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2004.13354
Jinwoo Ahn
Jinwoo Ahn, Seungjin Lee, Jinhoon Lee, Yungwoo Ko, Donghyun Min, Junghee Lee, Youngjae Kim
SGX-SSD: A Policy-based Versioning SSD with Intel SGX
7 pages, 4 figures
null
null
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper demonstrates that SSDs, which perform device-level versioning, can be exposed to data tampering attacks when the retention time of data is less than the malware's dwell time. To deal with that threat, we propose SGX-SSD, a SGX-based versioning SSD which selectively preserves file history based on the given...
[ { "created": "Tue, 28 Apr 2020 08:11:30 GMT", "version": "v1" }, { "created": "Wed, 29 Apr 2020 01:03:18 GMT", "version": "v2" } ]
2020-04-30
[ [ "Ahn", "Jinwoo", "" ], [ "Lee", "Seungjin", "" ], [ "Lee", "Jinhoon", "" ], [ "Ko", "Yungwoo", "" ], [ "Min", "Donghyun", "" ], [ "Lee", "Junghee", "" ], [ "Kim", "Youngjae", "" ] ]
This paper demonstrates that SSDs, which perform device-level versioning, can be exposed to data tampering attacks when the retention time of data is less than the malware's dwell time. To deal with that threat, we propose SGX-SSD, a SGX-based versioning SSD which selectively preserves file history based on the given p...
1804.06454
Marco Baldi
Mohammad H. Tadayon, Alireza Tasdighi, Massimo Battaglioni, Marco Baldi, Franco Chiaraluce
Efficient Search of Compact QC-LDPC and SC-LDPC Convolutional Codes with Large Girth
4 pages, 3 figures, 1 table, accepted for publication in IEEE Communications Letters
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We propose a low-complexity method to find quasi-cyclic low-density parity-check block codes with girth 10 or 12 and shorter length than those designed through classical approaches. The method is extended to time-invariant spatially coupled low-density parity-check convolutional codes, permitting to achieve small syn...
[ { "created": "Tue, 17 Apr 2018 19:47:42 GMT", "version": "v1" } ]
2018-04-19
[ [ "Tadayon", "Mohammad H.", "" ], [ "Tasdighi", "Alireza", "" ], [ "Battaglioni", "Massimo", "" ], [ "Baldi", "Marco", "" ], [ "Chiaraluce", "Franco", "" ] ]
We propose a low-complexity method to find quasi-cyclic low-density parity-check block codes with girth 10 or 12 and shorter length than those designed through classical approaches. The method is extended to time-invariant spatially coupled low-density parity-check convolutional codes, permitting to achieve small syndr...
1710.09876
Samin Aref
Samin Aref, Andrew J. Mason, Mark C. Wilson
Computing the Line Index of Balance Using Integer Programming Optimisation
Accepted author copy, 20 pages, 4 tables and 3 figures. This work is followed up in another study with more focus on Operations Research aspects of the topic that can be found in arXiv:1611.09030
null
null
null
cs.SI math.OC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
An important measure of signed graphs is the line index of balance which has several applications in many fields. However, this graph-theoretic measure was underused for decades because of the inherent complexity in its computation which is closely related to solving NP-hard graph optimisation problems like MAXCUT. W...
[ { "created": "Thu, 26 Oct 2017 19:09:57 GMT", "version": "v1" }, { "created": "Tue, 6 Feb 2018 00:34:19 GMT", "version": "v2" }, { "created": "Wed, 7 Feb 2018 05:19:46 GMT", "version": "v3" } ]
2018-02-08
[ [ "Aref", "Samin", "" ], [ "Mason", "Andrew J.", "" ], [ "Wilson", "Mark C.", "" ] ]
An important measure of signed graphs is the line index of balance which has several applications in many fields. However, this graph-theoretic measure was underused for decades because of the inherent complexity in its computation which is closely related to solving NP-hard graph optimisation problems like MAXCUT. We ...
1903.00951
Babak Alipour
Babak Alipour, Leonardo Tonetto, Roozbeh Ketabi, Aaron Yi Ding, J\"org Ott, Ahmed Helmy
Practical Prediction of Human Movements Across Device Types and Spatiotemporal Granularities
null
null
null
null
cs.NI
http://creativecommons.org/licenses/by/4.0/
Understanding and predicting mobility are essential for the design and evaluation of future mobile edge caching and networking. Consequently, research on prediction of human mobility has drawn significant attention in the last decade. Employing information-theoretic concepts and machine learning methods, earlier rese...
[ { "created": "Sun, 3 Mar 2019 17:46:27 GMT", "version": "v1" } ]
2019-03-05
[ [ "Alipour", "Babak", "" ], [ "Tonetto", "Leonardo", "" ], [ "Ketabi", "Roozbeh", "" ], [ "Ding", "Aaron Yi", "" ], [ "Ott", "Jörg", "" ], [ "Helmy", "Ahmed", "" ] ]
Understanding and predicting mobility are essential for the design and evaluation of future mobile edge caching and networking. Consequently, research on prediction of human mobility has drawn significant attention in the last decade. Employing information-theoretic concepts and machine learning methods, earlier resear...
2109.00895
Yushan Zhu
Yushan Zhu, Huaixiao Tou, Wen Zhang, Ganqiang Ye, Hui Chen, Ningyu Zhang and Huajun Chen
Knowledge Perceived Multi-modal Pretraining in E-commerce
Accepted to ACM MM 2021
null
10.1145/3474085.3475648
null
cs.CV cs.AI cs.CL
http://creativecommons.org/licenses/by/4.0/
In this paper, we address multi-modal pretraining of product data in the field of E-commerce. Current multi-modal pretraining methods proposed for image and text modalities lack robustness in the face of modality-missing and modality-noise, which are two pervasive problems of multi-modal product data in real E-commer...
[ { "created": "Fri, 20 Aug 2021 08:01:28 GMT", "version": "v1" } ]
2021-09-03
[ [ "Zhu", "Yushan", "" ], [ "Tou", "Huaixiao", "" ], [ "Zhang", "Wen", "" ], [ "Ye", "Ganqiang", "" ], [ "Chen", "Hui", "" ], [ "Zhang", "Ningyu", "" ], [ "Chen", "Huajun", "" ] ]
In this paper, we address multi-modal pretraining of product data in the field of E-commerce. Current multi-modal pretraining methods proposed for image and text modalities lack robustness in the face of modality-missing and modality-noise, which are two pervasive problems of multi-modal product data in real E-commerce...
1605.02041
David Guillermo Fajardo Ortiz
David Fajardo-Ortiz, Luis Duran, Laura Moreno, Hector Ochoa, Victor-M Castano
Mapping knowledge translation and innovation processes in Cancer Drug Development: the case of liposomal doxorubicin
null
Journal of Translational Medicine 2014, 12:227
10.1186/s12967-014-0227-9
null
cs.DL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We explored how the knowledge translation and innovation processes are structured when they result in innovations, as in the case of liposomal doxorubicin research. In order to map the processes, a literature network analysis was made through Cytoscape and semantic analysis was performed by GOPubmed which is based in...
[ { "created": "Tue, 12 Apr 2016 05:55:21 GMT", "version": "v1" } ]
2016-05-09
[ [ "Fajardo-Ortiz", "David", "" ], [ "Duran", "Luis", "" ], [ "Moreno", "Laura", "" ], [ "Ochoa", "Hector", "" ], [ "Castano", "Victor-M", "" ] ]
We explored how the knowledge translation and innovation processes are structured when they result in innovations, as in the case of liposomal doxorubicin research. In order to map the processes, a literature network analysis was made through Cytoscape and semantic analysis was performed by GOPubmed which is based in t...
2108.11887
Lei Lei
Jiaju Qi, Qihao Zhou, Lei Lei, Kan Zheng
Federated Reinforcement Learning: Techniques, Applications, and Open Challenges
null
Intelligence & Robotics. 2021; 1(1):18-57
10.20517/ir.2021.02
null
cs.LG cs.AI
http://creativecommons.org/licenses/by/4.0/
This paper presents a comprehensive survey of Federated Reinforcement Learning (FRL), an emerging and promising field in Reinforcement Learning (RL). Starting with a tutorial of Federated Learning (FL) and RL, we then focus on the introduction of FRL as a new method with great potential by leveraging the basic idea o...
[ { "created": "Thu, 26 Aug 2021 16:22:49 GMT", "version": "v1" }, { "created": "Sun, 24 Oct 2021 19:02:03 GMT", "version": "v2" } ]
2023-05-12
[ [ "Qi", "Jiaju", "" ], [ "Zhou", "Qihao", "" ], [ "Lei", "Lei", "" ], [ "Zheng", "Kan", "" ] ]
This paper presents a comprehensive survey of Federated Reinforcement Learning (FRL), an emerging and promising field in Reinforcement Learning (RL). Starting with a tutorial of Federated Learning (FL) and RL, we then focus on the introduction of FRL as a new method with great potential by leveraging the basic idea of ...
2303.05946
Kyle Hart
Kyle M. Hart (1 and 2), Brendan Englot (2), Ryan P. O'Shea (1), John D. Kelly (1), David Martinez (1) ((1) Naval Air Warfare Center Aircraft Division Lakehurst, (2) Stevens Institute of Technology)
Monocular Simultaneous Localization and Mapping using Ground Textures
7 pages, 9 figures. To appear at ICRA 2023, London, UK. Distribution Statement A: Approved for public release; distribution is unlimited, as submitted under NAVAIR Public Release Authorization 2022-0586. The views expressed here are those of the authors and do not reflect the official policy or position of the ...
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recent work has shown impressive localization performance using only images of ground textures taken with a downward facing monocular camera. This provides a reliable navigation method that is robust to feature sparse environments and challenging lighting conditions. However, these localization methods require an exi...
[ { "created": "Fri, 10 Mar 2023 14:27:31 GMT", "version": "v1" } ]
2023-03-13
[ [ "Hart", "Kyle M.", "", "1 and 2" ], [ "Englot", "Brendan", "" ], [ "O'Shea", "Ryan P.", "" ], [ "Kelly", "John D.", "" ], [ "Martinez", "David", "" ] ]
Recent work has shown impressive localization performance using only images of ground textures taken with a downward facing monocular camera. This provides a reliable navigation method that is robust to feature sparse environments and challenging lighting conditions. However, these localization methods require an exist...
1405.1129
Vikram Krishnamurthy
Vikram Krishnamurthy and Omid Namvar Gharehshiran and Maziyar Hamdi
Interactive Sensing and Decision Making in Social Networks
Foundations and Trends in Signal Processing, Now Publishers, 2014
null
10.1561/2000000048
null
cs.SI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The proliferation of social media such as real time microblogging and online reputation systems facilitate real time sensing of social patterns and behavior. In the last decade, sensing and decision making in social networks have witnessed significant progress in the electrical engineering, computer science, economic...
[ { "created": "Tue, 6 May 2014 02:21:24 GMT", "version": "v1" } ]
2014-05-07
[ [ "Krishnamurthy", "Vikram", "" ], [ "Gharehshiran", "Omid Namvar", "" ], [ "Hamdi", "Maziyar", "" ] ]
The proliferation of social media such as real time microblogging and online reputation systems facilitate real time sensing of social patterns and behavior. In the last decade, sensing and decision making in social networks have witnessed significant progress in the electrical engineering, computer science, economics,...
2404.09265
Mindaugas Budzys
Tanveer Khan, Mindaugas Budzys, Antonis Michalas
Make Split, not Hijack: Preventing Feature-Space Hijacking Attacks in Split Learning
Accepted In Proceedings of the 29th ACM Symposium on Access Control Models and Technologies (SACMAT '24)
null
null
null
cs.CR cs.AI
http://creativecommons.org/licenses/by/4.0/
The popularity of Machine Learning (ML) makes the privacy of sensitive data more imperative than ever. Collaborative learning techniques like Split Learning (SL) aim to protect client data while enhancing ML processes. Though promising, SL has been proved to be vulnerable to a plethora of attacks, thus raising concer...
[ { "created": "Sun, 14 Apr 2024 14:14:31 GMT", "version": "v1" } ]
2024-04-16
[ [ "Khan", "Tanveer", "" ], [ "Budzys", "Mindaugas", "" ], [ "Michalas", "Antonis", "" ] ]
The popularity of Machine Learning (ML) makes the privacy of sensitive data more imperative than ever. Collaborative learning techniques like Split Learning (SL) aim to protect client data while enhancing ML processes. Though promising, SL has been proved to be vulnerable to a plethora of attacks, thus raising concerns...
2208.14925
Tim Schreiter
Tim Schreiter, Tiago Rodrigues de Almeida, Yufei Zhu, Eduardo Gutierrez Maestro, Lucas Morillo-Mendez, Andrey Rudenko, Tomasz P. Kucner, Oscar Martinez Mozos, Martin Magnusson, Luigi Palmieri, Kai O. Arras, Achim J. Lilienthal
The Magni Human Motion Dataset: Accurate, Complex, Multi-Modal, Natural, Semantically-Rich and Contextualized
in SIRRW Workshop held in conjunction with 31st IEEE International Conference on Robot & Human Interactive Communication, 29/08 - 02/09 2022, Naples (Italy)
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Rapid development of social robots stimulates active research in human motion modeling, interpretation and prediction, proactive collision avoidance, human-robot interaction and co-habitation in shared spaces. Modern approaches to this end require high quality datasets for training and evaluation. However, the majori...
[ { "created": "Wed, 31 Aug 2022 15:37:45 GMT", "version": "v1" } ]
2022-09-01
[ [ "Schreiter", "Tim", "" ], [ "de Almeida", "Tiago Rodrigues", "" ], [ "Zhu", "Yufei", "" ], [ "Maestro", "Eduardo Gutierrez", "" ], [ "Morillo-Mendez", "Lucas", "" ], [ "Rudenko", "Andrey", "" ], [ "Kucner", "To...
