge Cardoso, Marc Modat, Sebastien Ourselin, Lauge S{\o}rensen
Robust training of recurrent neural networks to handle missing data for disease progression modeling
9 pages, 1 figure, MIDL conference
null
null
null
cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Disease progression modeling (DPM) using longitudinal data is a challenging task in machine learning for healthcare that can provide clinicians with better tools for diagnosis and monitoring of disease. Existing DPM algorithms neglect temporal dependencies among measurements and make parametric assumptions about biom...
[ { "created": "Thu, 16 Aug 2018 14:09:22 GMT", "version": "v1" } ]
2018-08-17
[ [ "Ghazi", "Mostafa Mehdipour", "" ], [ "Nielsen", "Mads", "" ], [ "Pai", "Akshay", "" ], [ "Cardoso", "M. Jorge", "" ], [ "Modat", "Marc", "" ], [ "Ourselin", "Sebastien", "" ], [ "Sørensen", "Lauge", "" ]...
Disease progression modeling (DPM) using longitudinal data is a challenging task in machine learning for healthcare that can provide clinicians with better tools for diagnosis and monitoring of disease. Existing DPM algorithms neglect temporal dependencies among measurements and make parametric assumptions about biomar...
2311.18496
Tengjin Weng
Tengjin Weng, Yang Shen, Zhidong Zhao, Zhiming Cheng, Shuai Wang
Accurate Segmentation of Optic Disc And Cup from Multiple Pseudo-labels by Noise-aware Learning
CSCWD 2024
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Optic disc and cup segmentation plays a crucial role in automating the screening and diagnosis of optic glaucoma. While data-driven convolutional neural networks (CNNs) show promise in this area, the inherent ambiguity of segmenting objects and background boundaries in the task of optic disc and cup segmentation lead...
[ { "created": "Thu, 30 Nov 2023 12:17:16 GMT", "version": "v1" }, { "created": "Fri, 15 Mar 2024 08:38:04 GMT", "version": "v2" } ]
2024-03-18
[ [ "Weng", "Tengjin", "" ], [ "Shen", "Yang", "" ], [ "Zhao", "Zhidong", "" ], [ "Cheng", "Zhiming", "" ], [ "Wang", "Shuai", "" ] ]
Optic disc and cup segmentation plays a crucial role in automating the screening and diagnosis of optic glaucoma. While data-driven convolutional neural networks (CNNs) show promise in this area, the inherent ambiguity of segmenting objects and background boundaries in the task of optic disc and cup segmentation leads ...
2008.08193
Sudip Poddar
Sudip Poddar, Anirban Mukhopadhyay
EXCLUVIS: A MATLAB GUI Software for Comparative Study of Clustering and Visualization of Gene Expression Data
19 pages, 18 figures
null
null
null
cs.HC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Clustering is a popular data mining technique that aims to partition an input space into multiple homogeneous regions. There exist several clustering algorithms in the literature. The performance of a clustering algorithm depends on its input parameters which can substantially affect the behavior of the algorithm. Cl...
[ { "created": "Tue, 18 Aug 2020 23:34:57 GMT", "version": "v1" } ]
2020-08-20
[ [ "Poddar", "Sudip", "" ], [ "Mukhopadhyay", "Anirban", "" ] ]
Clustering is a popular data mining technique that aims to partition an input space into multiple homogeneous regions. There exist several clustering algorithms in the literature. The performance of a clustering algorithm depends on its input parameters which can substantially affect the behavior of the algorithm. Clus...
cs/0011038
Ming-Yang Kao
Miklos Csuros, Ming-Yang Kao
Provably Fast and Accurate Recovery of Evolutionary Trees through Harmonic Greedy Triplets
The paper will appear in SIAM Journal on Computing
null
null
null
cs.DS cs.LG
null
We give a greedy learning algorithm for reconstructing an evolutionary tree based on a certain harmonic average on triplets of terminal taxa. After the pairwise distances between terminal taxa are estimated from sequence data, the algorithm runs in O(n^2) time using O(n) work space, where n is the number of terminal ...
[ { "created": "Thu, 23 Nov 2000 14:48:53 GMT", "version": "v1" } ]
2007-05-23
[ [ "Csuros", "Miklos", "" ], [ "Kao", "Ming-Yang", "" ] ]
We give a greedy learning algorithm for reconstructing an evolutionary tree based on a certain harmonic average on triplets of terminal taxa. After the pairwise distances between terminal taxa are estimated from sequence data, the algorithm runs in O(n^2) time using O(n) work space, where n is the number of terminal ta...
1207.1417
Michal Rosen-Zvi
Michal Rosen-Zvi, Michael I. Jordan, Alan Yuille
The DLR Hierarchy of Approximate Inference
Appears in Proceedings of the Twenty-First Conference on Uncertainty in Artificial Intelligence (UAI2005)
null
null
UAI-P-2005-PG-493-500
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We propose a hierarchy for approximate inference based on the Dobrushin, Lanford, Ruelle (DLR) equations. This hierarchy includes existing algorithms, such as belief propagation, and also motivates novel algorithms such as factorized neighbors (FN) algorithms and variants of mean field (MF) algorithms. In particular,...
[ { "created": "Wed, 4 Jul 2012 16:25:12 GMT", "version": "v1" } ]
2015-03-20
[ [ "Rosen-Zvi", "Michal", "" ], [ "Jordan", "Michael I.", "" ], [ "Yuille", "Alan", "" ] ]
We propose a hierarchy for approximate inference based on the Dobrushin, Lanford, Ruelle (DLR) equations. This hierarchy includes existing algorithms, such as belief propagation, and also motivates novel algorithms such as factorized neighbors (FN) algorithms and variants of mean field (MF) algorithms. In particular, w...