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2011.03186
Chong Liu
Chong Liu, Yuqing Zhu, Kamalika Chaudhuri, and Yu-Xiang Wang
Revisiting Model-Agnostic Private Learning: Faster Rates and Active Learning
null
Journal of Machine Learning Research 22(262) (2021) 1-44
null
null
cs.LG cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The Private Aggregation of Teacher Ensembles (PATE) framework is one of the most promising recent approaches in differentially private learning. Existing theoretical analysis shows that PATE consistently learns any VC-classes in the realizable setting, but falls short in explaining its success in more general cases w...
[ { "created": "Fri, 6 Nov 2020 04:35:32 GMT", "version": "v1" }, { "created": "Fri, 13 Nov 2020 08:19:15 GMT", "version": "v2" }, { "created": "Tue, 21 Sep 2021 18:02:38 GMT", "version": "v3" }, { "created": "Fri, 11 Mar 2022 22:44:07 GMT", "version": "v4" } ]
2022-03-15
[ [ "Liu", "Chong", "" ], [ "Zhu", "Yuqing", "" ], [ "Chaudhuri", "Kamalika", "" ], [ "Wang", "Yu-Xiang", "" ] ]
The Private Aggregation of Teacher Ensembles (PATE) framework is one of the most promising recent approaches in differentially private learning. Existing theoretical analysis shows that PATE consistently learns any VC-classes in the realizable setting, but falls short in explaining its success in more general cases whe...
2004.00472
Dileep Kalathil
Archana Bura, Desik Rengarajan, Dileep Kalathil, Srinivas Shakkottai, and Jean-Francois Chamberland-Tremblay
Learning to Cache and Caching to Learn: Regret Analysis of Caching Algorithms
null
null
null
null
cs.NI cs.SY eess.SY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Crucial performance metrics of a caching algorithm include its ability to quickly and accurately learn a popularity distribution of requests. However, a majority of work on analytical performance analysis focuses on hit probability after an asymptotically large time has elapsed. We consider an online learning viewpoi...
[ { "created": "Wed, 1 Apr 2020 14:38:53 GMT", "version": "v1" } ]
2020-04-02
[ [ "Bura", "Archana", "" ], [ "Rengarajan", "Desik", "" ], [ "Kalathil", "Dileep", "" ], [ "Shakkottai", "Srinivas", "" ], [ "Chamberland-Tremblay", "Jean-Francois", "" ] ]
Crucial performance metrics of a caching algorithm include its ability to quickly and accurately learn a popularity distribution of requests. However, a majority of work on analytical performance analysis focuses on hit probability after an asymptotically large time has elapsed. We consider an online learning viewpoint...
2306.04911
Jungwuk Park
Jungwuk Park, Dong-Jun Han, Soyeong Kim, Jaekyun Moon
Test-Time Style Shifting: Handling Arbitrary Styles in Domain Generalization
ICML 2023 camera-ready version
null
null
null
cs.CV cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In domain generalization (DG), the target domain is unknown when the model is being trained, and the trained model should successfully work on an arbitrary (and possibly unseen) target domain during inference. This is a difficult problem, and despite active studies in recent years, it remains a great challenge. In th...
[ { "created": "Thu, 8 Jun 2023 03:26:16 GMT", "version": "v1" }, { "created": "Tue, 13 Jun 2023 00:37:33 GMT", "version": "v2" } ]
2023-06-14
[ [ "Park", "Jungwuk", "" ], [ "Han", "Dong-Jun", "" ], [ "Kim", "Soyeong", "" ], [ "Moon", "Jaekyun", "" ] ]
In domain generalization (DG), the target domain is unknown when the model is being trained, and the trained model should successfully work on an arbitrary (and possibly unseen) target domain during inference. This is a difficult problem, and despite active studies in recent years, it remains a great challenge. In this...
1905.07065
Li Chen
Li Chen
Privacy Preserving Adjacency Spectral Embedding on Stochastic Blockmodels
Accepted at Learning and Reasoning with Graph-Structured Representations at ICML 2019
null
null
null
cs.LG cs.CR stat.ME stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
For graphs generated from stochastic blockmodels, adjacency spectral embedding is asymptotically consistent. Further, adjacency spectral embedding composed with universally consistent classifiers is universally consistent to achieve the Bayes error. However when the graph contains private or sensitive information, tr...
[ { "created": "Thu, 16 May 2019 23:43:45 GMT", "version": "v1" } ]
2019-05-20
[ [ "Chen", "Li", "" ] ]
For graphs generated from stochastic blockmodels, adjacency spectral embedding is asymptotically consistent. Further, adjacency spectral embedding composed with universally consistent classifiers is universally consistent to achieve the Bayes error. However when the graph contains private or sensitive information, trea...
2406.07115
Yibo Wang
Sijia Chen, Yibo Wang, Yi-Feng Wu, Qing-Guo Chen, Zhao Xu, Weihua Luo, Kaifu Zhang, Lijun Zhang
Advancing Tool-Augmented Large Language Models: Integrating Insights from Errors in Inference Trees
null
null
null
null
cs.CL cs.AI cs.LG
http://creativecommons.org/licenses/by/4.0/
Tool-augmented large language models (LLMs) leverage tools, often in the form of APIs, to enhance their reasoning capabilities on complex tasks, thus taking on the role of intelligent agents interacting with the real world. The recently introduced ToolLLaMA model by Qin et al. [2024] utilizes the depth-first search-b...
[ { "created": "Tue, 11 Jun 2024 10:00:18 GMT", "version": "v1" } ]
2024-06-12
[ [ "Chen", "Sijia", "" ], [ "Wang", "Yibo", "" ], [ "Wu", "Yi-Feng", "" ], [ "Chen", "Qing-Guo", "" ], [ "Xu", "Zhao", "" ], [ "Luo", "Weihua", "" ], [ "Zhang", "Kaifu", "" ], [ "Zhang", "Lijun", ...
Tool-augmented large language models (LLMs) leverage tools, often in the form of APIs, to enhance their reasoning capabilities on complex tasks, thus taking on the role of intelligent agents interacting with the real world. The recently introduced ToolLLaMA model by Qin et al. [2024] utilizes the depth-first search-bas...
1503.03270
Vandna Bhalla Ms
Vandna Bhalla, Santanu Chaudhury, Arihant Jain
A Novel Hybrid CNN-AIS Visual Pattern Recognition Engine
null
null
null
null
cs.CV
http://creativecommons.org/licenses/by/3.0/
Machine learning methods are used today for most recognition problems. Convolutional Neural Networks (CNN) have time and again proved successful for many image processing tasks primarily for their architecture. In this paper we propose to apply CNN to small data sets like for example, personal albums or other similar...
[ { "created": "Wed, 11 Mar 2015 10:58:25 GMT", "version": "v1" } ]
2015-03-12
[ [ "Bhalla", "Vandna", "" ], [ "Chaudhury", "Santanu", "" ], [ "Jain", "Arihant", "" ] ]
Machine learning methods are used today for most recognition problems. Convolutional Neural Networks (CNN) have time and again proved successful for many image processing tasks primarily for their architecture. In this paper we propose to apply CNN to small data sets like for example, personal albums or other similar e...
1906.03764
Adam Harley
Adam W. Harley and Shrinidhi K. Lakshmikanth and Fangyu Li and Xian Zhou and Hsiao-Yu Fish Tung and Katerina Fragkiadaki
Learning from Unlabelled Videos Using Contrastive Predictive Neural 3D Mapping
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Predictive coding theories suggest that the brain learns by predicting observations at various levels of abstraction. One of the most basic prediction tasks is view prediction: how would a given scene look from an alternative viewpoint? Humans excel at this task. Our ability to imagine and fill in missing information...
[ { "created": "Mon, 10 Jun 2019 01:53:42 GMT", "version": "v1" }, { "created": "Mon, 24 Jun 2019 02:02:58 GMT", "version": "v2" }, { "created": "Wed, 10 Jul 2019 23:02:29 GMT", "version": "v3" }, { "created": "Mon, 30 Sep 2019 18:52:19 GMT", "version": "v4" }, { "c...
2020-05-19
[ [ "Harley", "Adam W.", "" ], [ "Lakshmikanth", "Shrinidhi K.", "" ], [ "Li", "Fangyu", "" ], [ "Zhou", "Xian", "" ], [ "Tung", "Hsiao-Yu Fish", "" ], [ "Fragkiadaki", "Katerina", "" ] ]
Predictive coding theories suggest that the brain learns by predicting observations at various levels of abstraction. One of the most basic prediction tasks is view prediction: how would a given scene look from an alternative viewpoint? Humans excel at this task. Our ability to imagine and fill in missing information i...
2202.06600
JunJie Li
Junjie Li and Hui Cao
Research on Dual Channel News Headline Classification Based on ERNIE Pre-training Model
null
null
null
null
cs.CL cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The classification of news headlines is an important direction in the field of NLP, and its data has the characteristics of compactness, uniqueness and various forms. Aiming at the problem that the traditional neural network model cannot adequately capture the underlying feature information of the data and cannot joi...
[ { "created": "Mon, 14 Feb 2022 10:44:12 GMT", "version": "v1" } ]
2022-02-15
[ [ "Li", "Junjie", "" ], [ "Cao", "Hui", "" ] ]
The classification of news headlines is an important direction in the field of NLP, and its data has the characteristics of compactness, uniqueness and various forms. Aiming at the problem that the traditional neural network model cannot adequately capture the underlying feature information of the data and cannot joint...
2309.00242
Sepideh Aghamolaei
Sepideh Aghamolaei and Mohammad Ghodsi
A Massively Parallel Dynamic Programming for Approximate Rectangle Escape Problem
null
null
null
null
cs.CG cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Sublinear time complexity is required by the massively parallel computation (MPC) model. Breaking dynamic programs into a set of sparse dynamic programs that can be divided, solved, and merged in sublinear time. The rectangle escape problem (REP) is defined as follows: For $n$ axis-aligned rectangles inside an axis...
[ { "created": "Fri, 1 Sep 2023 04:23:15 GMT", "version": "v1" } ]
2023-09-04
[ [ "Aghamolaei", "Sepideh", "" ], [ "Ghodsi", "Mohammad", "" ] ]
Sublinear time complexity is required by the massively parallel computation (MPC) model. Breaking dynamic programs into a set of sparse dynamic programs that can be divided, solved, and merged in sublinear time. The rectangle escape problem (REP) is defined as follows: For $n$ axis-aligned rectangles inside an axis-ali...
2205.02393
Aili Shen
Aili Shen, Xudong Han, Trevor Cohn, Timothy Baldwin, Lea Frermann
Optimising Equal Opportunity Fairness in Model Training
Accepted to NAACL 2022 main conference
null
null
null
cs.LG cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Real-world datasets often encode stereotypes and societal biases. Such biases can be implicitly captured by trained models, leading to biased predictions and exacerbating existing societal preconceptions. Existing debiasing methods, such as adversarial training and removing protected information from representations,...
[ { "created": "Thu, 5 May 2022 01:57:58 GMT", "version": "v1" } ]
2022-05-06
[ [ "Shen", "Aili", "" ], [ "Han", "Xudong", "" ], [ "Cohn", "Trevor", "" ], [ "Baldwin", "Timothy", "" ], [ "Frermann", "Lea", "" ] ]
Real-world datasets often encode stereotypes and societal biases. Such biases can be implicitly captured by trained models, leading to biased predictions and exacerbating existing societal preconceptions. Existing debiasing methods, such as adversarial training and removing protected information from representations, h...
2408.08002
Srinivas Vivek
Deep Inder Mohan and Srinivas Vivek
Practical Privacy-Preserving Identity Verification using Third-Party Cloud Services and FHE (Role of Data Encoding in Circuit Depth Management)
This work was presented (without proceedings) at the Turing Trustworthy Digital Identity International Conference 2022 at The Alan Turing Institute, London, UK, on Sep. 16, 2022
null
null
null
cs.CR
http://creativecommons.org/licenses/by/4.0/
National digital identity verification systems have played a critical role in the effective distribution of goods and services, particularly, in developing countries. Due to the cost involved in deploying and maintaining such systems, combined with a lack of in-house technical expertise, governments seek to outsource...
[ { "created": "Thu, 15 Aug 2024 08:12:07 GMT", "version": "v1" } ]
2024-08-16
[ [ "Mohan", "Deep Inder", "" ], [ "Vivek", "Srinivas", "" ] ]
National digital identity verification systems have played a critical role in the effective distribution of goods and services, particularly, in developing countries. Due to the cost involved in deploying and maintaining such systems, combined with a lack of in-house technical expertise, governments seek to outsource t...
2403.07199
Fabian Weigend
Fabian C Weigend, Xiao Liu, Shubham Sonawani, Neelesh Kumar, Venugopal Vasudevan, Heni Ben Amor
iRoCo: Intuitive Robot Control From Anywhere Using a Smartwatch
7 pages, 7 Figures, 4 Tables, Conference: ICRA
null
10.1109/ICRA57147.2024.10610805
null
cs.RO
http://creativecommons.org/licenses/by/4.0/
This paper introduces iRoCo (intuitive Robot Control) - a framework for ubiquitous human-robot collaboration using a single smartwatch and smartphone. By integrating probabilistic differentiable filters, iRoCo optimizes a combination of precise robot control and unrestricted user movement from ubiquitous devices. We ...
[ { "created": "Mon, 11 Mar 2024 22:47:07 GMT", "version": "v1" } ]
2024-08-15
[ [ "Weigend", "Fabian C", "" ], [ "Liu", "Xiao", "" ], [ "Sonawani", "Shubham", "" ], [ "Kumar", "Neelesh", "" ], [ "Vasudevan", "Venugopal", "" ], [ "Amor", "Heni Ben", "" ] ]
This paper introduces iRoCo (intuitive Robot Control) - a framework for ubiquitous human-robot collaboration using a single smartwatch and smartphone. By integrating probabilistic differentiable filters, iRoCo optimizes a combination of precise robot control and unrestricted user movement from ubiquitous devices. We de...
2109.02353
Hang Liu
Hang Liu, Zehong Lin, Xiaojun Yuan, and Ying-Jun Angela Zhang
Reconfigurable Intelligent Surface Empowered Over-the-Air Federated Edge Learning
This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible
null
null
null
cs.IT cs.LG cs.NI eess.SP math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Federated edge learning (FEEL) has emerged as a revolutionary paradigm to develop AI services at the edge of 6G wireless networks as it supports collaborative model training at a massive number of mobile devices. However, model communication over wireless channels, especially in uplink model uploading of FEEL, has be...