Rapid development of social robots stimulates active research in human motion modeling, interpretation and prediction, proactive collision avoidance, human-robot interaction and co-habitation in shared spaces. Modern approaches to this end require high quality datasets for training and evaluation. However, the majority...
2306.08935
Ritu Yadav
Ritu Yadav, Andrea Nascetti, Yifang Ban
Context-Aware Change Detection With Semi-Supervised Learning
Paper Accepted in IGARSS 2023
null
null
null
cs.CV cs.AI cs.LG eess.IV
http://creativecommons.org/licenses/by/4.0/
Change detection using earth observation data plays a vital role in quantifying the impact of disasters in affected areas. While data sources like Sentinel-2 provide rich optical information, they are often hindered by cloud cover, limiting their usage in disaster scenarios. However, leveraging pre-disaster optical d...
[ { "created": "Thu, 15 Jun 2023 08:17:49 GMT", "version": "v1" } ]
2023-06-16
[ [ "Yadav", "Ritu", "" ], [ "Nascetti", "Andrea", "" ], [ "Ban", "Yifang", "" ] ]
Change detection using earth observation data plays a vital role in quantifying the impact of disasters in affected areas. While data sources like Sentinel-2 provide rich optical information, they are often hindered by cloud cover, limiting their usage in disaster scenarios. However, leveraging pre-disaster optical dat...
2001.10494
Feiyang Cai
Feiyang Cai and Xenofon Koutsoukos
Real-time Out-of-distribution Detection in Learning-Enabled Cyber-Physical Systems
Accepted by 11th International Conference on Cyber-Physical Systems (ICCPS2020)
null
null
null
cs.LG cs.SY eess.SY stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Cyber-physical systems (CPS) greatly benefit by using machine learning components that can handle the uncertainty and variability of the real-world. Typical components such as deep neural networks, however, introduce new types of hazards that may impact system safety. The system behavior depends on data that are avai...
[ { "created": "Tue, 28 Jan 2020 17:51:07 GMT", "version": "v1" } ]
2020-01-29
[ [ "Cai", "Feiyang", "" ], [ "Koutsoukos", "Xenofon", "" ] ]
Cyber-physical systems (CPS) greatly benefit by using machine learning components that can handle the uncertainty and variability of the real-world. Typical components such as deep neural networks, however, introduce new types of hazards that may impact system safety. The system behavior depends on data that are availa...
2212.07811
Mike Thelwall Prof
Mike Thelwall, Kayvan Kousha, Mahshid Abdoli, Emma Stuart, Meiko Makita, Paul Wilson, Jonathan Levitt
Do altmetric scores reflect article quality? Evidence from the UK Research Excellence Framework 2021
null
Journal of the Association for Information Science and Technology, 74(5), 582-593 (2023)
10.1108/10.1002/asi.24751
null
cs.DL
http://creativecommons.org/licenses/by/4.0/
Altmetrics are web-based quantitative impact or attention indicators for academic articles that have been proposed to supplement citation counts. This article reports the first assessment of the extent to which mature altmetrics from Altmetric.com and Mendeley associate with journal article quality. It exploits exper...
[ { "created": "Sun, 11 Dec 2022 05:40:35 GMT", "version": "v1" } ]
2023-08-01
[ [ "Thelwall", "Mike", "" ], [ "Kousha", "Kayvan", "" ], [ "Abdoli", "Mahshid", "" ], [ "Stuart", "Emma", "" ], [ "Makita", "Meiko", "" ], [ "Wilson", "Paul", "" ], [ "Levitt", "Jonathan", "" ] ]
Altmetrics are web-based quantitative impact or attention indicators for academic articles that have been proposed to supplement citation counts. This article reports the first assessment of the extent to which mature altmetrics from Altmetric.com and Mendeley associate with journal article quality. It exploits expert ...
1710.11213
Sahil Singla
Soheil Ehsani, MohammadTaghi Hajiaghayi, Thomas Kesselheim, and Sahil Singla
Prophet Secretary for Combinatorial Auctions and Matroids
Preliminary version appeared in SODA 2018. This version improves the writeup on Fixed-Threshold algorithms
null
null
null
cs.DS cs.GT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The secretary and the prophet inequality problems are central to the field of Stopping Theory. Recently, there has been a lot of work in generalizing these models to multiple items because of their applications in mechanism design. The most important of these generalizations are to matroids and to combinatorial aucti...
[ { "created": "Mon, 30 Oct 2017 19:41:38 GMT", "version": "v1" }, { "created": "Sat, 17 Mar 2018 17:13:41 GMT", "version": "v2" } ]
2018-03-20
[ [ "Ehsani", "Soheil", "" ], [ "Hajiaghayi", "MohammadTaghi", "" ], [ "Kesselheim", "Thomas", "" ], [ "Singla", "Sahil", "" ] ]
The secretary and the prophet inequality problems are central to the field of Stopping Theory. Recently, there has been a lot of work in generalizing these models to multiple items because of their applications in mechanism design. The most important of these generalizations are to matroids and to combinatorial auction...
2304.02841
Zhijie Deng
Zhijie Deng and Yucen Luo
Learning Neural Eigenfunctions for Unsupervised Semantic Segmentation
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Unsupervised semantic segmentation is a long-standing challenge in computer vision with great significance. Spectral clustering is a theoretically grounded solution to it where the spectral embeddings for pixels are computed to construct distinct clusters. Despite recent progress in enhancing spectral clustering with...
[ { "created": "Thu, 6 Apr 2023 03:14:15 GMT", "version": "v1" } ]
2023-04-07
[ [ "Deng", "Zhijie", "" ], [ "Luo", "Yucen", "" ] ]
Unsupervised semantic segmentation is a long-standing challenge in computer vision with great significance. Spectral clustering is a theoretically grounded solution to it where the spectral embeddings for pixels are computed to construct distinct clusters. Despite recent progress in enhancing spectral clustering with p...
2108.06812
Nikolai Karpov
Nikolai Karpov, Qin Zhang
Batched Thompson Sampling for Multi-Armed Bandits
9 pages
null
null
null
cs.LG
http://creativecommons.org/licenses/by/4.0/
We study Thompson Sampling algorithms for stochastic multi-armed bandits in the batched setting, in which we want to minimize the regret over a sequence of arm pulls using a small number of policy changes (or, batches). We propose two algorithms and demonstrate their effectiveness by experiments on both synthetic and...
[ { "created": "Sun, 15 Aug 2021 20:47:46 GMT", "version": "v1" } ]
2021-08-17
[ [ "Karpov", "Nikolai", "" ], [ "Zhang", "Qin", "" ] ]
We study Thompson Sampling algorithms for stochastic multi-armed bandits in the batched setting, in which we want to minimize the regret over a sequence of arm pulls using a small number of policy changes (or, batches). We propose two algorithms and demonstrate their effectiveness by experiments on both synthetic and r...
2104.13456
Adrian {\L}a\'ncucki
Pawe{\l} Rychlikowski, Bart{\l}omiej Najdecki, Adrian {\L}a\'ncucki, Adam Kaczmarek
Named Entity Recognition and Linking Augmented with Large-Scale Structured Data
null
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper we describe our submissions to the 2nd and 3rd SlavNER Shared Tasks held at BSNLP 2019 and BSNLP 2021, respectively. The tasks focused on the analysis of Named Entities in multilingual Web documents in Slavic languages with rich inflection. Our solution takes advantage of large collections of both unstr...
[ { "created": "Tue, 27 Apr 2021 20:10:18 GMT", "version": "v1" } ]
2021-04-29
[ [ "Rychlikowski", "Paweł", "" ], [ "Najdecki", "Bartłomiej", "" ], [ "Łańcucki", "Adrian", "" ], [ "Kaczmarek", "Adam", "" ] ]
In this paper we describe our submissions to the 2nd and 3rd SlavNER Shared Tasks held at BSNLP 2019 and BSNLP 2021, respectively. The tasks focused on the analysis of Named Entities in multilingual Web documents in Slavic languages with rich inflection. Our solution takes advantage of large collections of both unstruc...
2205.06910
Kanishka Misra
Kanishka Misra, Julia Taylor Rayz, Allyson Ettinger
A Property Induction Framework for Neural Language Models
CogSci 2022 camera ready version, with hyperref-compatible citations. Code and Supplemental Material can be found in https://github.com/kanishkamisra/lm-induction
null
null
null
cs.CL
http://creativecommons.org/licenses/by-nc-sa/4.0/
To what extent can experience from language contribute to our conceptual knowledge? Computational explorations of this question have shed light on the ability of powerful neural language models (LMs) -- informed solely through text input -- to encode and elicit information about concepts and properties. To extend thi...
[ { "created": "Fri, 13 May 2022 22:05:49 GMT", "version": "v1" } ]
2022-05-17
[ [ "Misra", "Kanishka", "" ], [ "Rayz", "Julia Taylor", "" ], [ "Ettinger", "Allyson", "" ] ]
To what extent can experience from language contribute to our conceptual knowledge? Computational explorations of this question have shed light on the ability of powerful neural language models (LMs) -- informed solely through text input -- to encode and elicit information about concepts and properties. To extend this ...
0904.0352
Rami Puzis
Shlomi Dolev, Yuval Elovici, Rami Puzis, Polina Zilberman
Incremental Deployment of Network Monitors Based on Group Betweenness Centrality
null
Information Processing Letters, 109(20), 1172-1176 (2009)
10.1016/j.ipl.2009.07.019
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In many applications we are required to increase the deployment of a distributed monitoring system on an evolving network. In this paper we present a new method for finding candidate locations for additional deployment in the network. This method is based on the Group Betweenness Centrality (GBC) measure that is used...
[ { "created": "Thu, 2 Apr 2009 09:32:51 GMT", "version": "v1" }, { "created": "Sun, 12 Jul 2009 10:01:36 GMT", "version": "v2" }, { "created": "Fri, 2 Oct 2020 13:32:31 GMT", "version": "v3" } ]
2020-10-05
[ [ "Dolev", "Shlomi", "" ], [ "Elovici", "Yuval", "" ], [ "Puzis", "Rami", "" ], [ "Zilberman", "Polina", "" ] ]
In many applications we are required to increase the deployment of a distributed monitoring system on an evolving network. In this paper we present a new method for finding candidate locations for additional deployment in the network. This method is based on the Group Betweenness Centrality (GBC) measure that is used t...
2306.02500
Taylor Webb
Taylor W. Webb, Shanka Subhra Mondal, Jonathan D. Cohen
Systematic Visual Reasoning through Object-Centric Relational Abstraction
null
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Human visual reasoning is characterized by an ability to identify abstract patterns from only a small number of examples, and to systematically generalize those patterns to novel inputs. This capacity depends in large part on our ability to represent complex visual inputs in terms of both objects and relations. Recen...
[ { "created": "Sun, 4 Jun 2023 22:47:17 GMT", "version": "v1" }, { "created": "Fri, 10 Nov 2023 22:22:44 GMT", "version": "v2" } ]
2023-11-14
[ [ "Webb", "Taylor W.", "" ], [ "Mondal", "Shanka Subhra", "" ], [ "Cohen", "Jonathan D.", "" ] ]
Human visual reasoning is characterized by an ability to identify abstract patterns from only a small number of examples, and to systematically generalize those patterns to novel inputs. This capacity depends in large part on our ability to represent complex visual inputs in terms of both objects and relations. Recent ...
1909.04954
Philipp Mayr
Guillaume Cabanac, Ingo Frommholz, Philipp Mayr
Report on the 8th International Workshop on Bibliometric-enhanced Information Retrieval (BIR 2019)
8 pages, report to appear in ACM SIGIR Forum
null
null
null
cs.IR cs.DL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The Bibliometric-enhanced Information Retrieval workshop series (BIR) at ECIR tackled issues related to academic search, at the crossroads between Information Retrieval and Bibliometrics. BIR is a hot topic investigated by both academia (e.g., ArnetMiner, CiteSeerx, DocEar) and the industry (e.g., Google Scholar, Mic...
[ { "created": "Wed, 11 Sep 2019 10:07:59 GMT", "version": "v1" } ]
2019-09-12
[ [ "Cabanac", "Guillaume", "" ], [ "Frommholz", "Ingo", "" ], [ "Mayr", "Philipp", "" ] ]
The Bibliometric-enhanced Information Retrieval workshop series (BIR) at ECIR tackled issues related to academic search, at the crossroads between Information Retrieval and Bibliometrics. BIR is a hot topic investigated by both academia (e.g., ArnetMiner, CiteSeerx, DocEar) and the industry (e.g., Google Scholar, Micro...
2204.02004
Chaim Baskin
Tal Rozen, Moshe Kimhi, Brian Chmiel, Avi Mendelson, Chaim Baskin
Bimodal Distributed Binarized Neural Networks
null
null
null
null
cs.LG cs.CV
http://creativecommons.org/licenses/by-nc-sa/4.0/
Binary Neural Networks (BNNs) are an extremely promising method to reduce deep neural networks' complexity and power consumption massively. Binarization techniques, however, suffer from ineligible performance degradation compared to their full-precision counterparts. Prior work mainly focused on strategies for sign...
[ { "created": "Tue, 5 Apr 2022 06:07:05 GMT", "version": "v1" } ]
2022-04-06
[ [ "Rozen", "Tal", "" ], [ "Kimhi", "Moshe", "" ], [ "Chmiel", "Brian", "" ], [ "Mendelson", "Avi", "" ], [ "Baskin", "Chaim", "" ] ]
Binary Neural Networks (BNNs) are an extremely promising method to reduce deep neural networks' complexity and power consumption massively. Binarization techniques, however, suffer from ineligible performance degradation compared to their full-precision counterparts. Prior work mainly focused on strategies for sign fun...
2404.12703
Marius Kurz
Daniel Kempf, Marius Kurz, Marcel Blind, Patrick Kopper, Philipp Offenh\"auser, Anna Schwarz, Spencer Starr, Jens Keim, Andrea Beck
GAL{\AE}XI: Solving complex compressible flows with high-order discontinuous Galerkin methods on accelerator-based systems
19 pages, 12 figures, 3 tables. Code available at: https://github.com/flexi-framework/galaexi
null
null
null
cs.MS cs.CE
http://creativecommons.org/licenses/by-nc-nd/4.0/
This work presents GAL{\AE}XI as a novel, energy-efficient flow solver for the simulation of compressible flows on unstructured meshes leveraging the parallel computing power of modern Graphics Processing Units (GPUs). GAL{\AE}XI implements the high-order Discontinuous Galerkin Spectral Element Method (DGSEM) using s...
[ { "created": "Fri, 19 Apr 2024 08:21:05 GMT", "version": "v1" } ]
2024-04-22
[ [ "Kempf", "Daniel", "" ], [ "Kurz", "Marius", "" ], [ "Blind", "Marcel", "" ], [ "Kopper", "Patrick", "" ], [ "Offenhäuser", "Philipp", "" ], [ "Schwarz", "Anna", "" ], [ "Starr", "Spencer", "" ], [ ...
This work presents GAL{\AE}XI as a novel, energy-efficient flow solver for the simulation of compressible flows on unstructured meshes leveraging the parallel computing power of modern Graphics Processing Units (GPUs). GAL{\AE}XI implements the high-order Discontinuous Galerkin Spectral Element Method (DGSEM) using sho...
1007.2449
Kamran Karimi
Kamran Karimi
A Brief Introduction to Temporality and Causality
null
null
null
null
cs.LG cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Causality is a non-obvious concept that is often considered to be related to temporality. In this paper we present a number of past and present approaches to the definition of temporality and causality from philosophical, physical, and computational points of view. We note that time is an important ingredient in many...
[ { "created": "Wed, 14 Jul 2010 22:41:30 GMT", "version": "v1" } ]
2010-07-16
[ [ "Karimi", "Kamran", "" ] ]
Causality is a non-obvious concept that is often considered to be related to temporality. In this paper we present a number of past and present approaches to the definition of temporality and causality from philosophical, physical, and computational points of view. We note that time is an important ingredient in many r...
2403.20195
Victor Silva Dos Santos
Victor Silva dos Santos, Erwan Gloaguen, Shiva Tirdad
Enhancing Lithological Mapping with Spatially Constrained Bayesian Network (SCB-Net): An Approach for Field Data-Constrained Predictions with Uncertainty Evaluation
17 pages, 3559 words, 14 figures
null
null
null
cs.CV cs.LG eess.IV
http://creativecommons.org/licenses/by/4.0/
Geological maps are an extremely valuable source of information for the Earth sciences. They provide insights into mineral exploration, vulnerability to natural hazards, and many other applications. These maps are created using numerical or conceptual models that use geological observations to extrapolate data. Geost...
[ { "created": "Fri, 29 Mar 2024 14:17:30 GMT", "version": "v1" } ]
2024-04-01
[ [ "Santos", "Victor Silva dos", "" ], [ "Gloaguen", "Erwan", "" ], [ "Tirdad", "Shiva", "" ] ]
Geological maps are an extremely valuable source of information for the Earth sciences. They provide insights into mineral exploration, vulnerability to natural hazards, and many other applications. These maps are created using numerical or conceptual models that use geological observations to extrapolate data. Geostat...
2006.03622
Saman Motamed
Saman Motamed and Patrik Rogalla and Farzad Khalvati
Data Augmentation using Generative Adversarial Networks (GANs) for GAN-based Detection of Pneumonia and COVID-19 in Chest X-ray Images
null
null
null
null
cs.CV cs.LG eess.IV q-bio.QM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Successful training of convolutional neural networks (CNNs) requires a substantial amount of data. With small datasets networks generalize poorly. Data Augmentation techniques improve the generalizability of neural networks by using existing training data more effectively. Standard data augmentation methods, however,...
[ { "created": "Fri, 5 Jun 2020 18:30:20 GMT", "version": "v1" }, { "created": "Tue, 12 Jan 2021 20:27:04 GMT", "version": "v2" } ]
2021-01-14
[ [ "Motamed", "Saman", "" ], [ "Rogalla", "Patrik", "" ], [ "Khalvati", "Farzad", "" ] ]
Successful training of convolutional neural networks (CNNs) requires a substantial amount of data. With small datasets networks generalize poorly. Data Augmentation techniques improve the generalizability of neural networks by using existing training data more effectively. Standard data augmentation methods, however, p...
2308.02950
Louis Vervoort
Louis Vervoort, Vitaliy Mizyakov, Anastasia Ugleva
A criterion for Artificial General Intelligence: hypothetic-deductive reasoning, tested on ChatGPT
null
null
null
null
cs.AI
http://creativecommons.org/licenses/by/4.0/
We argue that a key reasoning skill that any advanced AI, say GPT-4, should master in order to qualify as 'thinking machine', or AGI, is hypothetic-deductive reasoning. Problem-solving or question-answering can quite generally be construed as involving two steps: hypothesizing that a certain set of hypotheses T appli...
[ { "created": "Sat, 5 Aug 2023 20:33:13 GMT", "version": "v1" } ]
2023-08-08
[ [ "Vervoort", "Louis", "" ], [ "Mizyakov", "Vitaliy", "" ], [ "Ugleva", "Anastasia", "" ] ]
We argue that a key reasoning skill that any advanced AI, say GPT-4, should master in order to qualify as 'thinking machine', or AGI, is hypothetic-deductive reasoning. Problem-solving or question-answering can quite generally be construed as involving two steps: hypothesizing that a certain set of hypotheses T applies...
1812.10550
Huy-Hieu Pham
Huy-Hieu Pham and Louahdi Khoudour and Alain Crouzil and Pablo Zegers and Sergio A. Velastin
Learning to Recognize 3D Human Action from A New Skeleton-based Representation Using Deep Convolutional Neural Networks
This paper is a preprint of a paper published to IET Computer Vision. The copy of the record will be available at the IET Digital Library
null
10.1049/iet-cvi.2018.5014
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recognizing human actions in untrimmed videos is an important challenging task. An effective 3D motion representation and a powerful learning model are two key factors influencing recognition performance. In this paper we introduce a new skeleton-based representation for 3D action recognition in videos. The key idea ...
[ { "created": "Wed, 26 Dec 2018 21:47:08 GMT", "version": "v1" } ]
2018-12-31
[ [ "Pham", "Huy-Hieu", "" ], [ "Khoudour", "Louahdi", "" ], [ "Crouzil", "Alain", "" ], [ "Zegers", "Pablo", "" ], [ "Velastin", "Sergio A.", "" ] ]
Recognizing human actions in untrimmed videos is an important challenging task. An effective 3D motion representation and a powerful learning model are two key factors influencing recognition performance. In this paper we introduce a new skeleton-based representation for 3D action recognition in videos. The key idea of...
1602.08456
Masaki Ogura Dr.
Masaki Ogura and Victor M. Preciado
Epidemic Processes over Adaptive State-Dependent Networks
null
Phys. Rev. E 93, 062316 (2016)
10.1103/PhysRevE.93.062316
null
cs.SI math.PR physics.soc-ph q-bio.PE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we study the dynamics of epidemic processes taking place in adaptive networks of arbitrary topology. We focus our study on the adaptive susceptible-infected-susceptible (ASIS) model, where healthy individuals are allowed to temporarily cut edges connecting them to infected nodes in order to prevent the...
[ { "created": "Fri, 26 Feb 2016 19:56:41 GMT", "version": "v1" }, { "created": "Thu, 9 Jun 2016 17:30:07 GMT", "version": "v2" } ]
2016-06-29
[ [ "Ogura", "Masaki", "" ], [ "Preciado", "Victor M.", "" ] ]
In this paper, we study the dynamics of epidemic processes taking place in adaptive networks of arbitrary topology. We focus our study on the adaptive susceptible-infected-susceptible (ASIS) model, where healthy individuals are allowed to temporarily cut edges connecting them to infected nodes in order to prevent the s...
1802.08984
Kalev Alpernas
Kalev Alpernas (Tel Aviv University), Cormac Flanagan (UC Santa Cruz), Sadjad Fouladi (Stanford University), Leonid Ryzhyk (VMware Research), Mooly Sagiv (Tel Aviv University), Thomas Schmitz (UC Santa Cruz) and Keith Winstein (Stanford University)
Secure Serverless Computing Using Dynamic Information Flow Control
null
null
null
null
cs.PL cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The rise of serverless computing provides an opportunity to rethink cloud security. We present an approach for securing serverless systems using a novel form of dynamic information flow control (IFC). We show that in serverless applications, the termination channel found in most existing IFC systems can be arbitrar...
[ { "created": "Sun, 25 Feb 2018 10:36:56 GMT", "version": "v1" } ]
2018-02-27
[ [ "Alpernas", "Kalev", "", "Tel Aviv University" ], [ "Flanagan", "Cormac", "", "UC Santa Cruz" ], [ "Fouladi", "Sadjad", "", "Stanford University" ], [ "Ryzhyk", "Leonid", "", "VMware Research" ], [ "Sagiv", "Mooly", "", ...
The rise of serverless computing provides an opportunity to rethink cloud security. We present an approach for securing serverless systems using a novel form of dynamic information flow control (IFC). We show that in serverless applications, the termination channel found in most existing IFC systems can be arbitrarily ...
0906.5233
Toby Walsh
George Katsirelos, Sebastian Maneth, Nina Narodytska, Toby Walsh
Restricted Global Grammar Constraints
Proceedings of the 15th International Conference on Principles and Practice of Constraint Programming, Lisbon, Portugal. September 2009
null
null
null
cs.AI cs.FL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We investigate the global GRAMMAR constraint over restricted classes of context free grammars like deterministic and unambiguous context-free grammars. We show that detecting disentailment for the GRAMMAR constraint in these cases is as hard as parsing an unrestricted context free grammar.We also consider the class o...
[ { "created": "Mon, 29 Jun 2009 09:23:39 GMT", "version": "v1" } ]
2009-06-30
[ [ "Katsirelos", "George", "" ], [ "Maneth", "Sebastian", "" ], [ "Narodytska", "Nina", "" ], [ "Walsh", "Toby", "" ] ]
We investigate the global GRAMMAR constraint over restricted classes of context free grammars like deterministic and unambiguous context-free grammars. We show that detecting disentailment for the GRAMMAR constraint in these cases is as hard as parsing an unrestricted context free grammar.We also consider the class of ...
1006.5188
Nicola Di Mauro
Nicola Di Mauro and Teresa M.A. Basile and Stefano Ferilli and Floriana Esposito
Feature Construction for Relational Sequence Learning
15 pages
null
null
null
cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We tackle the problem of multi-class relational sequence learning using relevant patterns discovered from a set of labelled sequences. To deal with this problem, firstly each relational sequence is mapped into a feature vector using the result of a feature construction method. Since, the efficacy of sequence learning...
[ { "created": "Sun, 27 Jun 2010 08:56:11 GMT", "version": "v1" } ]
2010-06-29
[ [ "Di Mauro", "Nicola", "" ], [ "Basile", "Teresa M. A.", "" ], [ "Ferilli", "Stefano", "" ], [ "Esposito", "Floriana", "" ] ]
We tackle the problem of multi-class relational sequence learning using relevant patterns discovered from a set of labelled sequences. To deal with this problem, firstly each relational sequence is mapped into a feature vector using the result of a feature construction method. Since, the efficacy of sequence learning a...
1905.10077
Lixin Su
Lixin Su, Jiafeng Guo, Yixing Fan, Yanyan Lan, and Xueqi Cheng
Controlling Risk of Web Question Answering
42nd International ACM SIGIR Conference on Research and Development in Information Retrieval
null
10.1145/3331184.3331261
null
cs.IR cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Web question answering (QA) has become an indispensable component in modern search systems, which can significantly improve users' search experience by providing a direct answer to users' information need. This could be achieved by applying machine reading comprehension (MRC) models over the retrieved passages to ext...
[ { "created": "Fri, 24 May 2019 07:55:42 GMT", "version": "v1" }, { "created": "Mon, 27 May 2019 02:24:32 GMT", "version": "v2" }, { "created": "Thu, 11 Jul 2019 05:10:47 GMT", "version": "v3" } ]
2019-07-12
[ [ "Su", "Lixin", "" ], [ "Guo", "Jiafeng", "" ], [ "Fan", "Yixing", "" ], [ "Lan", "Yanyan", "" ], [ "Cheng", "Xueqi", "" ] ]
Web question answering (QA) has become an indispensable component in modern search systems, which can significantly improve users' search experience by providing a direct answer to users' information need. This could be achieved by applying machine reading comprehension (MRC) models over the retrieved passages to extra...
2209.07220
Hyung-Il Kim
Hyung-Il Kim, Kimin Yun, Yong Man Ro
Face Shape-Guided Deep Feature Alignment for Face Recognition Robust to Face Misalignment
14 pages, 9 figures
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
For the past decades, face recognition (FR) has been actively studied in computer vision and pattern recognition society. Recently, due to the advances in deep learning, the FR technology shows high performance for most of the benchmark datasets. However, when the FR algorithm is applied to a real-world scenario, the...
[ { "created": "Thu, 15 Sep 2022 11:23:51 GMT", "version": "v1" } ]
2022-09-16
[ [ "Kim", "Hyung-Il", "" ], [ "Yun", "Kimin", "" ], [ "Ro", "Yong Man", "" ] ]
For the past decades, face recognition (FR) has been actively studied in computer vision and pattern recognition society. Recently, due to the advances in deep learning, the FR technology shows high performance for most of the benchmark datasets. However, when the FR algorithm is applied to a real-world scenario, the p...
2302.10441
Zhuohang Li
Zhuohang Li, Jiaxin Zhang, Jian Liu
Speech Privacy Leakage from Shared Gradients in Distributed Learning
null
null
null
null
cs.LG cs.CR
http://creativecommons.org/licenses/by/4.0/
Distributed machine learning paradigms, such as federated learning, have been recently adopted in many privacy-critical applications for speech analysis. However, such frameworks are vulnerable to privacy leakage attacks from shared gradients. Despite extensive efforts in the image domain, the exploration of speech p...