[ { "created": "Mon, 6 Sep 2021 10:44:54 GMT", "version": "v1" }, { "created": "Wed, 20 Jul 2022 03:33:40 GMT", "version": "v2" } ]
2022-07-21
[ [ "Liu", "Hang", "" ], [ "Lin", "Zehong", "" ], [ "Yuan", "Xiaojun", "" ], [ "Zhang", "Ying-Jun Angela", "" ] ]
Federated edge learning (FEEL) has emerged as a revolutionary paradigm to develop AI services at the edge of 6G wireless networks as it supports collaborative model training at a massive number of mobile devices. However, model communication over wireless channels, especially in uplink model uploading of FEEL, has been...
2310.07397
Jian Wang
Jian Wang, Yi Cheng, Dongding Lin, Chak Tou Leong, Wenjie Li
Target-oriented Proactive Dialogue Systems with Personalization: Problem Formulation and Dataset Curation
Accepted to EMNLP-2023 main conference
null
null
null
cs.CL cs.AI
http://creativecommons.org/licenses/by/4.0/
Target-oriented dialogue systems, designed to proactively steer conversations toward predefined targets or accomplish specific system-side goals, are an exciting area in conversational AI. In this work, by formulating a <dialogue act, topic> pair as the conversation target, we explore a novel problem of personalized ...
[ { "created": "Wed, 11 Oct 2023 11:32:57 GMT", "version": "v1" }, { "created": "Fri, 13 Oct 2023 11:16:58 GMT", "version": "v2" } ]
2023-10-16
[ [ "Wang", "Jian", "" ], [ "Cheng", "Yi", "" ], [ "Lin", "Dongding", "" ], [ "Leong", "Chak Tou", "" ], [ "Li", "Wenjie", "" ] ]
Target-oriented dialogue systems, designed to proactively steer conversations toward predefined targets or accomplish specific system-side goals, are an exciting area in conversational AI. In this work, by formulating a <dialogue act, topic> pair as the conversation target, we explore a novel problem of personalized ta...
1801.09522
Sharath Adavanne
Sharath Adavanne, Archontis Politis, Tuomas Virtanen
Multichannel Sound Event Detection Using 3D Convolutional Neural Networks for Learning Inter-channel Features
null
null
null
null
cs.SD cs.LG eess.AS
http://creativecommons.org/licenses/by-nc-sa/4.0/
In this paper, we propose a stacked convolutional and recurrent neural network (CRNN) with a 3D convolutional neural network (CNN) in the first layer for the multichannel sound event detection (SED) task. The 3D CNN enables the network to simultaneously learn the inter- and intra-channel features from the input multi...
[ { "created": "Mon, 29 Jan 2018 14:24:39 GMT", "version": "v1" } ]
2018-01-30
[ [ "Adavanne", "Sharath", "" ], [ "Politis", "Archontis", "" ], [ "Virtanen", "Tuomas", "" ] ]
In this paper, we propose a stacked convolutional and recurrent neural network (CRNN) with a 3D convolutional neural network (CNN) in the first layer for the multichannel sound event detection (SED) task. The 3D CNN enables the network to simultaneously learn the inter- and intra-channel features from the input multich...
1809.04662
Marco Baldi
Massimo Battaglioni, Alireza Tasdighi, Marco Baldi, Mohammad H. Tadayon, Franco Chiaraluce
Compact QC-LDPC Block and SC-LDPC Convolutional Codes for Low-Latency Communications
5 pages, 1 figure, presented at IEEE PIMRC 2018
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Low decoding latency and complexity are two important requirements of channel codes used in many applications, like machine-to-machine communications. In this paper, we show how these requirements can be fulfilled by using some special quasi-cyclic low-density parity-check block codes and spatially coupled low-densit...
[ { "created": "Wed, 12 Sep 2018 20:26:31 GMT", "version": "v1" } ]
2018-09-14
[ [ "Battaglioni", "Massimo", "" ], [ "Tasdighi", "Alireza", "" ], [ "Baldi", "Marco", "" ], [ "Tadayon", "Mohammad H.", "" ], [ "Chiaraluce", "Franco", "" ] ]
Low decoding latency and complexity are two important requirements of channel codes used in many applications, like machine-to-machine communications. In this paper, we show how these requirements can be fulfilled by using some special quasi-cyclic low-density parity-check block codes and spatially coupled low-density ...
1909.04770
Oscar Luis Vera P\'erez
Oscar Luis Vera-P\'erez, Benjamin Danglot, Martin Monperrus, Benoit Baudry
Suggestions on Test Suite Improvements with Automatic Infection and Propagation Analysis
null
null
null
null
cs.SE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
An extreme transformation removes the body of a method that is reached by one test case at least. If the test suite passes on the original program and still passes after the extreme transformation, the transformation is said to be undetected, and the test suite needs to be improved. In this work we propose a techniqu...
[ { "created": "Tue, 10 Sep 2019 21:46:01 GMT", "version": "v1" } ]
2019-09-12
[ [ "Vera-Pérez", "Oscar Luis", "" ], [ "Danglot", "Benjamin", "" ], [ "Monperrus", "Martin", "" ], [ "Baudry", "Benoit", "" ] ]
An extreme transformation removes the body of a method that is reached by one test case at least. If the test suite passes on the original program and still passes after the extreme transformation, the transformation is said to be undetected, and the test suite needs to be improved. In this work we propose a technique ...
2304.02812
Katherine Stasaski
Katherine Stasaski and Marti A. Hearst
Pragmatically Appropriate Diversity for Dialogue Evaluation
null
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
Linguistic pragmatics state that a conversation's underlying speech acts can constrain the type of response which is appropriate at each turn in the conversation. When generating dialogue responses, neural dialogue agents struggle to produce diverse responses. Currently, dialogue diversity is assessed using automatic...
[ { "created": "Thu, 6 Apr 2023 01:24:18 GMT", "version": "v1" } ]
2023-04-07
[ [ "Stasaski", "Katherine", "" ], [ "Hearst", "Marti A.", "" ] ]
Linguistic pragmatics state that a conversation's underlying speech acts can constrain the type of response which is appropriate at each turn in the conversation. When generating dialogue responses, neural dialogue agents struggle to produce diverse responses. Currently, dialogue diversity is assessed using automatic m...
1909.08248
EPTCS
Felicidad Aguado (IRLab, CITIC Research Center, University of A Coru\~na, Spain), Pedro Cabalar (IRLab, CITIC Research Center, University of A Coru\~na, Spain), Jorge Fandinno (University of Potsdam, Germany), Brais Mu\~niz (IRLab, CITIC Research Center, University of A Coru\~na, Spain), Gilberto P\'erez (IRLab...
A Rule-Based System for Explainable Donor-Patient Matching in Liver Transplantation
In Proceedings ICLP 2019, arXiv:1909.07646
EPTCS 306, 2019, pp. 266-272
10.4204/EPTCS.306.31
null
cs.LO cs.AI cs.PL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper we present web-liver, a rule-based system for decision support in the medical domain, focusing on its application in a liver transplantation unit for implementing policies for donor-patient matching. The rule-based system is built on top of an interpreter for logic programs with partial functions, calle...
[ { "created": "Wed, 18 Sep 2019 07:08:25 GMT", "version": "v1" } ]
2019-09-19
[ [ "Aguado", "Felicidad", "", "IRLab, CITIC Research Center, University of A\n Coruña, Spain" ], [ "Cabalar", "Pedro", "", "IRLab, CITIC Research Center, University of\n A Coruña, Spain" ], [ "Fandinno", "Jorge", "", "University of Potsdam, Germany" ], [ ...
In this paper we present web-liver, a rule-based system for decision support in the medical domain, focusing on its application in a liver transplantation unit for implementing policies for donor-patient matching. The rule-based system is built on top of an interpreter for logic programs with partial functions, called ...
2102.12459
Tao Lei
Tao Lei
When Attention Meets Fast Recurrence: Training Language Models with Reduced Compute
null
EMNLP 2021
null
null
cs.CL cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Large language models have become increasingly difficult to train because of the growing computation time and cost. In this work, we present SRU++, a highly-efficient architecture that combines fast recurrence and attention for sequence modeling. SRU++ exhibits strong modeling capacity and training efficiency. On sta...
[ { "created": "Wed, 24 Feb 2021 18:39:56 GMT", "version": "v1" }, { "created": "Tue, 30 Mar 2021 16:32:25 GMT", "version": "v2" }, { "created": "Wed, 15 Sep 2021 03:59:10 GMT", "version": "v3" } ]
2021-09-16
[ [ "Lei", "Tao", "" ] ]
Large language models have become increasingly difficult to train because of the growing computation time and cost. In this work, we present SRU++, a highly-efficient architecture that combines fast recurrence and attention for sequence modeling. SRU++ exhibits strong modeling capacity and training efficiency. On stand...
2112.14243
Adrian Haret
Adrian Haret, Johannes P. Wallner
An AGM Approach to Revising Preferences
Presented at the NMR 2021 workshop
null
null
null
cs.AI
http://creativecommons.org/licenses/by/4.0/
We look at preference change arising out of an interaction between two elements: the first is an initial preference ranking encoding a pre-existing attitude; the second element is new preference information signaling input from an authoritative source, which may come into conflict with the initial preference. The aim...
[ { "created": "Tue, 28 Dec 2021 18:12:57 GMT", "version": "v1" } ]
2021-12-30
[ [ "Haret", "Adrian", "" ], [ "Wallner", "Johannes P.", "" ] ]
We look at preference change arising out of an interaction between two elements: the first is an initial preference ranking encoding a pre-existing attitude; the second element is new preference information signaling input from an authoritative source, which may come into conflict with the initial preference. The aim i...
2103.13425
Xiaohan Ding
Xiaohan Ding, Xiangyu Zhang, Jungong Han, Guiguang Ding
Diverse Branch Block: Building a Convolution as an Inception-like Unit
CVPR 2021
null
null
null
cs.CV cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We propose a universal building block of Convolutional Neural Network (ConvNet) to improve the performance without any inference-time costs. The block is named Diverse Branch Block (DBB), which enhances the representational capacity of a single convolution by combining diverse branches of different scales and complex...
[ { "created": "Wed, 24 Mar 2021 18:12:00 GMT", "version": "v1" }, { "created": "Mon, 29 Mar 2021 13:00:50 GMT", "version": "v2" } ]
2021-03-30
[ [ "Ding", "Xiaohan", "" ], [ "Zhang", "Xiangyu", "" ], [ "Han", "Jungong", "" ], [ "Ding", "Guiguang", "" ] ]
We propose a universal building block of Convolutional Neural Network (ConvNet) to improve the performance without any inference-time costs. The block is named Diverse Branch Block (DBB), which enhances the representational capacity of a single convolution by combining diverse branches of different scales and complexit...
1611.08725
F. Richard Yu
Meng Li, F. Richard Yu, Pengbo Si, Enchang Sun, Yanhua Zhang, and Haipeng Yao
Machine-to-Machine (M2M) Communications in Software-defined and Virtualized Cellular Networks
arXiv admin note: text overlap with arXiv:1611.05087
null
null
null
cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Machine-to-machine (M2M) communications have attracted great attention from both academia and industry. In this paper, with recent advances in wireless network virtualization and software-defined networking (SDN), we propose a novel framework for M2M communications in software-defined cellular networks with wireless ...
[ { "created": "Sat, 26 Nov 2016 17:57:31 GMT", "version": "v1" } ]
2016-11-29
[ [ "Li", "Meng", "" ], [ "Yu", "F. Richard", "" ], [ "Si", "Pengbo", "" ], [ "Sun", "Enchang", "" ], [ "Zhang", "Yanhua", "" ], [ "Yao", "Haipeng", "" ] ]
Machine-to-machine (M2M) communications have attracted great attention from both academia and industry. In this paper, with recent advances in wireless network virtualization and software-defined networking (SDN), we propose a novel framework for M2M communications in software-defined cellular networks with wireless ne...
1503.00756
Marco Stronati
Konstantinos Chatzikokolakis, Catuscia Palamidessi, Marco Stronati
Constructing elastic distinguishability metrics for location privacy
null
null
10.1515/popets-2015-0023
null
cs.CR
http://creativecommons.org/licenses/by/3.0/
With the increasing popularity of hand-held devices, location-based applications and services have access to accurate and real-time location information, raising serious privacy concerns for their users. The recently introduced notion of geo-indistinguishability tries to address this problem by adapting the well-know...
[ { "created": "Mon, 2 Mar 2015 21:32:11 GMT", "version": "v1" }, { "created": "Thu, 21 May 2015 09:39:47 GMT", "version": "v2" } ]
2015-05-22
[ [ "Chatzikokolakis", "Konstantinos", "" ], [ "Palamidessi", "Catuscia", "" ], [ "Stronati", "Marco", "" ] ]
With the increasing popularity of hand-held devices, location-based applications and services have access to accurate and real-time location information, raising serious privacy concerns for their users. The recently introduced notion of geo-indistinguishability tries to address this problem by adapting the well-known ...
2306.04280
Jeremy Straub
Matthew Tassava, Cameron Kolodjski, Jeremy Straub
Development of a System Vulnerability Analysis Tool for Assessment of Complex Mission Critical Systems
null
null
null
null
cs.CR
http://creativecommons.org/licenses/by-nc-nd/4.0/
A system vulnerability analysis technique (SVAT) for complex mission critical systems (CMCS) was developed in response to the need to be able to conduct penetration testing on large industrial systems which cannot be taken offline or risk disablement or impairment for conventional penetration testing. SVAT-CMCS facil...
[ { "created": "Wed, 7 Jun 2023 09:35:47 GMT", "version": "v1" } ]
2023-06-08
[ [ "Tassava", "Matthew", "" ], [ "Kolodjski", "Cameron", "" ], [ "Straub", "Jeremy", "" ] ]
A system vulnerability analysis technique (SVAT) for complex mission critical systems (CMCS) was developed in response to the need to be able to conduct penetration testing on large industrial systems which cannot be taken offline or risk disablement or impairment for conventional penetration testing. SVAT-CMCS facilit...
2204.05454
Mengmeng Ma
Mengmeng Ma, Jian Ren, Long Zhao, Davide Testuggine, Xi Peng
Are Multimodal Transformers Robust to Missing Modality?