[ { "created": "Tue, 21 Feb 2023 04:48:29 GMT", "version": "v1" } ]
2023-02-22
[ [ "Li", "Zhuohang", "" ], [ "Zhang", "Jiaxin", "" ], [ "Liu", "Jian", "" ] ]
Distributed machine learning paradigms, such as federated learning, have been recently adopted in many privacy-critical applications for speech analysis. However, such frameworks are vulnerable to privacy leakage attacks from shared gradients. Despite extensive efforts in the image domain, the exploration of speech pri...
2403.05732
Nitsan Soffair
Nitsan Soffair, Shie Mannor
Conservative DDPG -- Pessimistic RL without Ensemble
Paper do not ready
null
null
null
cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
DDPG is hindered by the overestimation bias problem, wherein its $Q$-estimates tend to overstate the actual $Q$-values. Traditional solutions to this bias involve ensemble-based methods, which require significant computational resources, or complex log-policy-based approaches, which are difficult to understand and im...
[ { "created": "Fri, 8 Mar 2024 23:59:38 GMT", "version": "v1" }, { "created": "Sun, 2 Jun 2024 19:40:48 GMT", "version": "v2" } ]
2024-06-04
[ [ "Soffair", "Nitsan", "" ], [ "Mannor", "Shie", "" ] ]
DDPG is hindered by the overestimation bias problem, wherein its $Q$-estimates tend to overstate the actual $Q$-values. Traditional solutions to this bias involve ensemble-based methods, which require significant computational resources, or complex log-policy-based approaches, which are difficult to understand and impl...
2102.06930
Kleanthis Avramidis
Kleanthis Avramidis, Agelos Kratimenos, Christos Garoufis, Athanasia Zlatintsi and Petros Maragos
Deep Convolutional and Recurrent Networks for Polyphonic Instrument Classification from Monophonic Raw Audio Waveforms
5 pages, 4 figures, 6 tables, to be published in the Proc. of the 46th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2021) @ Toronto, Ontario, Canada
null
null
null
cs.SD cs.LG eess.AS
http://creativecommons.org/licenses/by/4.0/
Sound Event Detection and Audio Classification tasks are traditionally addressed through time-frequency representations of audio signals such as spectrograms. However, the emergence of deep neural networks as efficient feature extractors has enabled the direct use of audio signals for classification purposes. In this...
[ { "created": "Sat, 13 Feb 2021 13:44:46 GMT", "version": "v1" } ]
2021-02-16
[ [ "Avramidis", "Kleanthis", "" ], [ "Kratimenos", "Agelos", "" ], [ "Garoufis", "Christos", "" ], [ "Zlatintsi", "Athanasia", "" ], [ "Maragos", "Petros", "" ] ]
Sound Event Detection and Audio Classification tasks are traditionally addressed through time-frequency representations of audio signals such as spectrograms. However, the emergence of deep neural networks as efficient feature extractors has enabled the direct use of audio signals for classification purposes. In this p...
1711.09408
Jonathan Zhu
Jonathan J. H. Zhu, Hexin Chen, Tai-Quan Peng, Xiao Fan Liu and Haixing Dai
How to Measure Sessions of Mobile Device Use? Quantification, Evaluation, and Applications
Preprint of forthcoming article in Mobile Media & Communication
null
null
null
cs.CY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Research on mobile phone use often starts with a question of "How much time users spend on using their phones?". The question involves an equal-length measure that captures the duration of mobile phone use but does not tackle the other temporal characteristics of user behavior, such as frequency, timing, and sequence...
[ { "created": "Sun, 26 Nov 2017 15:32:22 GMT", "version": "v1" } ]
2017-11-28
[ [ "Zhu", "Jonathan J. H.", "" ], [ "Chen", "Hexin", "" ], [ "Peng", "Tai-Quan", "" ], [ "Liu", "Xiao Fan", "" ], [ "Dai", "Haixing", "" ] ]
Research on mobile phone use often starts with a question of "How much time users spend on using their phones?". The question involves an equal-length measure that captures the duration of mobile phone use but does not tackle the other temporal characteristics of user behavior, such as frequency, timing, and sequence. ...
2110.09234
Martha Barnard
Martha Barnard (1), Radhika Iyer (1 and 2), Sara Y. Del Valle (1), Ashlynn R. Daughton (1) ((1) A-1 Information Systems and Modeling, Los Alamos National Lab, Los Alamos, NM, USA, (2) Department of Political Science and Department of Computing, Data Science, and Society, University of California, Berkeley, Berk...
Impact of COVID-19 Policies and Misinformation on Social Unrest
21 pages, 9 figures
null
null
LA-UR-21-29745
cs.CY cs.LG stat.AP
http://creativecommons.org/licenses/by-nc-sa/4.0/
The novel coronavirus disease (COVID-19) pandemic has impacted every corner of earth, disrupting governments and leading to socioeconomic instability. This crisis has prompted questions surrounding how different sectors of society interact and influence each other during times of change and stress. Given the unpreced...
[ { "created": "Thu, 7 Oct 2021 16:05:10 GMT", "version": "v1" } ]
2021-10-19
[ [ "Barnard", "Martha", "", "1 and 2" ], [ "Iyer", "Radhika", "", "1 and 2" ], [ "Del Valle", "Sara Y.", "" ], [ "Daughton", "Ashlynn R.", "" ] ]
The novel coronavirus disease (COVID-19) pandemic has impacted every corner of earth, disrupting governments and leading to socioeconomic instability. This crisis has prompted questions surrounding how different sectors of society interact and influence each other during times of change and stress. Given the unpreceden...
2102.04317
Shuquan Ye
Shuquan Ye, Dongdong Chen, Songfang Han, Ziyu Wan, Jing Liao
Meta-PU: An Arbitrary-Scale Upsampling Network for Point Cloud
To appear at TVCG
null
null
null
cs.GR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Point cloud upsampling is vital for the quality of the mesh in three-dimensional reconstruction. Recent research on point cloud upsampling has achieved great success due to the development of deep learning. However, the existing methods regard point cloud upsampling of different scale factors as independent tasks. Th...
[ { "created": "Mon, 8 Feb 2021 16:21:48 GMT", "version": "v1" } ]
2021-02-09
[ [ "Ye", "Shuquan", "" ], [ "Chen", "Dongdong", "" ], [ "Han", "Songfang", "" ], [ "Wan", "Ziyu", "" ], [ "Liao", "Jing", "" ] ]
Point cloud upsampling is vital for the quality of the mesh in three-dimensional reconstruction. Recent research on point cloud upsampling has achieved great success due to the development of deep learning. However, the existing methods regard point cloud upsampling of different scale factors as independent tasks. Thus...
1607.04557
Alfonso Cevallos
Alfonso Cevallos, Friedrich Eisenbrand, Rico Zenklusen
Local Search for Max-Sum Diversification
null
null
null
null
cs.DS cs.CG cs.DM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We provide simple and fast polynomial time approximation schemes (PTASs) for several variants of the max-sum diversification problem which, in its most basic form, is as follows: Given n points p_1,...,p_n in R^d and an integer k, select k points such that the average Euclidean distance between these points is maximi...
[ { "created": "Fri, 15 Jul 2016 15:38:02 GMT", "version": "v1" } ]
2016-07-18
[ [ "Cevallos", "Alfonso", "" ], [ "Eisenbrand", "Friedrich", "" ], [ "Zenklusen", "Rico", "" ] ]
We provide simple and fast polynomial time approximation schemes (PTASs) for several variants of the max-sum diversification problem which, in its most basic form, is as follows: Given n points p_1,...,p_n in R^d and an integer k, select k points such that the average Euclidean distance between these points is maximize...
1706.06322
Mohamd Sultan
Mohamad T. Sultan and Salim M. Zaki
Evaluation of energy consumption of reactive and proactive routing protocols in MANET
null
null
null
null
cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Mobile Ad hoc Network (MANET) is a distributed, infrastructure-less and decentralized network. A routing protocol in MANET is used to find routes between mobile nodes to facilitate communication within the network. Numerous routing protocols have been proposed for MANET. Those routing protocols are designed to adapti...
[ { "created": "Tue, 20 Jun 2017 08:56:12 GMT", "version": "v1" } ]
2017-06-21
[ [ "Sultan", "Mohamad T.", "" ], [ "Zaki", "Salim M.", "" ] ]
Mobile Ad hoc Network (MANET) is a distributed, infrastructure-less and decentralized network. A routing protocol in MANET is used to find routes between mobile nodes to facilitate communication within the network. Numerous routing protocols have been proposed for MANET. Those routing protocols are designed to adaptive...
1606.05839
EPTCS
Olivier Danvy (University of Aarhus), Ugo de'Liguoro (Universit\`a di Torino)
Proceedings of the Workshop on Continuations
null
EPTCS 212, 2016
10.4204/EPTCS.212
null
cs.PL cs.LO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The notion of continuation is ubiquitous in many different areas of computer science, including systems programming, programming languages, algorithmics, semantics, logic, and constructive mathematics. In fact the concept of continuation nicely realizes sophisticated control mechanisms, which are widely used in a var...
[ { "created": "Sun, 19 Jun 2016 07:25:03 GMT", "version": "v1" } ]
2016-06-21
[ [ "Danvy", "Olivier", "", "University of Aarhus" ], [ "de'Liguoro", "Ugo", "", "Università di\n Torino" ] ]
The notion of continuation is ubiquitous in many different areas of computer science, including systems programming, programming languages, algorithmics, semantics, logic, and constructive mathematics. In fact the concept of continuation nicely realizes sophisticated control mechanisms, which are widely used in a varie...
2001.00784
Dong Liu
Dong Liu, Chengjian Sun, Chenyang Yang, Lajos Hanzo
Optimizing Wireless Systems Using Unsupervised and Reinforced-Unsupervised Deep Learning
To appear in IEEE Network Magazine
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Resource allocation and transceivers in wireless networks are usually designed by solving optimization problems subject to specific constraints, which can be formulated as variable or functional optimization. If the objective and constraint functions of a variable optimization problem can be derived, standard numeric...
[ { "created": "Fri, 3 Jan 2020 11:01:52 GMT", "version": "v1" } ]
2020-01-06
[ [ "Liu", "Dong", "" ], [ "Sun", "Chengjian", "" ], [ "Yang", "Chenyang", "" ], [ "Hanzo", "Lajos", "" ] ]
Resource allocation and transceivers in wireless networks are usually designed by solving optimization problems subject to specific constraints, which can be formulated as variable or functional optimization. If the objective and constraint functions of a variable optimization problem can be derived, standard numerical...
2105.06807
Ruoxi Chen
Jinyin Chen, Ruoxi Chen, Haibin Zheng, Zhaoyan Ming, Wenrong Jiang and Chen Cui
Salient Feature Extractor for Adversarial Defense on Deep Neural Networks
null
null
null
null
cs.CV cs.AI cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recent years have witnessed unprecedented success achieved by deep learning models in the field of computer vision. However, their vulnerability towards carefully crafted adversarial examples has also attracted the increasing attention of researchers. Motivated by the observation that adversarial examples are due to ...
[ { "created": "Fri, 14 May 2021 12:56:06 GMT", "version": "v1" } ]
2021-05-17
[ [ "Chen", "Jinyin", "" ], [ "Chen", "Ruoxi", "" ], [ "Zheng", "Haibin", "" ], [ "Ming", "Zhaoyan", "" ], [ "Jiang", "Wenrong", "" ], [ "Cui", "Chen", "" ] ]
Recent years have witnessed unprecedented success achieved by deep learning models in the field of computer vision. However, their vulnerability towards carefully crafted adversarial examples has also attracted the increasing attention of researchers. Motivated by the observation that adversarial examples are due to th...
1407.1429
Mohammad Nassiry
Mohammad Nassiry, Muriati Mukhtar
Business types classification via e-commerce stage model in oil industry in Iran
null
null
null
null
cs.OH
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Since the strategies and plans for e-commerce development are different for different industries and since the oil industry is one of the most important industries in Iran, the scope of this research is thus confined to that of the oil industry in Iran. The main aim of this study is to identify and classify the diffe...
[ { "created": "Sat, 5 Jul 2014 19:33:10 GMT", "version": "v1" } ]
2014-07-08
[ [ "Nassiry", "Mohammad", "" ], [ "Mukhtar", "Muriati", "" ] ]
Since the strategies and plans for e-commerce development are different for different industries and since the oil industry is one of the most important industries in Iran, the scope of this research is thus confined to that of the oil industry in Iran. The main aim of this study is to identify and classify the differe...
1701.03305
Masahito Hayashi
Ryo Yaguchi and Masahito Hayashi
Finite-Length Bounds for Joint Source-Channel Coding with Markovian Source and Additive Channel Noise to Achieve Large and Moderate Deviation Bounds
This paper and arXiv:1701.03290 address joint source-channel coding with markovian source. While arXiv:1701.03290 discusses the second order analysis, this paper discusses finite-length bounds as well as large and moderate deviation bounds. Hence, there is no overlap between these two papers
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We derive novel upper and lower finite-length bounds of the error probability in joint source-channel coding when the source obeys an ergodic Markov process and the channel is a Markovian additive channel or a Markovian conditional additive channel. These bounds are tight in the large and moderate deviation regimes.
[ { "created": "Thu, 12 Jan 2017 11:09:57 GMT", "version": "v1" }, { "created": "Tue, 2 May 2017 03:39:26 GMT", "version": "v2" } ]
2017-05-03
[ [ "Yaguchi", "Ryo", "" ], [ "Hayashi", "Masahito", "" ] ]
We derive novel upper and lower finite-length bounds of the error probability in joint source-channel coding when the source obeys an ergodic Markov process and the channel is a Markovian additive channel or a Markovian conditional additive channel. These bounds are tight in the large and moderate deviation regimes.
2402.11724
Jianling Wang
Jianling Wang, Haokai Lu, James Caverlee, Ed Chi and Minmin Chen
Large Language Models as Data Augmenters for Cold-Start Item Recommendation
null
null
null
null
cs.IR
http://creativecommons.org/licenses/by/4.0/
The reasoning and generalization capabilities of LLMs can help us better understand user preferences and item characteristics, offering exciting prospects to enhance recommendation systems. Though effective while user-item interactions are abundant, conventional recommendation systems struggle to recommend cold-start...
[ { "created": "Sun, 18 Feb 2024 22:29:04 GMT", "version": "v1" } ]
2024-02-20
[ [ "Wang", "Jianling", "" ], [ "Lu", "Haokai", "" ], [ "Caverlee", "James", "" ], [ "Chi", "Ed", "" ], [ "Chen", "Minmin", "" ] ]
The reasoning and generalization capabilities of LLMs can help us better understand user preferences and item characteristics, offering exciting prospects to enhance recommendation systems. Though effective while user-item interactions are abundant, conventional recommendation systems struggle to recommend cold-start i...
1904.09763
Seungjun Jung
Seungjun Jung, Muhammad Abul Hasan and Changick Kim
Water-Filling: An Efficient Algorithm for Digitized Document Shadow Removal
Accepted at Asian Conference on Computer Vision (2018)
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we propose a novel algorithm to rectify illumination of the digitized documents by eliminating shading artifacts. Firstly, a topographic surface of an input digitized document is created using luminance value of each pixel. Then the shading artifact on the document is estimated by simulating an immersi...
[ { "created": "Mon, 22 Apr 2019 08:01:27 GMT", "version": "v1" }, { "created": "Thu, 2 May 2019 18:44:59 GMT", "version": "v2" } ]
2019-05-06
[ [ "Jung", "Seungjun", "" ], [ "Hasan", "Muhammad Abul", "" ], [ "Kim", "Changick", "" ] ]
In this paper, we propose a novel algorithm to rectify illumination of the digitized documents by eliminating shading artifacts. Firstly, a topographic surface of an input digitized document is created using luminance value of each pixel. Then the shading artifact on the document is estimated by simulating an immersion...
1605.07515
Michael Roth
Michael Roth, Mirella Lapata
Neural Semantic Role Labeling with Dependency Path Embeddings
Camera-ready ACL paper
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper introduces a novel model for semantic role labeling that makes use of neural sequence modeling techniques. Our approach is motivated by the observation that complex syntactic structures and related phenomena, such as nested subordinations and nominal predicates, are not handled well by existing models. Our...
[ { "created": "Tue, 24 May 2016 15:54:48 GMT", "version": "v1" }, { "created": "Mon, 18 Jul 2016 09:08:51 GMT", "version": "v2" } ]
2016-07-19
[ [ "Roth", "Michael", "" ], [ "Lapata", "Mirella", "" ] ]
This paper introduces a novel model for semantic role labeling that makes use of neural sequence modeling techniques. Our approach is motivated by the observation that complex syntactic structures and related phenomena, such as nested subordinations and nominal predicates, are not handled well by existing models. Our m...
1707.00513
Chao Zhang
Chao Zhang, Vineeth Varma, Samson Lasaulce, Raphael Visoz
Interference Coordination via Power Domain Channel Estimation
null
null
null
null
cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A novel technique is proposed which enables each transmitter to acquire global channel state information (CSI) from the sole knowledge of individual received signal power measurements, which makes dedicated feedback or inter-transmitter signaling channels unnecessary. To make this possible, we resort to a completely ...
[ { "created": "Wed, 14 Jun 2017 08:04:12 GMT", "version": "v1" } ]
2017-07-04
[ [ "Zhang", "Chao", "" ], [ "Varma", "Vineeth", "" ], [ "Lasaulce", "Samson", "" ], [ "Visoz", "Raphael", "" ] ]
A novel technique is proposed which enables each transmitter to acquire global channel state information (CSI) from the sole knowledge of individual received signal power measurements, which makes dedicated feedback or inter-transmitter signaling channels unnecessary. To make this possible, we resort to a completely ne...
2306.01310
Jaeseung Heo
Jaeseung Heo, Seungbeom Lee, Sungsoo Ahn, Dongwoo Kim
EPIC: Graph Augmentation with Edit Path Interpolation via Learnable Cost
null
null
null
null
cs.LG cs.AI
http://creativecommons.org/licenses/by/4.0/
Data augmentation plays a critical role in improving model performance across various domains, but it becomes challenging with graph data due to their complex and irregular structure. To address this issue, we propose EPIC (Edit Path Interpolation via learnable Cost), a novel interpolation-based method for augmenting...
[ { "created": "Fri, 2 Jun 2023 07:19:07 GMT", "version": "v1" }, { "created": "Tue, 4 Jun 2024 05:54:38 GMT", "version": "v2" } ]
2024-06-05
[ [ "Heo", "Jaeseung", "" ], [ "Lee", "Seungbeom", "" ], [ "Ahn", "Sungsoo", "" ], [ "Kim", "Dongwoo", "" ] ]
Data augmentation plays a critical role in improving model performance across various domains, but it becomes challenging with graph data due to their complex and irregular structure. To address this issue, we propose EPIC (Edit Path Interpolation via learnable Cost), a novel interpolation-based method for augmenting g...
2405.06001
Yushi Huang
Ruihao Gong, Yang Yong, Shiqiao Gu, Yushi Huang, Chentao Lv, Yunchen Zhang, Xianglong Liu, Dacheng Tao
LLMC: Benchmarking Large Language Model Quantization with a Versatile Compression Toolkit
null
null
null
null
cs.LG cs.AI cs.CL
http://creativecommons.org/licenses/by/4.0/
Recent advancements in large language models (LLMs) are propelling us toward artificial general intelligence with their remarkable emergent abilities and reasoning capabilities. However, the substantial computational and memory requirements limit the widespread adoption. Quantization, a key compression technique, can...
[ { "created": "Thu, 9 May 2024 11:49:05 GMT", "version": "v1" }, { "created": "Sat, 20 Jul 2024 07:29:51 GMT", "version": "v2" } ]
2024-07-23
[ [ "Gong", "Ruihao", "" ], [ "Yong", "Yang", "" ], [ "Gu", "Shiqiao", "" ], [ "Huang", "Yushi", "" ], [ "Lv", "Chentao", "" ], [ "Zhang", "Yunchen", "" ], [ "Liu", "Xianglong", "" ], [ "Tao", "Dach...
Recent advancements in large language models (LLMs) are propelling us toward artificial general intelligence with their remarkable emergent abilities and reasoning capabilities. However, the substantial computational and memory requirements limit the widespread adoption. Quantization, a key compression technique, can e...
2110.07888
Xingcheng Fu
Xingcheng Fu, Jianxin Li, Jia Wu, Qingyun Sun, Cheng Ji, Senzhang Wang, Jiajun Tan, Hao Peng and Philip S. Yu
ACE-HGNN: Adaptive Curvature Exploration Hyperbolic Graph Neural Network
null
null
10.1109/ICDM51629.2021.00021
null
cs.LG cs.SI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Graph Neural Networks (GNNs) have been widely studied in various graph data mining tasks. Most existingGNNs embed graph data into Euclidean space and thus are less effective to capture the ubiquitous hierarchical structures in real-world networks. Hyperbolic Graph Neural Networks(HGNNs) extend GNNs to hyperbolic spac...
[ { "created": "Fri, 15 Oct 2021 07:18:57 GMT", "version": "v1" } ]
2022-03-04
[ [ "Fu", "Xingcheng", "" ], [ "Li", "Jianxin", "" ], [ "Wu", "Jia", "" ], [ "Sun", "Qingyun", "" ], [ "Ji", "Cheng", "" ], [ "Wang", "Senzhang", "" ], [ "Tan", "Jiajun", "" ], [ "Peng", "Hao", ...
Graph Neural Networks (GNNs) have been widely studied in various graph data mining tasks. Most existingGNNs embed graph data into Euclidean space and thus are less effective to capture the ubiquitous hierarchical structures in real-world networks. Hyperbolic Graph Neural Networks(HGNNs) extend GNNs to hyperbolic space ...
2101.06829
Tianxing He
Tianxing He, Bryan McCann, Caiming Xiong, Ehsan Hosseini-Asl
Joint Energy-based Model Training for Better Calibrated Natural Language Understanding Models
null
EACL 2021
null
null
cs.CL cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this work, we explore joint energy-based model (EBM) training during the finetuning of pretrained text encoders (e.g., Roberta) for natural language understanding (NLU) tasks. Our experiments show that EBM training can help the model reach a better calibration that is competitive to strong baselines, with little o...
[ { "created": "Mon, 18 Jan 2021 01:41:31 GMT", "version": "v1" }, { "created": "Fri, 19 Feb 2021 18:36:31 GMT", "version": "v2" } ]
2021-02-22
[ [ "He", "Tianxing", "" ], [ "McCann", "Bryan", "" ], [ "Xiong", "Caiming", "" ], [ "Hosseini-Asl", "Ehsan", "" ] ]
In this work, we explore joint energy-based model (EBM) training during the finetuning of pretrained text encoders (e.g., Roberta) for natural language understanding (NLU) tasks. Our experiments show that EBM training can help the model reach a better calibration that is competitive to strong baselines, with little or ...
2201.01182
Kshitija Taywade
Kshitija Taywade, Brent Harrison, Adib Bagh
Modelling Cournot Games as Multi-agent Multi-armed Bandits
12 pages. arXiv admin note: text overlap with arXiv:2201.00486
null
null
null
cs.GT cs.AI cs.LG cs.MA econ.EM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We investigate the use of a multi-agent multi-armed bandit (MA-MAB) setting for modeling repeated Cournot oligopoly games, where the firms acting as agents choose from the set of arms representing production quantity (a discrete value). Agents interact with separate and independent bandit problems. In this formulatio...
[ { "created": "Sat, 1 Jan 2022 22:02:47 GMT", "version": "v1" } ]
2022-01-05
[ [ "Taywade", "Kshitija", "" ], [ "Harrison", "Brent", "" ], [ "Bagh", "Adib", "" ] ]
We investigate the use of a multi-agent multi-armed bandit (MA-MAB) setting for modeling repeated Cournot oligopoly games, where the firms acting as agents choose from the set of arms representing production quantity (a discrete value). Agents interact with separate and independent bandit problems. In this formulation,...
2407.13071
Vatsal Vinay Parikh
Vatsal Vinay Parikh
Analysing the Public Discourse around OpenAI's Text-To-Video Model 'Sora' using Topic Modeling
null
null
null
null
cs.CY cs.CL cs.IR cs.LG cs.SI
http://creativecommons.org/publicdomain/zero/1.0/
The recent introduction of OpenAI's text-to-video model Sora has sparked widespread public discourse across online communities. This study aims to uncover the dominant themes and narratives surrounding Sora by conducting topic modeling analysis on a corpus of 1,827 Reddit comments from five relevant subreddits (r/Ope...
[ { "created": "Thu, 30 May 2024 01:55:30 GMT", "version": "v1" } ]
2024-07-19
[ [ "Parikh", "Vatsal Vinay", "" ] ]
The recent introduction of OpenAI's text-to-video model Sora has sparked widespread public discourse across online communities. This study aims to uncover the dominant themes and narratives surrounding Sora by conducting topic modeling analysis on a corpus of 1,827 Reddit comments from five relevant subreddits (r/OpenA...
1904.13279
Tim Pfeifer
Tim Pfeifer and Peter Protzel
Incrementally Learned Mixture Models for GNSS Localization
8 pages, 5 figures, published in proceedings of IEEE Intelligent Vehicles Symposium (IV) 2019
null
10.1109/IVS.2019.8813847
null
cs.RO eess.SP
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
GNSS localization is an important part of today's autonomous systems, although it suffers from non-Gaussian errors caused by non-line-of-sight effects. Recent methods are able to mitigate these effects by including the corresponding distributions in the sensor fusion algorithm. However, these approaches require prior...
[ { "created": "Tue, 30 Apr 2019 14:39:00 GMT", "version": "v1" }, { "created": "Thu, 19 Mar 2020 11:27:11 GMT", "version": "v2" } ]
2020-03-20
[ [ "Pfeifer", "Tim", "" ], [ "Protzel", "Peter", "" ] ]
GNSS localization is an important part of today's autonomous systems, although it suffers from non-Gaussian errors caused by non-line-of-sight effects. Recent methods are able to mitigate these effects by including the corresponding distributions in the sensor fusion algorithm. However, these approaches require prior k...
2011.01584
Li-Yang Tan
Guy Blanc, Neha Gupta, Jane Lange, Li-Yang Tan
Estimating decision tree learnability with polylogarithmic sample complexity
25 pages, to appear in NeurIPS 2020
null
null
null
cs.LG cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We show that top-down decision tree learning heuristics are amenable to highly efficient learnability estimation: for monotone target functions, the error of the decision tree hypothesis constructed by these heuristics can be estimated with polylogarithmically many labeled examples, exponentially smaller than the num...
[ { "created": "Tue, 3 Nov 2020 09:26:27 GMT", "version": "v1" } ]
2020-11-04
[ [ "Blanc", "Guy", "" ], [ "Gupta", "Neha", "" ], [ "Lange", "Jane", "" ], [ "Tan", "Li-Yang", "" ] ]
We show that top-down decision tree learning heuristics are amenable to highly efficient learnability estimation: for monotone target functions, the error of the decision tree hypothesis constructed by these heuristics can be estimated with polylogarithmically many labeled examples, exponentially smaller than the numbe...
2009.06560
Lily Xu
Lily Xu, Elizabeth Bondi, Fei Fang, Andrew Perrault, Kai Wang, Milind Tambe
Dual-Mandate Patrols: Multi-Armed Bandits for Green Security
Published at AAAI 2021. 9 pages (paper and references), 3 page appendix. 6 figures and 1 table
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Conservation efforts in green security domains to protect wildlife and forests are constrained by the limited availability of defenders (i.e., patrollers), who must patrol vast areas to protect from attackers (e.g., poachers or illegal loggers). Defenders must choose how much time to spend in each region of the prote...