In CVPR 2022
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Multimodal data collected from the real world are often imperfect due to missing modalities. Therefore multimodal models that are robust against modal-incomplete data are highly preferred. Recently, Transformer models have shown great success in processing multimodal data. However, existing work has been limited to e...
[ { "created": "Tue, 12 Apr 2022 00:21:31 GMT", "version": "v1" } ]
2022-04-13
[ [ "Ma", "Mengmeng", "" ], [ "Ren", "Jian", "" ], [ "Zhao", "Long", "" ], [ "Testuggine", "Davide", "" ], [ "Peng", "Xi", "" ] ]
Multimodal data collected from the real world are often imperfect due to missing modalities. Therefore multimodal models that are robust against modal-incomplete data are highly preferred. Recently, Transformer models have shown great success in processing multimodal data. However, existing work has been limited to eit...
2004.09007
Ahmed Abdelkader
Ahmed Abdelkader, Michael J. Curry, Liam Fowl, Tom Goldstein, Avi Schwarzschild, Manli Shu, Christoph Studer, Chen Zhu
Headless Horseman: Adversarial Attacks on Transfer Learning Models
5 pages, 2 figures. Accepted in ICASSP 2020. Code available on https://github.com/zhuchen03/headless-attack.git
null
10.1109/ICASSP40776.2020.9053181
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Transfer learning facilitates the training of task-specific classifiers using pre-trained models as feature extractors. We present a family of transferable adversarial attacks against such classifiers, generated without access to the classification head; we call these \emph{headless attacks}. We first demonstrate suc...
[ { "created": "Mon, 20 Apr 2020 01:07:45 GMT", "version": "v1" } ]
2020-04-21
[ [ "Abdelkader", "Ahmed", "" ], [ "Curry", "Michael J.", "" ], [ "Fowl", "Liam", "" ], [ "Goldstein", "Tom", "" ], [ "Schwarzschild", "Avi", "" ], [ "Shu", "Manli", "" ], [ "Studer", "Christoph", "" ], [ ...
Transfer learning facilitates the training of task-specific classifiers using pre-trained models as feature extractors. We present a family of transferable adversarial attacks against such classifiers, generated without access to the classification head; we call these \emph{headless attacks}. We first demonstrate succe...
2309.04259
Paul Bilokon
Paul Bilokon and Burak Gunduz
C++ Design Patterns for Low-latency Applications Including High-frequency Trading
null
null
null
null
cs.PF q-fin.TR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This work aims to bridge the existing knowledge gap in the optimisation of latency-critical code, specifically focusing on high-frequency trading (HFT) systems. The research culminates in three main contributions: the creation of a Low-Latency Programming Repository, the optimisation of a market-neutral statistical a...
[ { "created": "Fri, 8 Sep 2023 11:01:05 GMT", "version": "v1" } ]
2023-09-11
[ [ "Bilokon", "Paul", "" ], [ "Gunduz", "Burak", "" ] ]
This work aims to bridge the existing knowledge gap in the optimisation of latency-critical code, specifically focusing on high-frequency trading (HFT) systems. The research culminates in three main contributions: the creation of a Low-Latency Programming Repository, the optimisation of a market-neutral statistical arb...
1908.09031
Jiachen Li
Jiachen Li and Wei Zhan and Yeping Hu and Masayoshi Tomizuka
Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving
IEEE Transactions on Intelligent Transportation Systems
null
10.1109/TITS.2019.2930310
null
cs.RO cs.CV cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Accurately tracking and predicting behaviors of surrounding objects are key prerequisites for intelligent systems such as autonomous vehicles to achieve safe and high-quality decision making and motion planning. However, there still remain challenges for multi-target tracking due to object number fluctuation and occl...
[ { "created": "Fri, 23 Aug 2019 20:34:53 GMT", "version": "v1" } ]
2020-03-31
[ [ "Li", "Jiachen", "" ], [ "Zhan", "Wei", "" ], [ "Hu", "Yeping", "" ], [ "Tomizuka", "Masayoshi", "" ] ]
Accurately tracking and predicting behaviors of surrounding objects are key prerequisites for intelligent systems such as autonomous vehicles to achieve safe and high-quality decision making and motion planning. However, there still remain challenges for multi-target tracking due to object number fluctuation and occlus...
2405.20310
Jianghao Shen
Jianghao Shen, Nan Xue, Tianfu Wu
A Pixel Is Worth More Than One 3D Gaussians in Single-View 3D Reconstruction
preprint, under review
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Learning 3D scene representation from a single-view image is a long-standing fundamental problem in computer vision, with the inherent ambiguity in predicting contents unseen from the input view. Built on the recently proposed 3D Gaussian Splatting (3DGS), the Splatter Image method has made promising progress on fast...
[ { "created": "Thu, 30 May 2024 17:52:52 GMT", "version": "v1" }, { "created": "Fri, 31 May 2024 15:27:52 GMT", "version": "v2" }, { "created": "Mon, 3 Jun 2024 15:13:55 GMT", "version": "v3" } ]
2024-06-04
[ [ "Shen", "Jianghao", "" ], [ "Xue", "Nan", "" ], [ "Wu", "Tianfu", "" ] ]
Learning 3D scene representation from a single-view image is a long-standing fundamental problem in computer vision, with the inherent ambiguity in predicting contents unseen from the input view. Built on the recently proposed 3D Gaussian Splatting (3DGS), the Splatter Image method has made promising progress on fast s...
1809.04585
Yichen Jiang
Yichen Jiang, Mohit Bansal
Closed-Book Training to Improve Summarization Encoder Memory
EMNLP 2018 (16 pages)
null
null
null
cs.CL cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A good neural sequence-to-sequence summarization model should have a strong encoder that can distill and memorize the important information from long input texts so that the decoder can generate salient summaries based on the encoder's memory. In this paper, we aim to improve the memorization capabilities of the enco...
[ { "created": "Wed, 12 Sep 2018 17:50:07 GMT", "version": "v1" } ]
2018-09-13
[ [ "Jiang", "Yichen", "" ], [ "Bansal", "Mohit", "" ] ]
A good neural sequence-to-sequence summarization model should have a strong encoder that can distill and memorize the important information from long input texts so that the decoder can generate salient summaries based on the encoder's memory. In this paper, we aim to improve the memorization capabilities of the encode...
2306.03937
Gwendolyne Legate
Gwen Legate, Nicolas Bernier, Lucas Caccia, Edouard Oyallon, Eugene Belilovsky
Guiding The Last Layer in Federated Learning with Pre-Trained Models
null
null
null
null
cs.LG cs.AI
http://creativecommons.org/licenses/by/4.0/
Federated Learning (FL) is an emerging paradigm that allows a model to be trained across a number of participants without sharing data. Recent works have begun to consider the effects of using pre-trained models as an initialization point for existing FL algorithms; however, these approaches ignore the vast body of e...
[ { "created": "Tue, 6 Jun 2023 18:02:02 GMT", "version": "v1" }, { "created": "Mon, 6 Nov 2023 18:19:49 GMT", "version": "v2" } ]
2023-11-07
[ [ "Legate", "Gwen", "" ], [ "Bernier", "Nicolas", "" ], [ "Caccia", "Lucas", "" ], [ "Oyallon", "Edouard", "" ], [ "Belilovsky", "Eugene", "" ] ]
Federated Learning (FL) is an emerging paradigm that allows a model to be trained across a number of participants without sharing data. Recent works have begun to consider the effects of using pre-trained models as an initialization point for existing FL algorithms; however, these approaches ignore the vast body of eff...
2402.04075
Reza Khanmohammadi
Reza Khanmohammadi, Ahmed I Ghanem, Kyle Verdecchia, Ryan Hall, Mohamed Elshaikh, Benjamin Movsas, Hassan Bagher-Ebadian, Indrin Chetty, Mohammad M. Ghassemi, Kundan Thind
Iterative Prompt Refinement for Radiation Oncology Symptom Extraction Using Teacher-Student Large Language Models
null
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
This study introduces a novel teacher-student architecture utilizing Large Language Models (LLMs) to improve prostate cancer radiotherapy symptom extraction from clinical notes. Mixtral, the student model, initially extracts symptoms, followed by GPT-4, the teacher model, which refines prompts based on Mixtral's perf...
[ { "created": "Tue, 6 Feb 2024 15:25:09 GMT", "version": "v1" } ]
2024-02-07
[ [ "Khanmohammadi", "Reza", "" ], [ "Ghanem", "Ahmed I", "" ], [ "Verdecchia", "Kyle", "" ], [ "Hall", "Ryan", "" ], [ "Elshaikh", "Mohamed", "" ], [ "Movsas", "Benjamin", "" ], [ "Bagher-Ebadian", "Hassan", "...
This study introduces a novel teacher-student architecture utilizing Large Language Models (LLMs) to improve prostate cancer radiotherapy symptom extraction from clinical notes. Mixtral, the student model, initially extracts symptoms, followed by GPT-4, the teacher model, which refines prompts based on Mixtral's perfor...
1912.05393
Martijn Wezel Van
M.J.A. van Wezel, L.J. Hamburger, Y. Napolean
Fine-grained Classification of Rowing teams
7 pages, NCCV 2019, 6 figures, deep learning, attention learning, CNN, rowing boat, team detector, club detector, data set, dataset
null
null
null
cs.CV cs.LG eess.IV
http://creativecommons.org/licenses/by/4.0/
Fine-grained classification tasks such as identifying different breeds of dog are quite challenging as visual differences between categories is quite small and can be easily overwhelmed by external factors such as object pose, lighting, etc. This work focuses on the specific case of classifying rowing teams from vari...
[ { "created": "Wed, 11 Dec 2019 15:36:25 GMT", "version": "v1" } ]
2019-12-12
[ [ "van Wezel", "M. J. A.", "" ], [ "Hamburger", "L. J.", "" ], [ "Napolean", "Y.", "" ] ]
Fine-grained classification tasks such as identifying different breeds of dog are quite challenging as visual differences between categories is quite small and can be easily overwhelmed by external factors such as object pose, lighting, etc. This work focuses on the specific case of classifying rowing teams from variou...
2103.17202
Abhinav Kumar
Abhinav Kumar, Garrick Brazil and Xiaoming Liu
GrooMeD-NMS: Grouped Mathematically Differentiable NMS for Monocular 3D Object Detection
Accepted to CVPR 2021
null
null
null
cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Modern 3D object detectors have immensely benefited from the end-to-end learning idea. However, most of them use a post-processing algorithm called Non-Maximal Suppression (NMS) only during inference. While there were attempts to include NMS in the training pipeline for tasks such as 2D object detection, they have be...
[ { "created": "Wed, 31 Mar 2021 16:29:50 GMT", "version": "v1" } ]
2021-04-01
[ [ "Kumar", "Abhinav", "" ], [ "Brazil", "Garrick", "" ], [ "Liu", "Xiaoming", "" ] ]
Modern 3D object detectors have immensely benefited from the end-to-end learning idea. However, most of them use a post-processing algorithm called Non-Maximal Suppression (NMS) only during inference. While there were attempts to include NMS in the training pipeline for tasks such as 2D object detection, they have been...
1411.6593
David Tolpin
David Tolpin, Oded Betzalel, Ariel Felner, Solomon Eyal Shimony
Rational Deployment of Multiple Heuristics in IDA*
7 pages, 6 tables, 20 references
null
null
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recent advances in metareasoning for search has shown its usefulness in improving numerous search algorithms. This paper applies rational metareasoning to IDA* when several admissible heuristics are available. The obvious basic approach of taking the maximum of the heuristics is improved upon by lazy evaluation of th...
[ { "created": "Mon, 24 Nov 2014 20:04:20 GMT", "version": "v1" } ]
2014-11-25
[ [ "Tolpin", "David", "" ], [ "Betzalel", "Oded", "" ], [ "Felner", "Ariel", "" ], [ "Shimony", "Solomon Eyal", "" ] ]
Recent advances in metareasoning for search has shown its usefulness in improving numerous search algorithms. This paper applies rational metareasoning to IDA* when several admissible heuristics are available. The obvious basic approach of taking the maximum of the heuristics is improved upon by lazy evaluation of the ...
2403.10378
Haonan Li
Rocktim Jyoti Das and Simeon Emilov Hristov and Haonan Li and Dimitar Iliyanov Dimitrov and Ivan Koychev and Preslav Nakov
EXAMS-V: A Multi-Discipline Multilingual Multimodal Exam Benchmark for Evaluating Vision Language Models
null
null
null
null
cs.CL cs.CV
http://creativecommons.org/licenses/by-nc-sa/4.0/
We introduce EXAMS-V, a new challenging multi-discipline multimodal multilingual exam benchmark for evaluating vision language models. It consists of 20,932 multiple-choice questions across 20 school disciplines covering natural science, social science, and other miscellaneous studies, e.g., religion, fine arts, busi...
[ { "created": "Fri, 15 Mar 2024 15:08:39 GMT", "version": "v1" } ]
2024-03-18
[ [ "Das", "Rocktim Jyoti", "" ], [ "Hristov", "Simeon Emilov", "" ], [ "Li", "Haonan", "" ], [ "Dimitrov", "Dimitar Iliyanov", "" ], [ "Koychev", "Ivan", "" ], [ "Nakov", "Preslav", "" ] ]
We introduce EXAMS-V, a new challenging multi-discipline multimodal multilingual exam benchmark for evaluating vision language models. It consists of 20,932 multiple-choice questions across 20 school disciplines covering natural science, social science, and other miscellaneous studies, e.g., religion, fine arts, busine...
0805.2438
Russell O'Connor
Russell O'Connor
Certified Exact Transcendental Real Number Computation in Coq
This paper is to be part of the proceedings of the 21st International Conference on Theorem Proving in Higher Order Logics (TPHOLs 2008)
Ait Mohamed, C. Munoz, and S. Tahar (Eds.): TPHOLs 2008, LNCS 5170, pp. 246-261, 2008
10.1007/978-3-540-71067-7_21
null
cs.LO cs.MS cs.NA
http://creativecommons.org/licenses/publicdomain/
Reasoning about real number expressions in a proof assistant is challenging. Several problems in theorem proving can be solved by using exact real number computation. I have implemented a library for reasoning and computing with complete metric spaces in the Coq proof assistant and used this library to build a constr...
[ { "created": "Fri, 16 May 2008 18:02:24 GMT", "version": "v1" } ]
2010-08-04
[ [ "O'Connor", "Russell", "" ] ]
Reasoning about real number expressions in a proof assistant is challenging. Several problems in theorem proving can be solved by using exact real number computation. I have implemented a library for reasoning and computing with complete metric spaces in the Coq proof assistant and used this library to build a construc...
2405.06948
Shengyuan Liu
Shengyuan Liu, Bo Wang, Ye Ma, Te Yang, Xipeng Cao, Quan Chen, Han Li, Di Dong, Peng Jiang
Training-free Subject-Enhanced Attention Guidance for Compositional Text-to-image Generation
26 pages, 13 figures
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Existing subject-driven text-to-image generation models suffer from tedious fine-tuning steps and struggle to maintain both text-image alignment and subject fidelity. For generating compositional subjects, it often encounters problems such as object missing and attribute mixing, where some subjects in the input promp...
[ { "created": "Sat, 11 May 2024 08:11:25 GMT", "version": "v1" } ]
2024-05-14
[ [ "Liu", "Shengyuan", "" ], [ "Wang", "Bo", "" ], [ "Ma", "Ye", "" ], [ "Yang", "Te", "" ], [ "Cao", "Xipeng", "" ], [ "Chen", "Quan", "" ], [ "Li", "Han", "" ], [ "Dong", "Di", "" ], [ ...
Existing subject-driven text-to-image generation models suffer from tedious fine-tuning steps and struggle to maintain both text-image alignment and subject fidelity. For generating compositional subjects, it often encounters problems such as object missing and attribute mixing, where some subjects in the input prompt ...
1602.08139
Jean-Marc Valin
Jean-Marc Valin, Fran\c{c}ois Michaud, Jean Rouat
Robust Localization and Tracking of Simultaneous Moving Sound Sources Using Beamforming and Particle Filtering
26 pages
Robotics and Autonomous Systems Journal (Elsevier), Vol. 55, No. 3, pp. 216-228, 2007
10.1016/j.robot.2006.08.004
null
cs.RO cs.SD
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Mobile robots in real-life settings would benefit from being able to localize and track sound sources. Such a capability can help localizing a person or an interesting event in the environment, and also provides enhanced processing for other capabilities such as speech recognition. To give this capability to a robot,...
[ { "created": "Thu, 25 Feb 2016 22:40:00 GMT", "version": "v1" } ]
2016-02-29
[ [ "Valin", "Jean-Marc", "" ], [ "Michaud", "François", "" ], [ "Rouat", "Jean", "" ] ]
Mobile robots in real-life settings would benefit from being able to localize and track sound sources. Such a capability can help localizing a person or an interesting event in the environment, and also provides enhanced processing for other capabilities such as speech recognition. To give this capability to a robot, t...
2306.06930
Wenying Duan
Wenying Duan, Xiaoxi He, Zimu Zhou, Lothar Thiele, Hong Rao
Localised Adaptive Spatial-Temporal Graph Neural Network
This paper was accepted by KDD 2023
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Spatial-temporal graph models are prevailing for abstracting and modelling spatial and temporal dependencies. In this work, we ask the following question: whether and to what extent can we localise spatial-temporal graph models? We limit our scope to adaptive spatial-temporal graph neural networks (ASTGNNs), the stat...
[ { "created": "Mon, 12 Jun 2023 08:08:53 GMT", "version": "v1" }, { "created": "Thu, 15 Jun 2023 13:54:24 GMT", "version": "v2" } ]
2023-06-16
[ [ "Duan", "Wenying", "" ], [ "He", "Xiaoxi", "" ], [ "Zhou", "Zimu", "" ], [ "Thiele", "Lothar", "" ], [ "Rao", "Hong", "" ] ]
Spatial-temporal graph models are prevailing for abstracting and modelling spatial and temporal dependencies. In this work, we ask the following question: whether and to what extent can we localise spatial-temporal graph models? We limit our scope to adaptive spatial-temporal graph neural networks (ASTGNNs), the state-...
2405.02732
Sneha Singhania
Sneha Singhania, Simon Razniewski, Gerhard Weikum
Recall Them All: Retrieval-Augmented Language Models for Long Object List Extraction from Long Documents
null
null
null
null
cs.CL cs.IR
http://creativecommons.org/licenses/by/4.0/
Methods for relation extraction from text mostly focus on high precision, at the cost of limited recall. High recall is crucial, though, to populate long lists of object entities that stand in a specific relation with a given subject. Cues for relevant objects can be spread across many passages in long texts. This po...
[ { "created": "Sat, 4 May 2024 18:32:08 GMT", "version": "v1" } ]
2024-05-07
[ [ "Singhania", "Sneha", "" ], [ "Razniewski", "Simon", "" ], [ "Weikum", "Gerhard", "" ] ]
Methods for relation extraction from text mostly focus on high precision, at the cost of limited recall. High recall is crucial, though, to populate long lists of object entities that stand in a specific relation with a given subject. Cues for relevant objects can be spread across many passages in long texts. This pose...
1501.06813
Frank Staals
Maarten L\"offler, Martin N\"ollenburg, Frank Staals
Mixed Map Labeling
Full version for the paper accepted at CIAC 2015
null
null
null
cs.CG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Point feature map labeling is a geometric problem, in which a set of input points must be labeled with a set of disjoint rectangles (the bounding boxes of the label texts). Typically, labeling models either use internal labels, which must touch their feature point, or external (boundary) labels, which are placed on o...
[ { "created": "Tue, 27 Jan 2015 16:40:19 GMT", "version": "v1" } ]
2015-01-28
[ [ "Löffler", "Maarten", "" ], [ "Nöllenburg", "Martin", "" ], [ "Staals", "Frank", "" ] ]
Point feature map labeling is a geometric problem, in which a set of input points must be labeled with a set of disjoint rectangles (the bounding boxes of the label texts). Typically, labeling models either use internal labels, which must touch their feature point, or external (boundary) labels, which are placed on one...
2006.04663
Benjamin Doerr
Benjamin Doerr
Runtime Analysis of Evolutionary Algorithms via Symmetry Arguments
Minor changes compared to the previous version
Inf. Process. Lett. 166: 106064 (2021)
10.1016/j.ipl.2020.106064
null
cs.NE cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We use an elementary argument building on group actions to prove that the selection-free steady state genetic algorithm analyzed by Sutton and Witt (GECCO 2019) takes an expected number of $\Omega(2^n / \sqrt n)$ iterations to find any particular target search point. This bound is valid for all population sizes $\mu$...
[ { "created": "Mon, 8 Jun 2020 15:04:51 GMT", "version": "v1" }, { "created": "Thu, 20 Aug 2020 11:32:39 GMT", "version": "v2" }, { "created": "Sat, 31 Oct 2020 10:42:28 GMT", "version": "v3" } ]
2021-09-21
[ [ "Doerr", "Benjamin", "" ] ]
We use an elementary argument building on group actions to prove that the selection-free steady state genetic algorithm analyzed by Sutton and Witt (GECCO 2019) takes an expected number of $\Omega(2^n / \sqrt n)$ iterations to find any particular target search point. This bound is valid for all population sizes $\mu$. ...
2107.09786
Jingtao Li
Xing Chen, Jingtao Li and Chaitali Chakrabarti
Communication and Computation Reduction for Split Learning using Asynchronous Training
Accepted by SIPS '21
null
10.1109/SiPS52927.2021.00022
null
cs.LG
http://creativecommons.org/licenses/by/4.0/
Split learning is a promising privacy-preserving distributed learning scheme that has low computation requirement at the edge device but has the disadvantage of high communication overhead between edge device and server. To reduce the communication overhead, this paper proposes a loss-based asynchronous training sche...
[ { "created": "Tue, 20 Jul 2021 22:08:13 GMT", "version": "v1" } ]
2022-03-10
[ [ "Chen", "Xing", "" ], [ "Li", "Jingtao", "" ], [ "Chakrabarti", "Chaitali", "" ] ]
Split learning is a promising privacy-preserving distributed learning scheme that has low computation requirement at the edge device but has the disadvantage of high communication overhead between edge device and server. To reduce the communication overhead, this paper proposes a loss-based asynchronous training scheme...
2211.07065
Eunchan Kim
Byeongmin Choi, YongHyun Lee, Yeunwoong Kyung and Eunchan Kim
ALBERT with Knowledge Graph Encoder Utilizing Semantic Similarity for Commonsense Question Answering
12 pages, 9 figures
Intelligent Automation & Soft Computing, vol. 36, no.1, pp. 71-82, 2023
10.32604/iasc.2023.032783
null
cs.CL cs.AI
http://creativecommons.org/licenses/by-nc-nd/4.0/
Recently, pre-trained language representation models such as bidirectional encoder representations from transformers (BERT) have been performing well in commonsense question answering (CSQA). However, there is a problem that the models do not directly use explicit information of knowledge sources existing outside. To...
[ { "created": "Mon, 14 Nov 2022 01:39:26 GMT", "version": "v1" } ]
2022-11-15
[ [ "Choi", "Byeongmin", "" ], [ "Lee", "YongHyun", "" ], [ "Kyung", "Yeunwoong", "" ], [ "Kim", "Eunchan", "" ] ]
Recently, pre-trained language representation models such as bidirectional encoder representations from transformers (BERT) have been performing well in commonsense question answering (CSQA). However, there is a problem that the models do not directly use explicit information of knowledge sources existing outside. To a...
2211.02044
Sven J\"ager
Sven J\"ager, Guillaume Sagnol, Daniel Schmidt genannt Waldschmidt, Philipp Warode
Competitive Kill-and-Restart and Preemptive Strategies for Non-Clairvoyant Scheduling
An extended abstract occurred in the Proceedings of the 24th International Conference on Integer Programming and Combinatorial Optimization
null
10.1007/s10107-024-02118-8
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We study kill-and-restart and preemptive strategies for the fundamental scheduling problem of minimizing the sum of weighted completion times on a single machine in the non-clairvoyant setting. First, we show a lower bound of~$3$ for any deterministic non-clairvoyant kill-and-restart strategy. Then, we give for any $...
[ { "created": "Thu, 3 Nov 2022 17:57:28 GMT", "version": "v1" }, { "created": "Mon, 14 Nov 2022 11:09:16 GMT", "version": "v2" }, { "created": "Thu, 1 Jun 2023 16:21:30 GMT", "version": "v3" } ]
2024-07-24
[ [ "Jäger", "Sven", "" ], [ "Sagnol", "Guillaume", "" ], [ "Waldschmidt", "Daniel Schmidt genannt", "" ], [ "Warode", "Philipp", "" ] ]
We study kill-and-restart and preemptive strategies for the fundamental scheduling problem of minimizing the sum of weighted completion times on a single machine in the non-clairvoyant setting. First, we show a lower bound of~$3$ for any deterministic non-clairvoyant kill-and-restart strategy. Then, we give for any $b ...
2403.14003
Alessandro Favero
Alessandro Favero, Luca Zancato, Matthew Trager, Siddharth Choudhary, Pramuditha Perera, Alessandro Achille, Ashwin Swaminathan, Stefano Soatto
Multi-Modal Hallucination Control by Visual Information Grounding
null
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2024
null
null
cs.CV cs.CL cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Generative Vision-Language Models (VLMs) are prone to generate plausible-sounding textual answers that, however, are not always grounded in the input image. We investigate this phenomenon, usually referred to as "hallucination" and show that it stems from an excessive reliance on the language prior. In particular, we...
[ { "created": "Wed, 20 Mar 2024 22:05:18 GMT", "version": "v1" } ]
2024-03-22
[ [ "Favero", "Alessandro", "" ], [ "Zancato", "Luca", "" ], [ "Trager", "Matthew", "" ], [ "Choudhary", "Siddharth", "" ], [ "Perera", "Pramuditha", "" ], [ "Achille", "Alessandro", "" ], [ "Swaminathan", "Ashwin"...
Generative Vision-Language Models (VLMs) are prone to generate plausible-sounding textual answers that, however, are not always grounded in the input image. We investigate this phenomenon, usually referred to as "hallucination" and show that it stems from an excessive reliance on the language prior. In particular, we s...
2005.08946
Fatemah Husain
Fatemah Husain
Arabic Offensive Language Detection Using Machine Learning and Ensemble Machine Learning Approaches
5 pages, 3 figures. arXiv admin note: text overlap with arXiv:2005.07297
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
This study aims at investigating the effect of applying single learner machine learning approach and ensemble machine learning approach for offensive language detection on Arabic language. Classifying Arabic social media text is a very challenging task due to the ambiguity and informality of the written format of the...
[ { "created": "Sat, 16 May 2020 06:40:36 GMT", "version": "v1" } ]
2020-05-20
[ [ "Husain", "Fatemah", "" ] ]
This study aims at investigating the effect of applying single learner machine learning approach and ensemble machine learning approach for offensive language detection on Arabic language. Classifying Arabic social media text is a very challenging task due to the ambiguity and informality of the written format of the t...
2302.13687
Albert Li
Albert H. Li, Preston Culbertson, Joel W. Burdick, Aaron D. Ames
FRoGGeR: Fast Robust Grasp Generation via the Min-Weight Metric
Accepted at IROS 2023. The arXiv version contains the appendix, which does not appear in the conference version
null
null
null
cs.RO math.OC
http://creativecommons.org/licenses/by-nc-nd/4.0/
Many approaches to grasp synthesis optimize analytic quality metrics that measure grasp robustness based on finger placements and local surface geometry. However, generating feasible dexterous grasps by optimizing these metrics is slow, often taking minutes. To address this issue, this paper presents FRoGGeR: a metho...
[ { "created": "Mon, 27 Feb 2023 11:46:13 GMT", "version": "v1" }, { "created": "Mon, 24 Jul 2023 07:23:45 GMT", "version": "v2" } ]
2023-07-25
[ [ "Li", "Albert H.", "" ], [ "Culbertson", "Preston", "" ], [ "Burdick", "Joel W.", "" ], [ "Ames", "Aaron D.", "" ] ]
Many approaches to grasp synthesis optimize analytic quality metrics that measure grasp robustness based on finger placements and local surface geometry. However, generating feasible dexterous grasps by optimizing these metrics is slow, often taking minutes. To address this issue, this paper presents FRoGGeR: a method ...
1011.5168
Emilio Ferrara
Salvatore Catanese, Pasquale De Meo, Emilio Ferrara, Giacomo Fiumara
Analyzing the Facebook Friendship Graph
6 pages, 1 figure; MIFI '10: Proceedings of the 1st International Workshop on Mining the Future Internet
Proceedings of the 1st International Workshop on Mining the Future Internet (MIFI '10), 2010
null
null
cs.SI physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Online Social Networks (OSN) during last years acquired a huge and increasing popularity as one of the most important emerging Web phenomena, deeply modifying the behavior of users and contributing to build a solid substrate of connections and relationships among people using the Web. In this preliminary work paper, ...