[ { "created": "Mon, 14 Sep 2020 16:40:44 GMT", "version": "v1" }, { "created": "Tue, 15 Dec 2020 05:35:48 GMT", "version": "v2" }, { "created": "Fri, 26 Apr 2024 13:51:17 GMT", "version": "v3" } ]
2024-04-29
[ [ "Xu", "Lily", "" ], [ "Bondi", "Elizabeth", "" ], [ "Fang", "Fei", "" ], [ "Perrault", "Andrew", "" ], [ "Wang", "Kai", "" ], [ "Tambe", "Milind", "" ] ]
Conservation efforts in green security domains to protect wildlife and forests are constrained by the limited availability of defenders (i.e., patrollers), who must patrol vast areas to protect from attackers (e.g., poachers or illegal loggers). Defenders must choose how much time to spend in each region of the protect...
2212.00222
Madelyn Shapiro
Emilie Purvine, Davis Brown, Brett Jefferson, Cliff Joslyn, Brenda Praggastis, Archit Rathore, Madelyn Shapiro, Bei Wang, Youjia Zhou
Experimental Observations of the Topology of Convolutional Neural Network Activations
Accepted at AAAI 2023. This version includes supplementary material
null
null
null
cs.LG cs.CG
http://creativecommons.org/licenses/by/4.0/
Topological data analysis (TDA) is a branch of computational mathematics, bridging algebraic topology and data science, that provides compact, noise-robust representations of complex structures. Deep neural networks (DNNs) learn millions of parameters associated with a series of transformations defined by the model a...
[ { "created": "Thu, 1 Dec 2022 02:05:44 GMT", "version": "v1" } ]
2022-12-02
[ [ "Purvine", "Emilie", "" ], [ "Brown", "Davis", "" ], [ "Jefferson", "Brett", "" ], [ "Joslyn", "Cliff", "" ], [ "Praggastis", "Brenda", "" ], [ "Rathore", "Archit", "" ], [ "Shapiro", "Madelyn", "" ], [...
Topological data analysis (TDA) is a branch of computational mathematics, bridging algebraic topology and data science, that provides compact, noise-robust representations of complex structures. Deep neural networks (DNNs) learn millions of parameters associated with a series of transformations defined by the model arc...
1404.3660
Ren\'e van Bevern
Ren\'e van Bevern, Sepp Hartung, Andr\'e Nichterlein, Manuel Sorge
Constant-factor approximations for Capacitated Arc Routing without triangle inequality
null
Operations Research Letters 42(4):290--292, 2014
10.1016/j.orl.2014.05.002
null
cs.DS cs.DM math.CO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Given an undirected graph with edge costs and edge demands, the Capacitated Arc Routing problem (CARP) asks for minimum-cost routes for equal-capacity vehicles so as to satisfy all demands. Constant-factor polynomial-time approximation algorithms were proposed for CARP with triangle inequality, while CARP was claimed...
[ { "created": "Mon, 14 Apr 2014 17:28:19 GMT", "version": "v1" } ]
2014-07-15
[ [ "van Bevern", "René", "" ], [ "Hartung", "Sepp", "" ], [ "Nichterlein", "André", "" ], [ "Sorge", "Manuel", "" ] ]
Given an undirected graph with edge costs and edge demands, the Capacitated Arc Routing problem (CARP) asks for minimum-cost routes for equal-capacity vehicles so as to satisfy all demands. Constant-factor polynomial-time approximation algorithms were proposed for CARP with triangle inequality, while CARP was claimed t...
2105.01747
Pradeep Kr. Banerjee
Pradeep Kr. Banerjee, Guido Mont\'ufar
Information Complexity and Generalization Bounds
To appear in 2021 IEEE International Symposium on Information Theory (ISIT); 23 pages
null
10.1109/ISIT45174.2021.9517960
null
cs.LG cs.IT math.IT
http://creativecommons.org/licenses/by/4.0/
We present a unifying picture of PAC-Bayesian and mutual information-based upper bounds on the generalization error of randomized learning algorithms. As we show, Tong Zhang's information exponential inequality (IEI) gives a general recipe for constructing bounds of both flavors. We show that several important result...
[ { "created": "Tue, 4 May 2021 20:37:57 GMT", "version": "v1" }, { "created": "Sun, 24 Oct 2021 02:02:45 GMT", "version": "v2" } ]
2021-10-26
[ [ "Banerjee", "Pradeep Kr.", "" ], [ "Montúfar", "Guido", "" ] ]
We present a unifying picture of PAC-Bayesian and mutual information-based upper bounds on the generalization error of randomized learning algorithms. As we show, Tong Zhang's information exponential inequality (IEI) gives a general recipe for constructing bounds of both flavors. We show that several important results ...
2310.15928
Claire Chen
Carlota Par\'es Morlans, Claire Chen, Yijia Weng, Michelle Yi, Yuying Huang, Nick Heppert, Linqi Zhou, Leonidas Guibas, Jeannette Bohg
AO-Grasp: Articulated Object Grasp Generation
Project website: https://stanford-iprl-lab.github.io/ao-grasp
null
null
null
cs.RO
http://creativecommons.org/licenses/by/4.0/
We introduce AO-Grasp, a grasp proposal method that generates 6 DoF grasps that enable robots to interact with articulated objects, such as opening and closing cabinets and appliances. AO-Grasp consists of two main contributions: the AO-Grasp Model and the AO-Grasp Dataset. Given a segmented partial point cloud of a ...
[ { "created": "Tue, 24 Oct 2023 15:26:57 GMT", "version": "v1" }, { "created": "Mon, 18 Mar 2024 17:36:33 GMT", "version": "v2" } ]
2024-03-19
[ [ "Morlans", "Carlota Parés", "" ], [ "Chen", "Claire", "" ], [ "Weng", "Yijia", "" ], [ "Yi", "Michelle", "" ], [ "Huang", "Yuying", "" ], [ "Heppert", "Nick", "" ], [ "Zhou", "Linqi", "" ], [ "Guiba...
We introduce AO-Grasp, a grasp proposal method that generates 6 DoF grasps that enable robots to interact with articulated objects, such as opening and closing cabinets and appliances. AO-Grasp consists of two main contributions: the AO-Grasp Model and the AO-Grasp Dataset. Given a segmented partial point cloud of a si...
2406.17070
Dimitris Chytas
Dimitris Chytas, Nithin Raveendran, Bane Vasi\'c
Collective Bit Flipping-Based Decoding of Quantum LDPC Codes
13 pages, 12 figures
null
null
null
cs.IT math.IT quant-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Quantum low-density parity-check (QLDPC) codes have been proven to achieve higher minimum distances at higher code rates than surface codes. However, this family of codes imposes stringent latency requirements and poor performance under iterative decoding, especially when the variable degree is low. In this work, we ...
[ { "created": "Mon, 24 Jun 2024 18:51:48 GMT", "version": "v1" } ]
2024-06-26
[ [ "Chytas", "Dimitris", "" ], [ "Raveendran", "Nithin", "" ], [ "Vasić", "Bane", "" ] ]
Quantum low-density parity-check (QLDPC) codes have been proven to achieve higher minimum distances at higher code rates than surface codes. However, this family of codes imposes stringent latency requirements and poor performance under iterative decoding, especially when the variable degree is low. In this work, we im...
2104.10845
Li Zhang
Yuxuan Chen, Li Zhang, Shijian Li, Gang Pan
Optimize Neural Fictitious Self-Play in Regret Minimization Thinking
null
null
null
null
cs.AI
http://creativecommons.org/licenses/by/4.0/
Optimization of deep learning algorithms to approach Nash Equilibrium remains a significant problem in imperfect information games, e.g. StarCraft and poker. Neural Fictitious Self-Play (NFSP) has provided an effective way to learn approximate Nash Equilibrium without prior domain knowledge in imperfect information g...
[ { "created": "Thu, 22 Apr 2021 03:24:23 GMT", "version": "v1" } ]
2021-04-23
[ [ "Chen", "Yuxuan", "" ], [ "Zhang", "Li", "" ], [ "Li", "Shijian", "" ], [ "Pan", "Gang", "" ] ]
Optimization of deep learning algorithms to approach Nash Equilibrium remains a significant problem in imperfect information games, e.g. StarCraft and poker. Neural Fictitious Self-Play (NFSP) has provided an effective way to learn approximate Nash Equilibrium without prior domain knowledge in imperfect information gam...
2405.08709
Amirreza Zamani
Amirreza Zamani, Sajad Daei, Tobias J. Oechtering, Mikael Skoglund
Multi-Task Private Semantic Communication
null
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We study a multi-task private semantic communication problem, in which an encoder has access to an information source arbitrarily correlated with some latent private data. A user has $L$ tasks with priorities. The encoder designs a message to be revealed which is called the semantic of the information source. Due to ...
[ { "created": "Tue, 14 May 2024 15:50:49 GMT", "version": "v1" } ]
2024-05-15
[ [ "Zamani", "Amirreza", "" ], [ "Daei", "Sajad", "" ], [ "Oechtering", "Tobias J.", "" ], [ "Skoglund", "Mikael", "" ] ]
We study a multi-task private semantic communication problem, in which an encoder has access to an information source arbitrarily correlated with some latent private data. A user has $L$ tasks with priorities. The encoder designs a message to be revealed which is called the semantic of the information source. Due to th...
2402.08897
Adam Seewald
Adam Seewald, Marvin Chanc\'an, Connor M. McCann, Seonghoon Noh, Omeed Fallahi, Hector Castillo, Ian Abraham, Aaron M. Dollar
RB5 Low-Cost Explorer: Implementing Autonomous Long-Term Exploration on Low-Cost Robotic Hardware
7 pages, 5 figures, ICRA'24
null
null
null
cs.RO
http://creativecommons.org/licenses/by-nc-sa/4.0/
This systems paper presents the implementation and design of RB5, a wheeled robot for autonomous long-term exploration with fewer and cheaper sensors. Requiring just an RGB-D camera and low-power computing hardware, the system consists of an experimental platform with rocker-bogie suspension. It operates in unknown a...
[ { "created": "Wed, 14 Feb 2024 02:07:04 GMT", "version": "v1" } ]
2024-02-15
[ [ "Seewald", "Adam", "" ], [ "Chancán", "Marvin", "" ], [ "McCann", "Connor M.", "" ], [ "Noh", "Seonghoon", "" ], [ "Fallahi", "Omeed", "" ], [ "Castillo", "Hector", "" ], [ "Abraham", "Ian", "" ], [ ...
This systems paper presents the implementation and design of RB5, a wheeled robot for autonomous long-term exploration with fewer and cheaper sensors. Requiring just an RGB-D camera and low-power computing hardware, the system consists of an experimental platform with rocker-bogie suspension. It operates in unknown and...
2312.07553
Joon Hyun Jeong
Joonhyun Jeong
Hijacking Context in Large Multi-modal Models
Technical Report. Preprint
ICLR 2024 Workshop on Reliable and Responsible Foundation Models
null
null
cs.AI cs.CL
http://creativecommons.org/licenses/by/4.0/
Recently, Large Multi-modal Models (LMMs) have demonstrated their ability to understand the visual contents of images given the instructions regarding the images. Built upon the Large Language Models (LLMs), LMMs also inherit their abilities and characteristics such as in-context learning where a coherent sequence of...
[ { "created": "Thu, 7 Dec 2023 11:23:29 GMT", "version": "v1" }, { "created": "Mon, 13 May 2024 10:42:05 GMT", "version": "v2" } ]
2024-05-14
[ [ "Jeong", "Joonhyun", "" ] ]
Recently, Large Multi-modal Models (LMMs) have demonstrated their ability to understand the visual contents of images given the instructions regarding the images. Built upon the Large Language Models (LLMs), LMMs also inherit their abilities and characteristics such as in-context learning where a coherent sequence of i...
2405.13365
Zavareh Bozorgasl
Zavareh Bozorgasl and Hao Chen
Clipped Uniform Quantizers for Communication-Efficient Federated Learning
Work in progress
null
null
null
cs.LG cs.MA eess.SP
http://creativecommons.org/licenses/by/4.0/
This paper introduces an approach to employ clipped uniform quantization in federated learning settings, aiming to enhance model efficiency by reducing communication overhead without compromising accuracy. By employing optimal clipping thresholds and adaptive quantization schemes, our method significantly curtails th...
[ { "created": "Wed, 22 May 2024 05:48:25 GMT", "version": "v1" } ]
2024-05-24
[ [ "Bozorgasl", "Zavareh", "" ], [ "Chen", "Hao", "" ] ]
This paper introduces an approach to employ clipped uniform quantization in federated learning settings, aiming to enhance model efficiency by reducing communication overhead without compromising accuracy. By employing optimal clipping thresholds and adaptive quantization schemes, our method significantly curtails the ...
2303.01295
Antonio Guerriero
Antonio Guerriero, Roberto Pietrantuono, Stefano Russo
Iterative Assessment and Improvement of DNN Operational Accuracy
Paper accepted at 45th International Conference on Software Engineering (ICSE'23 NIER), May 2023
null
10.1109/ICSE-NIER58687.2023.00014
null
cs.LG cs.AI cs.CV cs.SE
http://creativecommons.org/licenses/by/4.0/
Deep Neural Networks (DNN) are nowadays largely adopted in many application domains thanks to their human-like, or even superhuman, performance in specific tasks. However, due to unpredictable/unconsidered operating conditions, unexpected failures show up on field, making the performance of a DNN in operation very di...
[ { "created": "Thu, 2 Mar 2023 14:21:54 GMT", "version": "v1" } ]
2024-03-27
[ [ "Guerriero", "Antonio", "" ], [ "Pietrantuono", "Roberto", "" ], [ "Russo", "Stefano", "" ] ]
Deep Neural Networks (DNN) are nowadays largely adopted in many application domains thanks to their human-like, or even superhuman, performance in specific tasks. However, due to unpredictable/unconsidered operating conditions, unexpected failures show up on field, making the performance of a DNN in operation very diff...