[ { "created": "Tue, 23 Nov 2010 17:07:32 GMT", "version": "v1" }, { "created": "Thu, 2 Jun 2011 15:10:49 GMT", "version": "v2" } ]
2011-06-03
[ [ "Catanese", "Salvatore", "" ], [ "De Meo", "Pasquale", "" ], [ "Ferrara", "Emilio", "" ], [ "Fiumara", "Giacomo", "" ] ]
Online Social Networks (OSN) during last years acquired a huge and increasing popularity as one of the most important emerging Web phenomena, deeply modifying the behavior of users and contributing to build a solid substrate of connections and relationships among people using the Web. In this preliminary work paper, ou...
2402.02037
Huang Dong
Dong Huang, Yuhao Qing, Weiyi Shang, Heming Cui, Jie M.Zhang
EffiBench: Benchmarking the Efficiency of Automatically Generated Code
30 pages, 7 figures
null
null
null
cs.SE cs.CL
http://creativecommons.org/licenses/by/4.0/
Code generation models have increasingly become integral to aiding software development. Although current research has thoroughly examined the correctness of the code produced by code generation models, a vital aspect that plays a pivotal role in green computing and sustainability efforts has often been neglected. Th...
[ { "created": "Sat, 3 Feb 2024 05:24:39 GMT", "version": "v1" }, { "created": "Thu, 15 Feb 2024 15:57:06 GMT", "version": "v2" }, { "created": "Fri, 7 Jun 2024 09:21:21 GMT", "version": "v3" }, { "created": "Thu, 4 Jul 2024 02:55:05 GMT", "version": "v4" } ]
2024-07-08
[ [ "Huang", "Dong", "" ], [ "Qing", "Yuhao", "" ], [ "Shang", "Weiyi", "" ], [ "Cui", "Heming", "" ], [ "Zhang", "Jie M.", "" ] ]
Code generation models have increasingly become integral to aiding software development. Although current research has thoroughly examined the correctness of the code produced by code generation models, a vital aspect that plays a pivotal role in green computing and sustainability efforts has often been neglected. This...
2102.04588
Debasish Mohapatra
Debasish Ray Mohapatra, Victor Zappi, Sidney Fels
A comparative study of two-dimensional vocal tract acoustic modeling based on Finite-Difference Time-Domain methods
4 pages, 3 figures
null
null
null
cs.SD cs.CL eess.AS
http://creativecommons.org/licenses/by/4.0/
The two-dimensional (2D) numerical approaches for vocal tract (VT) modelling can afford a better balance between the low computational cost and accurate rendering of acoustic wave propagation. However, they require a high spatio-temporal resolution in the numerical scheme for a precise estimation of acoustic formants...
[ { "created": "Tue, 9 Feb 2021 00:40:52 GMT", "version": "v1" } ]
2021-02-10
[ [ "Mohapatra", "Debasish Ray", "" ], [ "Zappi", "Victor", "" ], [ "Fels", "Sidney", "" ] ]
The two-dimensional (2D) numerical approaches for vocal tract (VT) modelling can afford a better balance between the low computational cost and accurate rendering of acoustic wave propagation. However, they require a high spatio-temporal resolution in the numerical scheme for a precise estimation of acoustic formants a...
1911.05281
Chen Xu
Chen Xu, Jian Wang, Tianhang Yu, Chuili Kong, Yourui Huangfu, Rong Li, Yiqun Ge, Jun Wang
Buffer-aware Wireless Scheduling based on Deep Reinforcement Learning
submitted to WCNC2020
null
null
null
cs.IT cs.LG math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, the downlink packet scheduling problem for cellular networks is modeled, which jointly optimizes throughput, fairness and packet drop rate. Two genie-aided heuristic search methods are employed to explore the solution space. A deep reinforcement learning (DRL) framework with A2C algorithm is proposed f...
[ { "created": "Wed, 13 Nov 2019 04:15:02 GMT", "version": "v1" } ]
2019-11-14
[ [ "Xu", "Chen", "" ], [ "Wang", "Jian", "" ], [ "Yu", "Tianhang", "" ], [ "Kong", "Chuili", "" ], [ "Huangfu", "Yourui", "" ], [ "Li", "Rong", "" ], [ "Ge", "Yiqun", "" ], [ "Wang", "Jun", "" ...
In this paper, the downlink packet scheduling problem for cellular networks is modeled, which jointly optimizes throughput, fairness and packet drop rate. Two genie-aided heuristic search methods are employed to explore the solution space. A deep reinforcement learning (DRL) framework with A2C algorithm is proposed for...
1607.03516
Muhammad Ghifary
Muhammad Ghifary and W. Bastiaan Kleijn and Mengjie Zhang and David Balduzzi and Wen Li
Deep Reconstruction-Classification Networks for Unsupervised Domain Adaptation
to appear in European Conference on Computer Vision (ECCV) 2016
null
null
null
cs.CV cs.AI cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we propose a novel unsupervised domain adaptation algorithm based on deep learning for visual object recognition. Specifically, we design a new model called Deep Reconstruction-Classification Network (DRCN), which jointly learns a shared encoding representation for two tasks: i) supervised classificati...
[ { "created": "Tue, 12 Jul 2016 20:48:58 GMT", "version": "v1" }, { "created": "Mon, 1 Aug 2016 09:58:13 GMT", "version": "v2" } ]
2016-08-03
[ [ "Ghifary", "Muhammad", "" ], [ "Kleijn", "W. Bastiaan", "" ], [ "Zhang", "Mengjie", "" ], [ "Balduzzi", "David", "" ], [ "Li", "Wen", "" ] ]
In this paper, we propose a novel unsupervised domain adaptation algorithm based on deep learning for visual object recognition. Specifically, we design a new model called Deep Reconstruction-Classification Network (DRCN), which jointly learns a shared encoding representation for two tasks: i) supervised classification...
2006.10645
Xiaohang Zhan
Xiaohang Zhan, Jiahao Xie, Ziwei Liu, Yew Soon Ong, Chen Change Loy
Online Deep Clustering for Unsupervised Representation Learning
Accepted by CVPR 2020. Code: https://github.com/open-mmlab/OpenSelfSup
null
null
null
cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Joint clustering and feature learning methods have shown remarkable performance in unsupervised representation learning. However, the training schedule alternating between feature clustering and network parameters update leads to unstable learning of visual representations. To overcome this challenge, we propose Onli...
[ { "created": "Thu, 18 Jun 2020 16:15:46 GMT", "version": "v1" } ]
2020-06-19
[ [ "Zhan", "Xiaohang", "" ], [ "Xie", "Jiahao", "" ], [ "Liu", "Ziwei", "" ], [ "Ong", "Yew Soon", "" ], [ "Loy", "Chen Change", "" ] ]
Joint clustering and feature learning methods have shown remarkable performance in unsupervised representation learning. However, the training schedule alternating between feature clustering and network parameters update leads to unstable learning of visual representations. To overcome this challenge, we propose Online...
1705.03250
George Grispos
George Grispos and Jesus Garcia-Galan and Liliana Pasquale and Bashar Nuseibeh
Are You Ready? Towards the Engineering of Forensic-Ready Systems
Presented at IEEE 11th International Conference on Research Challenges in Information Science, Brighton, United Kindgom
null
null
null
cs.SE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
As security incidents continue to impact organisations, there is a growing demand for systems to be 'forensic ready'- to maximise the potential use of evidence whilst minimising the costs of an investigation. Researchers have supported organisational forensic readiness efforts by proposing the use of policies and pro...
[ { "created": "Tue, 9 May 2017 09:47:01 GMT", "version": "v1" }, { "created": "Mon, 15 May 2017 12:51:38 GMT", "version": "v2" } ]
2017-05-16
[ [ "Grispos", "George", "" ], [ "Garcia-Galan", "Jesus", "" ], [ "Pasquale", "Liliana", "" ], [ "Nuseibeh", "Bashar", "" ] ]
As security incidents continue to impact organisations, there is a growing demand for systems to be 'forensic ready'- to maximise the potential use of evidence whilst minimising the costs of an investigation. Researchers have supported organisational forensic readiness efforts by proposing the use of policies and proce...
1711.09368
Siyu Zhou
Siyu Zhou, Weiqiang Zhao, Jiashi Feng, Hanjiang Lai, Yan Pan, Jian Yin, Shuicheng Yan
Personalized and Occupational-aware Age Progression by Generative Adversarial Networks
9 pages, 10 figures
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Face age progression, which aims to predict the future looks, is important for various applications and has been received considerable attentions. Existing methods and datasets are limited in exploring the effects of occupations which may influence the personal appearances. In this paper, we firstly introduce an occu...
[ { "created": "Sun, 26 Nov 2017 10:50:56 GMT", "version": "v1" }, { "created": "Fri, 1 Dec 2017 06:58:03 GMT", "version": "v2" } ]
2017-12-04
[ [ "Zhou", "Siyu", "" ], [ "Zhao", "Weiqiang", "" ], [ "Feng", "Jiashi", "" ], [ "Lai", "Hanjiang", "" ], [ "Pan", "Yan", "" ], [ "Yin", "Jian", "" ], [ "Yan", "Shuicheng", "" ] ]
Face age progression, which aims to predict the future looks, is important for various applications and has been received considerable attentions. Existing methods and datasets are limited in exploring the effects of occupations which may influence the personal appearances. In this paper, we firstly introduce an occupa...
1912.01713
Oleksii Konashevych
Oleksii Konashevych
Cross-Blockchain Databases for Governments: The Technology for Public Registries and Smart Laws
This document needs major revision and is not going to be updated
null
null
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
There is an ongoing competition among blockchain technologies and the existence of one ultimate blockchain is impossible for many reasons. On the other hand, such variety can create difficulties in adoption, especially for the governments and corporations. The proposed technology ensures a blockchain agnostic approac...
[ { "created": "Thu, 28 Nov 2019 00:10:09 GMT", "version": "v1" }, { "created": "Fri, 24 Apr 2020 02:32:40 GMT", "version": "v2" } ]
2020-07-24
[ [ "Konashevych", "Oleksii", "" ] ]
There is an ongoing competition among blockchain technologies and the existence of one ultimate blockchain is impossible for many reasons. On the other hand, such variety can create difficulties in adoption, especially for the governments and corporations. The proposed technology ensures a blockchain agnostic approach ...
2003.07329
Jize Zhang
Jize Zhang and Bhavya Kailkhura and T. Yong-Jin Han
Mix-n-Match: Ensemble and Compositional Methods for Uncertainty Calibration in Deep Learning
ICML 2020
null
null
null
cs.LG stat.ML
http://creativecommons.org/licenses/by-nc-sa/4.0/
This paper studies the problem of post-hoc calibration of machine learning classifiers. We introduce the following desiderata for uncertainty calibration: (a) accuracy-preserving, (b) data-efficient, and (c) high expressive power. We show that none of the existing methods satisfy all three requirements, and demonstra...
[ { "created": "Mon, 16 Mar 2020 17:00:35 GMT", "version": "v1" }, { "created": "Tue, 30 Jun 2020 06:44:30 GMT", "version": "v2" } ]
2020-07-01
[ [ "Zhang", "Jize", "" ], [ "Kailkhura", "Bhavya", "" ], [ "Han", "T. Yong-Jin", "" ] ]
This paper studies the problem of post-hoc calibration of machine learning classifiers. We introduce the following desiderata for uncertainty calibration: (a) accuracy-preserving, (b) data-efficient, and (c) high expressive power. We show that none of the existing methods satisfy all three requirements, and demonstrate...
2004.02709
Matt Gardner
Matt Gardner, Yoav Artzi, Victoria Basmova, Jonathan Berant, Ben Bogin, Sihao Chen, Pradeep Dasigi, Dheeru Dua, Yanai Elazar, Ananth Gottumukkala, Nitish Gupta, Hanna Hajishirzi, Gabriel Ilharco, Daniel Khashabi, Kevin Lin, Jiangming Liu, Nelson F. Liu, Phoebe Mulcaire, Qiang Ning, Sameer Singh, Noah A. Smith, ...
Evaluating Models' Local Decision Boundaries via Contrast Sets
null
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
Standard test sets for supervised learning evaluate in-distribution generalization. Unfortunately, when a dataset has systematic gaps (e.g., annotation artifacts), these evaluations are misleading: a model can learn simple decision rules that perform well on the test set but do not capture a dataset's intended capabi...
[ { "created": "Mon, 6 Apr 2020 14:47:18 GMT", "version": "v1" }, { "created": "Thu, 1 Oct 2020 21:26:57 GMT", "version": "v2" } ]
2020-10-05
[ [ "Gardner", "Matt", "" ], [ "Artzi", "Yoav", "" ], [ "Basmova", "Victoria", "" ], [ "Berant", "Jonathan", "" ], [ "Bogin", "Ben", "" ], [ "Chen", "Sihao", "" ], [ "Dasigi", "Pradeep", "" ], [ "Dua", ...
Standard test sets for supervised learning evaluate in-distribution generalization. Unfortunately, when a dataset has systematic gaps (e.g., annotation artifacts), these evaluations are misleading: a model can learn simple decision rules that perform well on the test set but do not capture a dataset's intended capabili...
cs/0309041
Konstantin Rybnikov
Konstantin Rybnikov
Fast Verification of Convexity of Piecewise-linear Surfaces
10 pages (abbreviated version). Significantly different from all older versions. Discount the previous version -- it had many omissions and typos, like the following one: everything works starting from dimension n=3, not n=2 as was printed in the old abstract. Hyperbolic and spherical cases have been substantia...
null
null
null
cs.CG cs.CV
null
We show that a realization of a closed connected PL-manifold of dimension n-1 in n-dimensional Euclidean space (n>2) is the boundary of a convex polyhedron (finite or infinite) if and only if the interior of each (n-3)-face has a point, which has a neighborhood lying on the boundary of an n-dimensional convex body. N...
[ { "created": "Tue, 23 Sep 2003 06:47:28 GMT", "version": "v1" }, { "created": "Mon, 24 Nov 2003 11:23:31 GMT", "version": "v2" } ]
2007-05-23
[ [ "Rybnikov", "Konstantin", "" ] ]
We show that a realization of a closed connected PL-manifold of dimension n-1 in n-dimensional Euclidean space (n>2) is the boundary of a convex polyhedron (finite or infinite) if and only if the interior of each (n-3)-face has a point, which has a neighborhood lying on the boundary of an n-dimensional convex body. No ...
2312.15993
Ruidong Yan
Yuqi Zheng, Ruidong Yan, Bin Jia, Rui Jiang, Adriana TAPUS, Xiaojing Chen, Shiteng Zheng, Ying Shang
Adaptive Kalman-based hybrid car following strategy using TD3 and CACC
32pages,13figures
null
null
null
cs.AI cs.RO cs.SY eess.SY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In autonomous driving, the hybrid strategy of deep reinforcement learning and cooperative adaptive cruise control (CACC) can fully utilize the advantages of the two algorithms and significantly improve the performance of car following. However, it is challenging for the traditional hybrid strategy based on fixed coef...
[ { "created": "Tue, 26 Dec 2023 10:51:46 GMT", "version": "v1" } ]
2023-12-27
[ [ "Zheng", "Yuqi", "" ], [ "Yan", "Ruidong", "" ], [ "Jia", "Bin", "" ], [ "Jiang", "Rui", "" ], [ "TAPUS", "Adriana", "" ], [ "Chen", "Xiaojing", "" ], [ "Zheng", "Shiteng", "" ], [ "Shang", "Yin...
In autonomous driving, the hybrid strategy of deep reinforcement learning and cooperative adaptive cruise control (CACC) can fully utilize the advantages of the two algorithms and significantly improve the performance of car following. However, it is challenging for the traditional hybrid strategy based on fixed coeffi...
2405.04370
Junyi Ma
Junyi Ma, Jingyi Xu, Xieyuanli Chen, Hesheng Wang
Diff-IP2D: Diffusion-Based Hand-Object Interaction Prediction on Egocentric Videos
null
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Understanding how humans would behave during hand-object interaction is vital for applications in service robot manipulation and extended reality. To achieve this, some recent works have been proposed to simultaneously forecast hand trajectories and object affordances on human egocentric videos. The joint prediction ...
[ { "created": "Tue, 7 May 2024 14:51:05 GMT", "version": "v1" }, { "created": "Mon, 20 May 2024 02:57:51 GMT", "version": "v2" } ]
2024-05-21
[ [ "Ma", "Junyi", "" ], [ "Xu", "Jingyi", "" ], [ "Chen", "Xieyuanli", "" ], [ "Wang", "Hesheng", "" ] ]
Understanding how humans would behave during hand-object interaction is vital for applications in service robot manipulation and extended reality. To achieve this, some recent works have been proposed to simultaneously forecast hand trajectories and object affordances on human egocentric videos. The joint prediction se...
2102.03785
Rami Mochaourab
Rami Mochaourab and Sugandh Sinha and Stanley Greenstein and Panagiotis Papapetrou
Robust Explanations for Private Support Vector Machines
13 pages, 9 figures, 1 table
null
null
null
cs.LG cs.CR math.OC
http://creativecommons.org/licenses/by/4.0/
We consider counterfactual explanations for private support vector machines (SVM), where the privacy mechanism that publicly releases the classifier guarantees differential privacy. While privacy preservation is essential when dealing with sensitive data, there is a consequent degradation in the classification accura...
[ { "created": "Sun, 7 Feb 2021 11:55:32 GMT", "version": "v1" }, { "created": "Wed, 9 Jun 2021 19:21:19 GMT", "version": "v2" } ]
2021-06-11
[ [ "Mochaourab", "Rami", "" ], [ "Sinha", "Sugandh", "" ], [ "Greenstein", "Stanley", "" ], [ "Papapetrou", "Panagiotis", "" ] ]
We consider counterfactual explanations for private support vector machines (SVM), where the privacy mechanism that publicly releases the classifier guarantees differential privacy. While privacy preservation is essential when dealing with sensitive data, there is a consequent degradation in the classification accuracy...
1701.03263
Marten Maack
Klaus Jansen and Marten Maack
An EPTAS for Scheduling on Unrelated Machines of Few Different Types
null
null
null
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In the classical problem of scheduling on unrelated parallel machines, a set of jobs has to be assigned to a set of machines. The jobs have a processing time depending on the machine and the goal is to minimize the makespan, that is the maximum machine load. It is well known that this problem is NP-hard and does not ...
[ { "created": "Thu, 12 Jan 2017 08:12:36 GMT", "version": "v1" }, { "created": "Wed, 6 Dec 2017 16:22:53 GMT", "version": "v2" } ]
2017-12-07
[ [ "Jansen", "Klaus", "" ], [ "Maack", "Marten", "" ] ]
In the classical problem of scheduling on unrelated parallel machines, a set of jobs has to be assigned to a set of machines. The jobs have a processing time depending on the machine and the goal is to minimize the makespan, that is the maximum machine load. It is well known that this problem is NP-hard and does not al...
2308.06420
Yen Nhi Truong Vu
Yen Nhi Truong Vu, Dan Guo, Ahmed Taha, Jason Su, Thomas Paul Matthews
M&M: Tackling False Positives in Mammography with a Multi-view and Multi-instance Learning Sparse Detector
MICCAI 2023 with supplementary materials
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Deep-learning-based object detection methods show promise for improving screening mammography, but high rates of false positives can hinder their effectiveness in clinical practice. To reduce false positives, we identify three challenges: (1) unlike natural images, a malignant mammogram typically contains only one ma...
[ { "created": "Fri, 11 Aug 2023 23:59:47 GMT", "version": "v1" } ]
2023-08-15
[ [ "Vu", "Yen Nhi Truong", "" ], [ "Guo", "Dan", "" ], [ "Taha", "Ahmed", "" ], [ "Su", "Jason", "" ], [ "Matthews", "Thomas Paul", "" ] ]
Deep-learning-based object detection methods show promise for improving screening mammography, but high rates of false positives can hinder their effectiveness in clinical practice. To reduce false positives, we identify three challenges: (1) unlike natural images, a malignant mammogram typically contains only one mali...
1905.07903
Ruslan Nikolaev
Ruslan Nikolaev and Binoy Ravindran
Snapshot-Free, Transparent, and Robust Memory Reclamation for Lock-Free Data Structures
An extended version of the PLDI'21 paper (with Appendix)
42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation (PLDI 2021)
10.1145/3453483.3454090
null
cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present a family of safe memory reclamation schemes, Hyaline, which are fast, scalable, and transparent to the underlying lock-free data structures. Hyaline is based on reference counting - considered impractical for memory reclamation in the past due to high overheads. Hyaline uses reference counters only during ...
[ { "created": "Mon, 20 May 2019 06:34:15 GMT", "version": "v1" }, { "created": "Sat, 1 May 2021 13:38:45 GMT", "version": "v2" } ]
2021-05-04
[ [ "Nikolaev", "Ruslan", "" ], [ "Ravindran", "Binoy", "" ] ]
We present a family of safe memory reclamation schemes, Hyaline, which are fast, scalable, and transparent to the underlying lock-free data structures. Hyaline is based on reference counting - considered impractical for memory reclamation in the past due to high overheads. Hyaline uses reference counters only during re...
2103.16748
Ning Yu
Ning Yu, Guilin Liu, Aysegul Dundar, Andrew Tao, Bryan Catanzaro, Larry Davis, Mario Fritz
Dual Contrastive Loss and Attention for GANs
Accepted to ICCV'21
null
null
null
cs.CV cs.GR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Generative Adversarial Networks (GANs) produce impressive results on unconditional image generation when powered with large-scale image datasets. Yet generated images are still easy to spot especially on datasets with high variance (e.g. bedroom, church). In this paper, we propose various improvements to further push...
[ { "created": "Wed, 31 Mar 2021 01:10:26 GMT", "version": "v1" }, { "created": "Thu, 7 Oct 2021 10:58:28 GMT", "version": "v2" }, { "created": "Thu, 17 Mar 2022 20:59:31 GMT", "version": "v3" } ]
2022-03-21
[ [ "Yu", "Ning", "" ], [ "Liu", "Guilin", "" ], [ "Dundar", "Aysegul", "" ], [ "Tao", "Andrew", "" ], [ "Catanzaro", "Bryan", "" ], [ "Davis", "Larry", "" ], [ "Fritz", "Mario", "" ] ]
Generative Adversarial Networks (GANs) produce impressive results on unconditional image generation when powered with large-scale image datasets. Yet generated images are still easy to spot especially on datasets with high variance (e.g. bedroom, church). In this paper, we propose various improvements to further push t...
2103.15042
Yinyin He
Yin-Yin He, Jianxin Wu, Xiu-Shen Wei
Distilling Virtual Examples for Long-tailed Recognition
Accepted to ICCV 2021
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We tackle the long-tailed visual recognition problem from the knowledge distillation perspective by proposing a Distill the Virtual Examples (DiVE) method. Specifically, by treating the predictions of a teacher model as virtual examples, we prove that distilling from these virtual examples is equivalent to label dist...
[ { "created": "Sun, 28 Mar 2021 04:25:43 GMT", "version": "v1" }, { "created": "Sun, 29 Aug 2021 14:03:22 GMT", "version": "v2" }, { "created": "Sun, 19 Sep 2021 08:14:44 GMT", "version": "v3" } ]
2021-09-21
[ [ "He", "Yin-Yin", "" ], [ "Wu", "Jianxin", "" ], [ "Wei", "Xiu-Shen", "" ] ]
We tackle the long-tailed visual recognition problem from the knowledge distillation perspective by proposing a Distill the Virtual Examples (DiVE) method. Specifically, by treating the predictions of a teacher model as virtual examples, we prove that distilling from these virtual examples is equivalent to label distri...
2201.11653
Jin Hyun Park Mr
Jin Hyun Park
Representations learnt by SGD and Adaptive learning rules: Conditions that vary sparsity and selectivity in neural network
null
null
null
null
cs.LG cs.AI
http://creativecommons.org/licenses/by/4.0/
From the point of view of the human brain, continual learning can perform various tasks without mutual interference. An effective way to reduce mutual interference can be found in sparsity and selectivity of neurons. According to Aljundi et al. and Hadsell et al., imposing sparsity at the representational level is ad...
[ { "created": "Tue, 25 Jan 2022 05:40:24 GMT", "version": "v1" }, { "created": "Mon, 19 Feb 2024 09:08:11 GMT", "version": "v2" } ]
2024-02-21
[ [ "Park", "Jin Hyun", "" ] ]
From the point of view of the human brain, continual learning can perform various tasks without mutual interference. An effective way to reduce mutual interference can be found in sparsity and selectivity of neurons. According to Aljundi et al. and Hadsell et al., imposing sparsity at the representational level is adva...
2112.07431
Xiaomeng Li
Yi Li, Yiqun Duan, Zhanghui Kuang, Yimin Chen, Wayne Zhang, Xiaomeng Li
Uncertainty Estimation via Response Scaling for Pseudo-mask Noise Mitigation in Weakly-supervised Semantic Segmentation
Accept at AAAI 2022, Code is available at https://github.com/XMed-Lab/URN
null
null
null
cs.CV
http://creativecommons.org/publicdomain/zero/1.0/
Weakly-Supervised Semantic Segmentation (WSSS) segments objects without a heavy burden of dense annotation. While as a price, generated pseudo-masks exist obvious noisy pixels, which result in sub-optimal segmentation models trained over these pseudo-masks. But rare studies notice or work on this problem, even these ...
[ { "created": "Tue, 14 Dec 2021 14:37:19 GMT", "version": "v1" } ]
2021-12-15
[ [ "Li", "Yi", "" ], [ "Duan", "Yiqun", "" ], [ "Kuang", "Zhanghui", "" ], [ "Chen", "Yimin", "" ], [ "Zhang", "Wayne", "" ], [ "Li", "Xiaomeng", "" ] ]
Weakly-Supervised Semantic Segmentation (WSSS) segments objects without a heavy burden of dense annotation. While as a price, generated pseudo-masks exist obvious noisy pixels, which result in sub-optimal segmentation models trained over these pseudo-masks. But rare studies notice or work on this problem, even these no...
2408.03977
Mengting Li
Mengting Li, Chuang Zhu
Learning from Noisy Labels for Long-tailed Data via Optimal Transport
null
null
null
null
cs.LG cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Noisy labels, which are common in real-world datasets, can significantly impair the training of deep learning models. However, recent adversarial noise-combating methods overlook the long-tailed distribution of real data, which can significantly harm the effect of denoising strategies. Meanwhile, the mismanagement of...
[ { "created": "Wed, 7 Aug 2024 14:15:18 GMT", "version": "v1" } ]
2024-08-09
[ [ "Li", "Mengting", "" ], [ "Zhu", "Chuang", "" ] ]
Noisy labels, which are common in real-world datasets, can significantly impair the training of deep learning models. However, recent adversarial noise-combating methods overlook the long-tailed distribution of real data, which can significantly harm the effect of denoising strategies. Meanwhile, the mismanagement of n...
1612.01361
Hoang Dau
Hoang Dau and Iwan Duursma and Han Mao Kiah and Olgica Milenkovic
Repairing Reed-Solomon Codes With Multiple Erasures
15 pages
IEEE Transactions on Information Theory (2018) 64(10) 6567-6582
10.1109/TIT.2018.2827942
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Despite their exceptional error-correcting properties, Reed-Solomon codes have been overlooked in distributed storage applications due to the common belief that they have poor repair bandwidth: A naive repair approach would require the whole file to be reconstructed in order to recover a single erased codeword symbol...
[ { "created": "Mon, 28 Nov 2016 22:32:07 GMT", "version": "v1" }, { "created": "Sun, 3 May 2020 02:30:48 GMT", "version": "v2" } ]
2020-05-05
[ [ "Dau", "Hoang", "" ], [ "Duursma", "Iwan", "" ], [ "Kiah", "Han Mao", "" ], [ "Milenkovic", "Olgica", "" ] ]
Despite their exceptional error-correcting properties, Reed-Solomon codes have been overlooked in distributed storage applications due to the common belief that they have poor repair bandwidth: A naive repair approach would require the whole file to be reconstructed in order to recover a single erased codeword symbol. ...
1305.3586
Dilip Bethanabhotla
Dilip Bethanabhotla, Giuseppe Caire and Michael J. Neely
Utility Optimal Scheduling and Admission Control for Adaptive Video Streaming in Small Cell Networks
5 pages, 4 figures. Accepted and will be presented at IEEE International Symposium on Information Theory (ISIT) 2013
null
10.1109/ISIT.2013.6620565
null
cs.IT cs.MM cs.NI math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We consider the jointly optimal design of a transmission scheduling and admission control policy for adaptive video streaming over small cell networks. We formulate the problem as a dynamic network utility maximization and observe that it naturally decomposes into two subproblems: admission control and transmission s...