1406.5988
Luca Sanguinetti
Luca Sanguinetti, Aris L. Moustakas, Emil Bjornson, and Merouane Debbah
Large System Analysis of the Energy Consumption Distribution in Multi-User MIMO Systems with Mobility
8 figures, 2 tables, to appear on IEEE Transactions on Wireless Communications
null
10.1109/TWC.2014.2372761
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this work, we consider the downlink of a single-cell multi-user MIMO system in which the base station (BS) makes use of $N$ antennas to communicate with $K$ single-antenna user equipments (UEs). The UEs move around in the cell according to a random walk mobility model. We aim at determining the energy consumption ...
[ { "created": "Mon, 23 Jun 2014 17:18:15 GMT", "version": "v1" }, { "created": "Mon, 5 Jan 2015 08:31:45 GMT", "version": "v2" } ]
2016-11-18
[ [ "Sanguinetti", "Luca", "" ], [ "Moustakas", "Aris L.", "" ], [ "Bjornson", "Emil", "" ], [ "Debbah", "Merouane", "" ] ]
In this work, we consider the downlink of a single-cell multi-user MIMO system in which the base station (BS) makes use of $N$ antennas to communicate with $K$ single-antenna user equipments (UEs). The UEs move around in the cell according to a random walk mobility model. We aim at determining the energy consumption di...
1911.00616
Eduardo Soares Mr
Eduardo Soares, Plamen Angelov
Novelty Detection and Learning from Extremely Weak Supervision
null
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper we offer a method and algorithm, which make possible fully autonomous (unsupervised) detection of new classes, and learning following a very parsimonious training priming (few labeled data samples only). Moreover, new unknown classes may appear at a later stage and the proposed xClass method and algorit...
[ { "created": "Fri, 1 Nov 2019 23:51:08 GMT", "version": "v1" } ]
2019-11-05
[ [ "Soares", "Eduardo", "" ], [ "Angelov", "Plamen", "" ] ]
In this paper we offer a method and algorithm, which make possible fully autonomous (unsupervised) detection of new classes, and learning following a very parsimonious training priming (few labeled data samples only). Moreover, new unknown classes may appear at a later stage and the proposed xClass method and algorithm...
2203.11903
Chace Lee
Chace Lee, Angelica Willis, Christina Chen, Marcin Sieniek, Akib Uddin, Jonny Wong, Rory Pilgrim, Katherine Chou, Daniel Tse, Shravya Shetty, Ryan G. Gomes
Enabling faster and more reliable sonographic assessment of gestational age through machine learning
null
null
null
null
cs.LG cs.CV eess.IV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Fetal ultrasounds are an essential part of prenatal care and can be used to estimate gestational age (GA). Accurate GA assessment is important for providing appropriate prenatal care throughout pregnancy and identifying complications such as fetal growth disorders. Since derivation of GA from manual fetal biometry me...
[ { "created": "Tue, 22 Mar 2022 17:15:56 GMT", "version": "v1" } ]
2022-03-23
[ [ "Lee", "Chace", "" ], [ "Willis", "Angelica", "" ], [ "Chen", "Christina", "" ], [ "Sieniek", "Marcin", "" ], [ "Uddin", "Akib", "" ], [ "Wong", "Jonny", "" ], [ "Pilgrim", "Rory", "" ], [ "Chou", ...
Fetal ultrasounds are an essential part of prenatal care and can be used to estimate gestational age (GA). Accurate GA assessment is important for providing appropriate prenatal care throughout pregnancy and identifying complications such as fetal growth disorders. Since derivation of GA from manual fetal biometry meas...
2210.00891
Enzo Tartaglione
Enzo Tartaglione
Information Removal at the bottleneck in Deep Neural Networks
null
null
null
null
cs.LG cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Deep learning models are nowadays broadly deployed to solve an incredibly large variety of tasks. Commonly, leveraging over the availability of "big data", deep neural networks are trained as black-boxes, minimizing an objective function at its output. This however does not allow control over the propagation of some ...
[ { "created": "Fri, 30 Sep 2022 14:20:21 GMT", "version": "v1" } ]
2022-10-04
[ [ "Tartaglione", "Enzo", "" ] ]
Deep learning models are nowadays broadly deployed to solve an incredibly large variety of tasks. Commonly, leveraging over the availability of "big data", deep neural networks are trained as black-boxes, minimizing an objective function at its output. This however does not allow control over the propagation of some sp...
1004.3566
Vishal Goyal
G. Murugesan, C. Chellappan
An Economic-based Resource Management and Scheduling for Grid Computing Applications
International Journal of Computer Science Issues online at http://ijcsi.org/articles/An-Economic-based-Resource-Management-and-Scheduling-for-Grid-Computing-Applications.php
IJCSI, Volume 7, Issue 2, March 2010
null
null
cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Resource management and scheduling plays a crucial role in achieving high utilization of resources in grid computing environments. Due to heterogeneity of resources, scheduling an application is significantly complicated and challenging task in grid system. Most of the researches in this area are mainly focused on to...
[ { "created": "Tue, 20 Apr 2010 20:32:31 GMT", "version": "v1" } ]
2010-04-22
[ [ "Murugesan", "G.", "" ], [ "Chellappan", "C.", "" ] ]
Resource management and scheduling plays a crucial role in achieving high utilization of resources in grid computing environments. Due to heterogeneity of resources, scheduling an application is significantly complicated and challenging task in grid system. Most of the researches in this area are mainly focused on to i...
1912.12220
Do\u{g}analp Ergen\c{c}
Do\u{g}analp Ergen\c{c} and Ertan Onur
On Network Traffic Forecasting using Autoregressive Models
null
null
null
null
cs.NI eess.SP
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Various statistical analysis methods are studied for years to extract accurate trends of network traffic and predict the future load mainly to allocate required resources. Besides, many stochastic modeling techniques are offered to represent fundamental characteristics of different types of network traffic. In this s...
[ { "created": "Fri, 27 Dec 2019 16:26:25 GMT", "version": "v1" } ]
2019-12-30
[ [ "Ergenç", "Doğanalp", "" ], [ "Onur", "Ertan", "" ] ]
Various statistical analysis methods are studied for years to extract accurate trends of network traffic and predict the future load mainly to allocate required resources. Besides, many stochastic modeling techniques are offered to represent fundamental characteristics of different types of network traffic. In this stu...
2003.13165
Balakumar Sundaralingam
Balakumar Sundaralingam and Tucker Hermans
In-Hand Object-Dynamics Inference using Tactile Fingertips
Accepted at IEEE Transactions on Robotics (T-RO). Website: https://sites.google.com/view/tactile-obj-dynamics
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Having the ability to estimate an object's properties through interaction will enable robots to manipulate novel objects. Object's dynamics, specifically the friction and inertial parameters have only been estimated in a lab environment with precise and often external sensing. Could we infer an object's dynamics in t...
[ { "created": "Mon, 30 Mar 2020 00:12:11 GMT", "version": "v1" }, { "created": "Tue, 19 Jan 2021 04:37:38 GMT", "version": "v2" } ]
2021-01-20
[ [ "Sundaralingam", "Balakumar", "" ], [ "Hermans", "Tucker", "" ] ]
Having the ability to estimate an object's properties through interaction will enable robots to manipulate novel objects. Object's dynamics, specifically the friction and inertial parameters have only been estimated in a lab environment with precise and often external sensing. Could we infer an object's dynamics in the...
2302.07832
Aodong Li
Aodong Li, Chen Qiu, Marius Kloft, Padhraic Smyth, Stephan Mandt, Maja Rudolph
Deep Anomaly Detection under Labeling Budget Constraints
ICML 2023
null
null
null
cs.LG cs.AI
http://creativecommons.org/licenses/by/4.0/
Selecting informative data points for expert feedback can significantly improve the performance of anomaly detection (AD) in various contexts, such as medical diagnostics or fraud detection. In this paper, we determine a set of theoretical conditions under which anomaly scores generalize from labeled queries to unlab...
[ { "created": "Wed, 15 Feb 2023 18:18:35 GMT", "version": "v1" }, { "created": "Tue, 4 Jul 2023 18:33:10 GMT", "version": "v2" } ]
2023-07-06
[ [ "Li", "Aodong", "" ], [ "Qiu", "Chen", "" ], [ "Kloft", "Marius", "" ], [ "Smyth", "Padhraic", "" ], [ "Mandt", "Stephan", "" ], [ "Rudolph", "Maja", "" ] ]
Selecting informative data points for expert feedback can significantly improve the performance of anomaly detection (AD) in various contexts, such as medical diagnostics or fraud detection. In this paper, we determine a set of theoretical conditions under which anomaly scores generalize from labeled queries to unlabel...
1706.02337
Xiao Yang
Xiao Yang, Ersin Yumer, Paul Asente, Mike Kraley, Daniel Kifer, C. Lee Giles
Learning to Extract Semantic Structure from Documents Using Multimodal Fully Convolutional Neural Network
CVPR 2017 Spotlight
null
null
null
cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present an end-to-end, multimodal, fully convolutional network for extracting semantic structures from document images. We consider document semantic structure extraction as a pixel-wise segmentation task, and propose a unified model that classifies pixels based not only on their visual appearance, as in the tradi...
[ { "created": "Wed, 7 Jun 2017 18:51:31 GMT", "version": "v1" } ]
2017-06-09
[ [ "Yang", "Xiao", "" ], [ "Yumer", "Ersin", "" ], [ "Asente", "Paul", "" ], [ "Kraley", "Mike", "" ], [ "Kifer", "Daniel", "" ], [ "Giles", "C. Lee", "" ] ]
We present an end-to-end, multimodal, fully convolutional network for extracting semantic structures from document images. We consider document semantic structure extraction as a pixel-wise segmentation task, and propose a unified model that classifies pixels based not only on their visual appearance, as in the traditi...
2403.02308
Yuchen Duan
Yuchen Duan, Weiyun Wang, Zhe Chen, Xizhou Zhu, Lewei Lu, Tong Lu, Yu Qiao, Hongsheng Li, Jifeng Dai, Wenhai Wang
Vision-RWKV: Efficient and Scalable Visual Perception with RWKV-Like Architectures
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Transformers have revolutionized computer vision and natural language processing, but their high computational complexity limits their application in high-resolution image processing and long-context analysis. This paper introduces Vision-RWKV (VRWKV), a model adapted from the RWKV model used in the NLP field with ne...
[ { "created": "Mon, 4 Mar 2024 18:46:20 GMT", "version": "v1" }, { "created": "Thu, 7 Mar 2024 15:43:08 GMT", "version": "v2" } ]
2024-03-08
[ [ "Duan", "Yuchen", "" ], [ "Wang", "Weiyun", "" ], [ "Chen", "Zhe", "" ], [ "Zhu", "Xizhou", "" ], [ "Lu", "Lewei", "" ], [ "Lu", "Tong", "" ], [ "Qiao", "Yu", "" ], [ "Li", "Hongsheng", "" ...
Transformers have revolutionized computer vision and natural language processing, but their high computational complexity limits their application in high-resolution image processing and long-context analysis. This paper introduces Vision-RWKV (VRWKV), a model adapted from the RWKV model used in the NLP field with nece...
2407.00024
Lang He Ph.D
Lang He, Kai Chen, Junnan Zhao, Yimeng Wang, Ercheng Pei, Haifeng Chen, Jiewei Jiang, Shiqing Zhang, Jie Zhang, Zhongmin Wang, Tao He, Prayag Tiwari
LMVD: A Large-Scale Multimodal Vlog Dataset for Depression Detection in the Wild
null
null
null
null
cs.CV cs.AI cs.MM
http://creativecommons.org/licenses/by-nc-nd/4.0/
Depression can significantly impact many aspects of an individual's life, including their personal and social functioning, academic and work performance, and overall quality of life. Many researchers within the field of affective computing are adopting deep learning technology to explore potential patterns related to...
[ { "created": "Thu, 9 May 2024 01:27:10 GMT", "version": "v1" } ]
2024-07-02
[ [ "He", "Lang", "" ], [ "Chen", "Kai", "" ], [ "Zhao", "Junnan", "" ], [ "Wang", "Yimeng", "" ], [ "Pei", "Ercheng", "" ], [ "Chen", "Haifeng", "" ], [ "Jiang", "Jiewei", "" ], [ "Zhang", "Shiqing...
Depression can significantly impact many aspects of an individual's life, including their personal and social functioning, academic and work performance, and overall quality of life. Many researchers within the field of affective computing are adopting deep learning technology to explore potential patterns related to t...
1812.02615
Muhammad Junaid Farooq
Jin Shang and Muhammad Junaid Farooq and Quanyan Zhu
Real-Time Transmission Mechanism Design for Wireless IoT Sensors with Energy Harvesting under Power Saving Mode
null
null
null
null
cs.SY eess.SP
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The Internet of things (IoT) comprises of wireless sensors and actuators connected via access points to the Internet. Often, the sensing devices are remotely deployed with limited battery power and are equipped with energy harvesting equipment. These devices transmit real-time data to the base station (BS), which is ...
[ { "created": "Thu, 6 Dec 2018 15:46:04 GMT", "version": "v1" }, { "created": "Wed, 30 Jan 2019 17:02:29 GMT", "version": "v2" }, { "created": "Mon, 8 Apr 2019 17:28:31 GMT", "version": "v3" } ]
2019-04-09
[ [ "Shang", "Jin", "" ], [ "Farooq", "Muhammad Junaid", "" ], [ "Zhu", "Quanyan", "" ] ]
The Internet of things (IoT) comprises of wireless sensors and actuators connected via access points to the Internet. Often, the sensing devices are remotely deployed with limited battery power and are equipped with energy harvesting equipment. These devices transmit real-time data to the base station (BS), which is us...
1803.11256
Alexander Kott
Alexander Kott
Challenges and Characteristics of Intelligent Autonomy for Internet of Battle Things in Highly Adversarial Environments
This is a version of the paper that was presented at, and will appear in the Proceedings of the 2018 Spring Symposium of AAAI, March 26-28, 2018, Palo Alto, CA
null
null
null
cs.CY cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Numerous, artificially intelligent, networked things will populate the battlefield of the future, operating in close collaboration with human warfighters, and fighting as teams in highly adversarial environments. This paper explores the characteristics, capabilities and intelligence required of such a network of inte...