[ { "created": "Wed, 15 May 2013 18:56:03 GMT", "version": "v1" } ]
2016-11-17
[ [ "Bethanabhotla", "Dilip", "" ], [ "Caire", "Giuseppe", "" ], [ "Neely", "Michael J.", "" ] ]
We consider the jointly optimal design of a transmission scheduling and admission control policy for adaptive video streaming over small cell networks. We formulate the problem as a dynamic network utility maximization and observe that it naturally decomposes into two subproblems: admission control and transmission sch...
2309.07530
Pierre Gaillard
Pierre Gaillard (Thoth), S\'ebastien Gerchinovitz (IMT), \'Etienne de Montbrun (TSE-R)
Adaptive approximation of monotone functions
null
null
null
null
cs.LG cs.NA math.NA
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We study the classical problem of approximating a non-decreasing function $f: \mathcal{X} \to \mathcal{Y}$ in $L^p(\mu)$ norm by sequentially querying its values, for known compact real intervals $\mathcal{X}$, $\mathcal{Y}$ and a known probability measure $\mu$ on $\cX$. For any function~$f$ we characterize the mini...
[ { "created": "Thu, 14 Sep 2023 08:56:31 GMT", "version": "v1" } ]
2023-09-15
[ [ "Gaillard", "Pierre", "", "Thoth" ], [ "Gerchinovitz", "Sébastien", "", "IMT" ], [ "de Montbrun", "Étienne", "", "TSE-R" ] ]
We study the classical problem of approximating a non-decreasing function $f: \mathcal{X} \to \mathcal{Y}$ in $L^p(\mu)$ norm by sequentially querying its values, for known compact real intervals $\mathcal{X}$, $\mathcal{Y}$ and a known probability measure $\mu$ on $\cX$. For any function~$f$ we characterize the minimu...
1906.04091
Priyanka Bhovad
Priyanka Bhovad, Joshua Kaufmann, and Suyi Li
Peristaltic locomotion without digital controllers: Exploiting the origami multi-stability to coordinate robotic motions
null
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This study proposes and examines a novel approach to generate peristaltic-like locomotion in a segmented origami robot. Specifically, we demonstrate the use of multi-stability embedded in origami skeleton to eliminate the need for multiple actuators or digital controllers to coordinate the complex robotic movements i...
[ { "created": "Mon, 10 Jun 2019 16:10:04 GMT", "version": "v1" } ]
2019-06-11
[ [ "Bhovad", "Priyanka", "" ], [ "Kaufmann", "Joshua", "" ], [ "Li", "Suyi", "" ] ]
This study proposes and examines a novel approach to generate peristaltic-like locomotion in a segmented origami robot. Specifically, we demonstrate the use of multi-stability embedded in origami skeleton to eliminate the need for multiple actuators or digital controllers to coordinate the complex robotic movements in ...
2407.04573
Hang Gao
Hang Gao and Yongfeng Zhang
VRSD: Rethinking Similarity and Diversity for Retrieval in Large Language Models
null
null
null
null
cs.IR cs.CL
http://creativecommons.org/licenses/by/4.0/
Vector retrieval algorithms are vital for semantic queries in the evolving landscape of Large Language Models (LLMs). Retrieving vectors that simultaneously meet criteria for both similarity and diversity significantly enhances the capabilities of LLM-based agents. Despite the widespread use of the Maximal Marginal R...
[ { "created": "Fri, 5 Jul 2024 15:08:44 GMT", "version": "v1" } ]
2024-07-08
[ [ "Gao", "Hang", "" ], [ "Zhang", "Yongfeng", "" ] ]
Vector retrieval algorithms are vital for semantic queries in the evolving landscape of Large Language Models (LLMs). Retrieving vectors that simultaneously meet criteria for both similarity and diversity significantly enhances the capabilities of LLM-based agents. Despite the widespread use of the Maximal Marginal Rel...
2403.18258
Taro Togo
Taro Togo, Ren Togo, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama
Enhancing Generative Class Incremental Learning Performance with Model Forgetting Approach
null
null
null
null
cs.CV cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This study presents a novel approach to Generative Class Incremental Learning (GCIL) by introducing the forgetting mechanism, aimed at dynamically managing class information for better adaptation to streaming data. GCIL is one of the hot topics in the field of computer vision, and this is considered one of the crucia...
[ { "created": "Wed, 27 Mar 2024 05:10:38 GMT", "version": "v1" } ]
2024-03-28
[ [ "Togo", "Taro", "" ], [ "Togo", "Ren", "" ], [ "Maeda", "Keisuke", "" ], [ "Ogawa", "Takahiro", "" ], [ "Haseyama", "Miki", "" ] ]
This study presents a novel approach to Generative Class Incremental Learning (GCIL) by introducing the forgetting mechanism, aimed at dynamically managing class information for better adaptation to streaming data. GCIL is one of the hot topics in the field of computer vision, and this is considered one of the crucial ...
1712.00171
Wenbo Zhao
Wenbo Zhao, Yang Gao, Rita Singh
Speaker identification from the sound of the human breath
5 pages, 3 figures
null
null
null
cs.SD eess.AS stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper examines the speaker identification potential of breath sounds in continuous speech. Speech is largely produced during exhalation. In order to replenish air in the lungs, speakers must periodically inhale. When inhalation occurs in the midst of continuous speech, it is generally through the mouth. Intra-sp...
[ { "created": "Fri, 1 Dec 2017 03:16:23 GMT", "version": "v1" }, { "created": "Mon, 4 Dec 2017 17:30:42 GMT", "version": "v2" } ]
2017-12-05
[ [ "Zhao", "Wenbo", "" ], [ "Gao", "Yang", "" ], [ "Singh", "Rita", "" ] ]
This paper examines the speaker identification potential of breath sounds in continuous speech. Speech is largely produced during exhalation. In order to replenish air in the lungs, speakers must periodically inhale. When inhalation occurs in the midst of continuous speech, it is generally through the mouth. Intra-spee...
1206.2058
Ali Shadvar
Ali Shadvar
Dimension Reduction by Mutual Information Discriminant Analysis
13pages, 3 tables, International Journal of Artificial Intelligence & Applications
null
null
null
cs.CV cs.IT cs.LG math.IT
http://creativecommons.org/licenses/publicdomain/
In the past few decades, researchers have proposed many discriminant analysis (DA) algorithms for the study of high-dimensional data in a variety of problems. Most DA algorithms for feature extraction are based on transformations that simultaneously maximize the between-class scatter and minimize the withinclass scat...
[ { "created": "Sun, 10 Jun 2012 21:22:50 GMT", "version": "v1" } ]
2012-06-12
[ [ "Shadvar", "Ali", "" ] ]
In the past few decades, researchers have proposed many discriminant analysis (DA) algorithms for the study of high-dimensional data in a variety of problems. Most DA algorithms for feature extraction are based on transformations that simultaneously maximize the between-class scatter and minimize the withinclass scatte...
1801.06358
Zhiyong Zhou
Zhiyong Zhou and Jun Yu
Sparse recovery based on q-ratio constrained minimal singular values
null
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We study verifiable sufficient conditions and computable performance bounds for sparse recovery algorithms such as the Basis Pursuit, the Dantzig selector and the Lasso estimator, in terms of a newly defined family of quality measures for the measurement matrices. With high probability, the developed measures for sub...
[ { "created": "Fri, 19 Jan 2018 10:30:15 GMT", "version": "v1" } ]
2018-01-22
[ [ "Zhou", "Zhiyong", "" ], [ "Yu", "Jun", "" ] ]
We study verifiable sufficient conditions and computable performance bounds for sparse recovery algorithms such as the Basis Pursuit, the Dantzig selector and the Lasso estimator, in terms of a newly defined family of quality measures for the measurement matrices. With high probability, the developed measures for subga...
2402.05439
Joongkyu Lee
Joongkyu Lee, Seung Joon Park, Yunhao Tang, Min-hwan Oh
Learning Uncertainty-Aware Temporally-Extended Actions
Accepted in AAAI 2024 (Main Technical Track)
null
null
null
cs.LG stat.ML
http://creativecommons.org/licenses/by-nc-nd/4.0/
In reinforcement learning, temporal abstraction in the action space, exemplified by action repetition, is a technique to facilitate policy learning through extended actions. However, a primary limitation in previous studies of action repetition is its potential to degrade performance, particularly when sub-optimal ac...
[ { "created": "Thu, 8 Feb 2024 06:32:06 GMT", "version": "v1" } ]
2024-02-09
[ [ "Lee", "Joongkyu", "" ], [ "Park", "Seung Joon", "" ], [ "Tang", "Yunhao", "" ], [ "Oh", "Min-hwan", "" ] ]
In reinforcement learning, temporal abstraction in the action space, exemplified by action repetition, is a technique to facilitate policy learning through extended actions. However, a primary limitation in previous studies of action repetition is its potential to degrade performance, particularly when sub-optimal acti...
2010.08887
Kibok Lee
Kibok Lee, Yian Zhu, Kihyuk Sohn, Chun-Liang Li, Jinwoo Shin, Honglak Lee
i-Mix: A Domain-Agnostic Strategy for Contrastive Representation Learning
ICLR 2021
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Contrastive representation learning has shown to be effective to learn representations from unlabeled data. However, much progress has been made in vision domains relying on data augmentations carefully designed using domain knowledge. In this work, we propose i-Mix, a simple yet effective domain-agnostic regularizat...
[ { "created": "Sat, 17 Oct 2020 23:32:26 GMT", "version": "v1" }, { "created": "Thu, 18 Mar 2021 07:13:31 GMT", "version": "v2" } ]
2021-03-19
[ [ "Lee", "Kibok", "" ], [ "Zhu", "Yian", "" ], [ "Sohn", "Kihyuk", "" ], [ "Li", "Chun-Liang", "" ], [ "Shin", "Jinwoo", "" ], [ "Lee", "Honglak", "" ] ]
Contrastive representation learning has shown to be effective to learn representations from unlabeled data. However, much progress has been made in vision domains relying on data augmentations carefully designed using domain knowledge. In this work, we propose i-Mix, a simple yet effective domain-agnostic regularizatio...
0911.2322
EPTCS
Amin Coja-Oghlan
Random Constraint Satisfaction Problems
null
EPTCS 9, 2009, pp. 32-37
10.4204/EPTCS.9.4
null
cs.DM cs.CC cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Random instances of constraint satisfaction problems such as k-SAT provide challenging benchmarks. If there are m constraints over n variables there is typically a large range of densities r=m/n where solutions are known to exist with probability close to one due to non-constructive arguments. However, no algorithms ...
[ { "created": "Thu, 12 Nov 2009 08:42:42 GMT", "version": "v1" } ]
2009-11-13
[ [ "Coja-Oghlan", "Amin", "" ] ]
Random instances of constraint satisfaction problems such as k-SAT provide challenging benchmarks. If there are m constraints over n variables there is typically a large range of densities r=m/n where solutions are known to exist with probability close to one due to non-constructive arguments. However, no algorithms ar...
2401.07124
Farhad Kooban
Sara Shomal Zadeh, Sina Aalipour birgani, Meisam Khorshidi, Farhad Kooban
Concrete Surface Crack Detection with Convolutional-based Deep Learning Models
11 pages, 3 figures, Journal paper
International Journal of Novel Research in Civil Structural and Earth Sciences, Vol. 10, Issue 3, (2023) pp: (25-35)
10.5281/zenodo.10061654
null
cs.CV cs.LG eess.IV
http://creativecommons.org/licenses/by/4.0/
Effective crack detection is pivotal for the structural health monitoring and inspection of buildings. This task presents a formidable challenge to computer vision techniques due to the inherently subtle nature of cracks, which often exhibit low-level features that can be easily confounded with background textures, f...
[ { "created": "Sat, 13 Jan 2024 17:31:12 GMT", "version": "v1" } ]
2024-01-17
[ [ "Zadeh", "Sara Shomal", "" ], [ "birgani", "Sina Aalipour", "" ], [ "Khorshidi", "Meisam", "" ], [ "Kooban", "Farhad", "" ] ]
Effective crack detection is pivotal for the structural health monitoring and inspection of buildings. This task presents a formidable challenge to computer vision techniques due to the inherently subtle nature of cracks, which often exhibit low-level features that can be easily confounded with background textures, for...
1207.1187
Hardik Shah Mr
Hardik Shah, Andreas Raabe and Alois Knoll
Dynamic Priority Queue: An SDRAM Arbiter With Bounded Access Latencies for Tight WCET Calculation
null
null
null
null
cs.AR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This report introduces a shared resource arbitration scheme "DPQ - Dynamic Priority Queue" which provides bandwidth guarantees and low worst case latency to each master in an MPSoC. Being a non-trivial candidate for timing analysis, SDRAM has been chosen as a showcase, but the approach is valid for any shared resourc...
[ { "created": "Thu, 5 Jul 2012 08:20:02 GMT", "version": "v1" } ]
2015-03-20
[ [ "Shah", "Hardik", "" ], [ "Raabe", "Andreas", "" ], [ "Knoll", "Alois", "" ] ]
This report introduces a shared resource arbitration scheme "DPQ - Dynamic Priority Queue" which provides bandwidth guarantees and low worst case latency to each master in an MPSoC. Being a non-trivial candidate for timing analysis, SDRAM has been chosen as a showcase, but the approach is valid for any shared resource ...
2309.17170
Luuk van den Bent
Luuk van den Bent, Tom\'as Coleman, Robert Babuska
A Vision-Guided Robotic System for Grasping Harvested Tomato Trusses in Cluttered Environments
7 pages, 7 figures
null
null
null
cs.RO cs.AI cs.CV
http://creativecommons.org/licenses/by/4.0/
Currently, truss tomato weighing and packaging require significant manual work. The main obstacle to automation lies in the difficulty of developing a reliable robotic grasping system for already harvested trusses. We propose a method to grasp trusses that are stacked in a crate with considerable clutter, which is ho...
[ { "created": "Fri, 29 Sep 2023 12:07:08 GMT", "version": "v1" } ]
2023-10-02
[ [ "Bent", "Luuk van den", "" ], [ "Coleman", "Tomás", "" ], [ "Babuska", "Robert", "" ] ]
Currently, truss tomato weighing and packaging require significant manual work. The main obstacle to automation lies in the difficulty of developing a reliable robotic grasping system for already harvested trusses. We propose a method to grasp trusses that are stacked in a crate with considerable clutter, which is how ...
2206.10192
Leonardo Rossi
Leonardo Rossi, Marco Valenti, Sara Elisabetta Legler, Andrea Prati
LDD: A Dataset for Grape Diseases Object Detection and Instance Segmentation
null
International Conference on Image Analysis and Processing. Springer, Cham, 2022
10.1007/978-3-031-06430-2_32
null
cs.CV
http://creativecommons.org/licenses/by-sa/4.0/
The Instance Segmentation task, an extension of the well-known Object Detection task, is of great help in many areas, such as precision agriculture: being able to automatically identify plant organs and the possible diseases associated with them, allows to effectively scale and automate crop monitoring and its diseas...
[ { "created": "Tue, 21 Jun 2022 08:50:13 GMT", "version": "v1" } ]
2022-06-22
[ [ "Rossi", "Leonardo", "" ], [ "Valenti", "Marco", "" ], [ "Legler", "Sara Elisabetta", "" ], [ "Prati", "Andrea", "" ] ]
The Instance Segmentation task, an extension of the well-known Object Detection task, is of great help in many areas, such as precision agriculture: being able to automatically identify plant organs and the possible diseases associated with them, allows to effectively scale and automate crop monitoring and its diseases...
2012.07935
Alexandros Psomas
Aranyak Mehta, Uri Nadav, Alexandros Psomas, Aviad Rubinstein
Hitting the High Notes: Subset Selection for Maximizing Expected Order Statistics
null
null
null
null
cs.GT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We consider the fundamental problem of selecting $k$ out of $n$ random variables in a way that the expected highest or second-highest value is maximized. This question captures several applications where we have uncertainty about the quality of candidates (e.g. auction bids, search results) and have the capacity to e...
[ { "created": "Mon, 14 Dec 2020 20:53:39 GMT", "version": "v1" } ]
2020-12-16
[ [ "Mehta", "Aranyak", "" ], [ "Nadav", "Uri", "" ], [ "Psomas", "Alexandros", "" ], [ "Rubinstein", "Aviad", "" ] ]
We consider the fundamental problem of selecting $k$ out of $n$ random variables in a way that the expected highest or second-highest value is maximized. This question captures several applications where we have uncertainty about the quality of candidates (e.g. auction bids, search results) and have the capacity to exp...
2211.14077
Miguel P\'erez Msc
Miguel Angel P\'erez-Cuti\~no and Juan Sebasti\'an Valverde and Jos\'e Miguel D\'iaz-B\'a\~nez
Detecting broken Absorber Tubes in CSP plants using intelligent sampling and dual loss
null
null
null
null
cs.LG cs.AI
http://creativecommons.org/licenses/by-nc-sa/4.0/
Concentrated solar power (CSP) is one of the growing technologies that is leading the process of changing from fossil fuels to renewable energies. The sophistication and size of the systems require an increase in maintenance tasks to ensure reliability, availability, maintainability and safety. Currently, automatic f...
[ { "created": "Fri, 25 Nov 2022 12:53:52 GMT", "version": "v1" } ]
2022-11-28
[ [ "Pérez-Cutiño", "Miguel Angel", "" ], [ "Valverde", "Juan Sebastián", "" ], [ "Díaz-Báñez", "José Miguel", "" ] ]
Concentrated solar power (CSP) is one of the growing technologies that is leading the process of changing from fossil fuels to renewable energies. The sophistication and size of the systems require an increase in maintenance tasks to ensure reliability, availability, maintainability and safety. Currently, automatic fau...
2107.14178
Michael Yang
Xuewen Yang, Yingru Liu, Xin Wang
ReFormer: The Relational Transformer for Image Captioning
null
null
null
null
cs.CV
http://creativecommons.org/publicdomain/zero/1.0/
Image captioning is shown to be able to achieve a better performance by using scene graphs to represent the relations of objects in the image. The current captioning encoders generally use a Graph Convolutional Net (GCN) to represent the relation information and merge it with the object region features via concatenat...
[ { "created": "Thu, 29 Jul 2021 17:03:36 GMT", "version": "v1" }, { "created": "Thu, 14 Jul 2022 20:11:17 GMT", "version": "v2" } ]
2022-07-18
[ [ "Yang", "Xuewen", "" ], [ "Liu", "Yingru", "" ], [ "Wang", "Xin", "" ] ]
Image captioning is shown to be able to achieve a better performance by using scene graphs to represent the relations of objects in the image. The current captioning encoders generally use a Graph Convolutional Net (GCN) to represent the relation information and merge it with the object region features via concatenatio...
1907.05681
D\'avid Terj\'ek
D\'avid Terj\'ek
Adversarial Lipschitz Regularization
ICLR 2020
null
null
null
cs.LG cs.CV stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Generative adversarial networks (GANs) are one of the most popular approaches when it comes to training generative models, among which variants of Wasserstein GANs are considered superior to the standard GAN formulation in terms of learning stability and sample quality. However, Wasserstein GANs require the critic to...
[ { "created": "Fri, 12 Jul 2019 11:41:18 GMT", "version": "v1" }, { "created": "Thu, 2 Jan 2020 16:02:17 GMT", "version": "v2" }, { "created": "Fri, 3 Jan 2020 09:11:31 GMT", "version": "v3" } ]
2020-01-06
[ [ "Terjék", "Dávid", "" ] ]
Generative adversarial networks (GANs) are one of the most popular approaches when it comes to training generative models, among which variants of Wasserstein GANs are considered superior to the standard GAN formulation in terms of learning stability and sample quality. However, Wasserstein GANs require the critic to b...
1803.07097
Ryo Ashida
Ryo Ashida and Kotaro Nakagawa
$\tilde{O}(n^{1/3})$-Space Algorithm for the Grid Graph Reachability Problem
null
null
10.4230/LIPIcs.SoCG.2018.5
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The directed graph reachability problem takes as input an $n$-vertex directed graph $G=(V,E)$, and two distinguished vertices $s$ and $t$. The problem is to determine whether there exists a path from $s$ to $t$ in $G$. This is a canonical complete problem for class NL. Asano et al. proposed an $\tilde{O}(\sqrt{n})$ s...
[ { "created": "Mon, 19 Mar 2018 18:06:52 GMT", "version": "v1" }, { "created": "Thu, 7 Feb 2019 06:17:14 GMT", "version": "v2" }, { "created": "Fri, 20 Sep 2019 07:25:38 GMT", "version": "v3" } ]
2019-09-23
[ [ "Ashida", "Ryo", "" ], [ "Nakagawa", "Kotaro", "" ] ]
The directed graph reachability problem takes as input an $n$-vertex directed graph $G=(V,E)$, and two distinguished vertices $s$ and $t$. The problem is to determine whether there exists a path from $s$ to $t$ in $G$. This is a canonical complete problem for class NL. Asano et al. proposed an $\tilde{O}(\sqrt{n})$ spa...
2204.04338
Javier Andreu-Perez Dr
Christian Flores Vega, Jonathan Quevedo, Elmer Escand\'on, Mehrin Kiani, Weiping Ding, Javier Andreu-Perez
Fuzzy temporal convolutional neural networks in P300-based Brain-computer interface for smart home interaction
null
Applied Soft Computing 117 (2022) 108359
10.1016/j.asoc.2021.108359
null
cs.LG cs.AI cs.NE q-bio.NC
http://creativecommons.org/licenses/by-nc-nd/4.0/
The processing and classification of electroencephalographic signals (EEG) are increasingly performed using deep learning frameworks, such as convolutional neural networks (CNNs), to generate abstract features from brain data, automatically paving the way for remarkable classification prowess. However, EEG patterns e...
[ { "created": "Sat, 9 Apr 2022 00:35:35 GMT", "version": "v1" } ]
2022-04-12
[ [ "Vega", "Christian Flores", "" ], [ "Quevedo", "Jonathan", "" ], [ "Escandón", "Elmer", "" ], [ "Kiani", "Mehrin", "" ], [ "Ding", "Weiping", "" ], [ "Andreu-Perez", "Javier", "" ] ]
The processing and classification of electroencephalographic signals (EEG) are increasingly performed using deep learning frameworks, such as convolutional neural networks (CNNs), to generate abstract features from brain data, automatically paving the way for remarkable classification prowess. However, EEG patterns exh...
2404.15653
Sachin Mehta
Sachin Mehta and Maxwell Horton and Fartash Faghri and Mohammad Hossein Sekhavat and Mahyar Najibi and Mehrdad Farajtabar and Oncel Tuzel and Mohammad Rastegari
CatLIP: CLIP-level Visual Recognition Accuracy with 2.7x Faster Pre-training on Web-scale Image-Text Data
null
null
null
null
cs.CV cs.AI cs.CL cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Contrastive learning has emerged as a transformative method for learning effective visual representations through the alignment of image and text embeddings. However, pairwise similarity computation in contrastive loss between image and text pairs poses computational challenges. This paper presents a novel weakly sup...
[ { "created": "Wed, 24 Apr 2024 05:13:28 GMT", "version": "v1" } ]
2024-04-25
[ [ "Mehta", "Sachin", "" ], [ "Horton", "Maxwell", "" ], [ "Faghri", "Fartash", "" ], [ "Sekhavat", "Mohammad Hossein", "" ], [ "Najibi", "Mahyar", "" ], [ "Farajtabar", "Mehrdad", "" ], [ "Tuzel", "Oncel", ""...
Contrastive learning has emerged as a transformative method for learning effective visual representations through the alignment of image and text embeddings. However, pairwise similarity computation in contrastive loss between image and text pairs poses computational challenges. This paper presents a novel weakly super...
1701.07594
Du\v{s}an Nemec
Dusan Nemec, Ales Janota, Marian Hrubos, Vojtech Simak
Intelligent real-time MEMS sensor fusion and calibration
null
IEEE Sensors Journal, vol. 16, no. 19, pp. 7150-7160, Oct.1, 2016
10.1109/JSEN.2016.2597292
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper discusses an innovative adaptive heterogeneous fusion algorithm based on estimation of the mean square error of all variables used in real time processing. The algorithm is designed for a fusion between derivative and absolute sensors and is explained by the fusion of the 3-axial gyroscope, 3-axial acceler...
[ { "created": "Thu, 26 Jan 2017 07:09:21 GMT", "version": "v1" } ]
2017-01-27
[ [ "Nemec", "Dusan", "" ], [ "Janota", "Ales", "" ], [ "Hrubos", "Marian", "" ], [ "Simak", "Vojtech", "" ] ]
This paper discusses an innovative adaptive heterogeneous fusion algorithm based on estimation of the mean square error of all variables used in real time processing. The algorithm is designed for a fusion between derivative and absolute sensors and is explained by the fusion of the 3-axial gyroscope, 3-axial accelerom...
1110.0594
Tugcan Aktas
Tugcan Aktas, Ali Ozgur Yilmaz, Emre Aktas
Practical Wireless Network Coding and Decoding Methods for Multiple Unicast Transmissions
6 pages, 5 figures, Submitted to WCNC 2012, IEEE Wireless Communication and Networking Conference
null
10.1109/WCNC.2012.6214460
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We propose a simple yet effective wireless network coding and decoding technique. It utilizes spatial diversity through cooperation between nodes which carry out distributed encoding operations dictated by generator matrices of linear block codes. For this purpose, we make use of greedy codes over the binary field an...
[ { "created": "Tue, 4 Oct 2011 07:37:38 GMT", "version": "v1" } ]
2016-11-17
[ [ "Aktas", "Tugcan", "" ], [ "Yilmaz", "Ali Ozgur", "" ], [ "Aktas", "Emre", "" ] ]
We propose a simple yet effective wireless network coding and decoding technique. It utilizes spatial diversity through cooperation between nodes which carry out distributed encoding operations dictated by generator matrices of linear block codes. For this purpose, we make use of greedy codes over the binary field and ...
2209.07148
Gholamali Aminian
Gholamali Aminian, Armin Behnamnia, Roberto Vega, Laura Toni, Chengchun Shi, Hamid R. Rabiee, Omar Rivasplata, Miguel R. D. Rodrigues
Semi-supervised Batch Learning From Logged Data
46 pages,
null
null
null
cs.LG cs.AI cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Off-policy learning methods are intended to learn a policy from logged data, which includes context, action, and feedback (cost or reward) for each sample point. In this work, we build on the counterfactual risk minimization framework, which also assumes access to propensity scores. We propose learning methods for pr...
[ { "created": "Thu, 15 Sep 2022 08:58:28 GMT", "version": "v1" }, { "created": "Wed, 28 Sep 2022 09:46:14 GMT", "version": "v2" }, { "created": "Sun, 18 Feb 2024 15:26:01 GMT", "version": "v3" } ]
2024-02-20
[ [ "Aminian", "Gholamali", "" ], [ "Behnamnia", "Armin", "" ], [ "Vega", "Roberto", "" ], [ "Toni", "Laura", "" ], [ "Shi", "Chengchun", "" ], [ "Rabiee", "Hamid R.", "" ], [ "Rivasplata", "Omar", "" ], [ ...
Off-policy learning methods are intended to learn a policy from logged data, which includes context, action, and feedback (cost or reward) for each sample point. In this work, we build on the counterfactual risk minimization framework, which also assumes access to propensity scores. We propose learning methods for prob...
1612.02372
Jia Xue
Jia Xue, Hang Zhang, Kristin Dana, Ko Nishino
Differential Angular Imaging for Material Recognition
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Material recognition for real-world outdoor surfaces has become increasingly important for computer vision to support its operation "in the wild." Computational surface modeling that underlies material recognition has transitioned from reflectance modeling using in-lab controlled radiometric measurements to image-bas...
[ { "created": "Wed, 7 Dec 2016 18:59:19 GMT", "version": "v1" }, { "created": "Fri, 14 Jul 2017 00:43:10 GMT", "version": "v2" } ]
2017-07-17
[ [ "Xue", "Jia", "" ], [ "Zhang", "Hang", "" ], [ "Dana", "Kristin", "" ], [ "Nishino", "Ko", "" ] ]
Material recognition for real-world outdoor surfaces has become increasingly important for computer vision to support its operation "in the wild." Computational surface modeling that underlies material recognition has transitioned from reflectance modeling using in-lab controlled radiometric measurements to image-based...