[ { "created": "Tue, 20 Mar 2018 22:15:14 GMT", "version": "v1" }, { "created": "Fri, 13 Apr 2018 19:36:14 GMT", "version": "v2" } ]
2018-04-17
[ [ "Kott", "Alexander", "" ] ]
Numerous, artificially intelligent, networked things will populate the battlefield of the future, operating in close collaboration with human warfighters, and fighting as teams in highly adversarial environments. This paper explores the characteristics, capabilities and intelligence required of such a network of intell...
2303.09187
Zhongwei Qiu
Zhongwei Qiu, Yang Qiansheng, Jian Wang, Haocheng Feng, Junyu Han, Errui Ding, Chang Xu, Dongmei Fu, Jingdong Wang
PSVT: End-to-End Multi-person 3D Pose and Shape Estimation with Progressive Video Transformers
CVPR2023
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Existing methods of multi-person video 3D human Pose and Shape Estimation (PSE) typically adopt a two-stage strategy, which first detects human instances in each frame and then performs single-person PSE with temporal model. However, the global spatio-temporal context among spatial instances can not be captured. In t...
[ { "created": "Thu, 16 Mar 2023 09:55:43 GMT", "version": "v1" } ]
2023-03-17
[ [ "Qiu", "Zhongwei", "" ], [ "Qiansheng", "Yang", "" ], [ "Wang", "Jian", "" ], [ "Feng", "Haocheng", "" ], [ "Han", "Junyu", "" ], [ "Ding", "Errui", "" ], [ "Xu", "Chang", "" ], [ "Fu", "Dongmei...
Existing methods of multi-person video 3D human Pose and Shape Estimation (PSE) typically adopt a two-stage strategy, which first detects human instances in each frame and then performs single-person PSE with temporal model. However, the global spatio-temporal context among spatial instances can not be captured. In thi...
2405.03251
Zhenmei Shi
Jiuxiang Gu, Chenyang Li, Yingyu Liang, Zhenmei Shi, Zhao Song
Exploring the Frontiers of Softmax: Provable Optimization, Applications in Diffusion Model, and Beyond
53 pages
null
null
null
cs.LG cs.AI
http://creativecommons.org/licenses/by-nc-sa/4.0/
The softmax activation function plays a crucial role in the success of large language models (LLMs), particularly in the self-attention mechanism of the widely adopted Transformer architecture. However, the underlying learning dynamics that contribute to the effectiveness of softmax remain largely unexplored. As a st...
[ { "created": "Mon, 6 May 2024 08:15:29 GMT", "version": "v1" } ]
2024-05-07
[ [ "Gu", "Jiuxiang", "" ], [ "Li", "Chenyang", "" ], [ "Liang", "Yingyu", "" ], [ "Shi", "Zhenmei", "" ], [ "Song", "Zhao", "" ] ]
The softmax activation function plays a crucial role in the success of large language models (LLMs), particularly in the self-attention mechanism of the widely adopted Transformer architecture. However, the underlying learning dynamics that contribute to the effectiveness of softmax remain largely unexplored. As a step...
2402.10102
Irina Ar\'evalo
Jose L. Salmeron and Irina Ar\'evalo
A privacy-preserving, distributed and cooperative FCM-based learning approach for Cancer Research
Rough Sets: International Joint Conference, IJCRS 2020
null
null
null
cs.AI cs.DC
http://creativecommons.org/licenses/by/4.0/
Distributed Artificial Intelligence is attracting interest day by day. In this paper, the authors introduce an innovative methodology for distributed learning of Particle Swarm Optimization-based Fuzzy Cognitive Maps in a privacy-preserving way. The authors design a training scheme for collaborative FCM learning that...
[ { "created": "Thu, 15 Feb 2024 16:56:25 GMT", "version": "v1" } ]
2024-02-16
[ [ "Salmeron", "Jose L.", "" ], [ "Arévalo", "Irina", "" ] ]
Distributed Artificial Intelligence is attracting interest day by day. In this paper, the authors introduce an innovative methodology for distributed learning of Particle Swarm Optimization-based Fuzzy Cognitive Maps in a privacy-preserving way. The authors design a training scheme for collaborative FCM learning that o...
2003.04470
Vuong M. Ngo
V.M. Ngo, N.A. Le-Khac, and M.T. Kechadi
Data Warehouse and Decision Support on Integrated Crop Big Data
13 pages, 11 figures. arXiv admin note: text overlap with arXiv:1905.12411
International Journal of Business Process Integration and Management 2020 Vol.10 No.1
10.1504/IJBPIM.2020.113115
null
cs.DB cs.DC cs.LG cs.PF
http://creativecommons.org/licenses/by/4.0/
In recent years, precision agriculture is becoming very popular. The introduction of modern information and communication technologies for collecting and processing Agricultural data revolutionise the agriculture practises. This has started a while ago (early 20th century) and it is driven by the low cost of collecti...
[ { "created": "Tue, 10 Mar 2020 00:10:22 GMT", "version": "v1" }, { "created": "Mon, 12 Apr 2021 08:45:11 GMT", "version": "v2" } ]
2021-04-13
[ [ "Ngo", "V. M.", "" ], [ "Le-Khac", "N. A.", "" ], [ "Kechadi", "M. T.", "" ] ]
In recent years, precision agriculture is becoming very popular. The introduction of modern information and communication technologies for collecting and processing Agricultural data revolutionise the agriculture practises. This has started a while ago (early 20th century) and it is driven by the low cost of collecting...
1701.05013
Veronika Cheplygina
Veronika Cheplygina, Isabel Pino Pe\~na, Jesper Holst Pedersen, David A. Lynch, Lauge S{\o}rensen, Marleen de Bruijne
Transfer learning for multi-center classification of chronic obstructive pulmonary disease
Accepted at Journal of Biomedical and Health Informatics
null
10.1109/JBHI.2017.2769800
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Chronic obstructive pulmonary disease (COPD) is a lung disease which can be quantified using chest computed tomography (CT) scans. Recent studies have shown that COPD can be automatically diagnosed using weakly supervised learning of intensity and texture distributions. However, up till now such classifiers have only...
[ { "created": "Wed, 18 Jan 2017 11:13:01 GMT", "version": "v1" }, { "created": "Thu, 23 Nov 2017 14:10:34 GMT", "version": "v2" } ]
2017-11-27
[ [ "Cheplygina", "Veronika", "" ], [ "Peña", "Isabel Pino", "" ], [ "Pedersen", "Jesper Holst", "" ], [ "Lynch", "David A.", "" ], [ "Sørensen", "Lauge", "" ], [ "de Bruijne", "Marleen", "" ] ]
Chronic obstructive pulmonary disease (COPD) is a lung disease which can be quantified using chest computed tomography (CT) scans. Recent studies have shown that COPD can be automatically diagnosed using weakly supervised learning of intensity and texture distributions. However, up till now such classifiers have only b...
2212.11122
Parviz Ali
Parviz Ali
Diamond Abrasive Electroplated Surface Anomaly Detection using Convolutional Neural Networks for Industrial Quality Inspection
null
null
null
null
cs.CV cs.LG
http://creativecommons.org/licenses/by/4.0/
Electroplated diamond abrasive tools require nickel coating on a metal surface for abrasive bonding and part functionality. The electroplated nickel-coated abrasive tool is expected to have a high-quality part performance by having a nickel coating thickness of between 50% to 60% of the abrasive median diameter, unif...
[ { "created": "Sun, 11 Dec 2022 20:14:18 GMT", "version": "v1" } ]
2022-12-22
[ [ "Ali", "Parviz", "" ] ]
Electroplated diamond abrasive tools require nickel coating on a metal surface for abrasive bonding and part functionality. The electroplated nickel-coated abrasive tool is expected to have a high-quality part performance by having a nickel coating thickness of between 50% to 60% of the abrasive median diameter, unifor...
1307.0214
Thijs Laarhoven
Thijs Laarhoven
Dynamic Traitor Tracing Schemes, Revisited
7 pages, 1 figure (6 subfigures), 1 table
IEEE Workshop on Information Forensics and Security (WIFS), pp. 191-196, 2013
10.1109/WIFS.2013.6707817
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We revisit recent results from the area of collusion-resistant traitor tracing, and show how they can be combined and improved to obtain more efficient dynamic traitor tracing schemes. In particular, we show how the dynamic Tardos scheme of Laarhoven et al. can be combined with the optimized score functions of Ooster...
[ { "created": "Sun, 30 Jun 2013 15:55:11 GMT", "version": "v1" } ]
2016-11-17
[ [ "Laarhoven", "Thijs", "" ] ]
We revisit recent results from the area of collusion-resistant traitor tracing, and show how they can be combined and improved to obtain more efficient dynamic traitor tracing schemes. In particular, we show how the dynamic Tardos scheme of Laarhoven et al. can be combined with the optimized score functions of Oosterwi...
1509.00721
Andrey Shchurov
Andrey A. Shchurov
A Multilayer Model of Computer Networks
5 pages, 4 figures. ISSN:2231-2803
International Journal of Computer Trends and Technology (IJCTT) V26(1):12-16, August 2015
10.14445/22312803/IJCTT-V26P103
null
cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The fundamental concept of applying the system methodology to network analysis declares that network architecture should take into account services and applications which this network provides and supports. This work introduces a formal model of computer networks on the basis of the hierarchical multilayer networks. ...
[ { "created": "Wed, 2 Sep 2015 14:34:53 GMT", "version": "v1" } ]
2015-09-03
[ [ "Shchurov", "Andrey A.", "" ] ]
The fundamental concept of applying the system methodology to network analysis declares that network architecture should take into account services and applications which this network provides and supports. This work introduces a formal model of computer networks on the basis of the hierarchical multilayer networks. In...
1811.00753
Kartik Ahuja
Kartik Ahuja, Mihaela van der Schaar
Risk-Stratify: Confident Stratification Of Patients Based On Risk
null
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A clinician desires to use a risk-stratification method that achieves confident risk-stratification - the risk estimates of the different patients reflect the true risks with a high probability. This allows him/her to use these risks to make accurate predictions about prognosis and decisions about screening, treatmen...
[ { "created": "Fri, 2 Nov 2018 06:30:52 GMT", "version": "v1" } ]
2018-11-05
[ [ "Ahuja", "Kartik", "" ], [ "van der Schaar", "Mihaela", "" ] ]
A clinician desires to use a risk-stratification method that achieves confident risk-stratification - the risk estimates of the different patients reflect the true risks with a high probability. This allows him/her to use these risks to make accurate predictions about prognosis and decisions about screening, treatments...
1812.03615
Isuru Godage
Jiahao Deng, Brandon H. Meng, Iyad Kanj, Isuru S. Godage
Near-optimal Smooth Path Planning for Multisection Continuum Arms
Submitted to 2019 IEEE International Conference on Soft Robotics (RoboSoft 2019)
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We study the path planning problem for continuum-arm robots, in which we are given a starting and an end point, and we need to compute a path for the tip of the continuum arm between the two points. We consider both cases where obstacles are present and where they are not. We demonstrate how to leverage the continuum...
[ { "created": "Mon, 10 Dec 2018 04:00:27 GMT", "version": "v1" } ]
2018-12-11
[ [ "Deng", "Jiahao", "" ], [ "Meng", "Brandon H.", "" ], [ "Kanj", "Iyad", "" ], [ "Godage", "Isuru S.", "" ] ]
We study the path planning problem for continuum-arm robots, in which we are given a starting and an end point, and we need to compute a path for the tip of the continuum arm between the two points. We consider both cases where obstacles are present and where they are not. We demonstrate how to leverage the continuum a...
1011.6030
Bernard Cousin
Shadi Jawhar (IRISA), Bernard Cousin (IRISA)
Optical Multicast Routing Under Light Splitter Constraints
null
7th International Conference on Information Technology : New Generations (ITNG 2010), Las Vegas : United States (2010)
10.1109/ITNG.2010.168
null
cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
During the past few years, we have observed the emergence of new applications that use multicast transmission. For a multicast routing algorithm to be applicable in optical networks, it must route data only to group members, optimize and maintain loop-free routes, and concentrate the routes on a subset of network lin...
[ { "created": "Sun, 28 Nov 2010 11:04:01 GMT", "version": "v1" } ]
2010-11-30
[ [ "Jawhar", "Shadi", "", "IRISA" ], [ "Cousin", "Bernard", "", "IRISA" ] ]
During the past few years, we have observed the emergence of new applications that use multicast transmission. For a multicast routing algorithm to be applicable in optical networks, it must route data only to group members, optimize and maintain loop-free routes, and concentrate the routes on a subset of network links...
2012.04733
Jiaqi Wang
Jiaqi Wang, Kai Chen, Rui Xu, Ziwei Liu, Chen Change Loy, Dahua Lin
CARAFE++: Unified Content-Aware ReAssembly of FEatures
Technical Report. Extended journal version of the conference paper that appeared as arXiv:1905.02188
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Feature reassembly, i.e. feature downsampling and upsampling, is a key operation in a number of modern convolutional network architectures, e.g., residual networks and feature pyramids. Its design is critical for dense prediction tasks such as object detection and semantic/instance segmentation. In this work, we prop...
[ { "created": "Mon, 7 Dec 2020 07:34:57 GMT", "version": "v1" } ]
2020-12-10
[ [ "Wang", "Jiaqi", "" ], [ "Chen", "Kai", "" ], [ "Xu", "Rui", "" ], [ "Liu", "Ziwei", "" ], [ "Loy", "Chen Change", "" ], [ "Lin", "Dahua", "" ] ]
Feature reassembly, i.e. feature downsampling and upsampling, is a key operation in a number of modern convolutional network architectures, e.g., residual networks and feature pyramids. Its design is critical for dense prediction tasks such as object detection and semantic/instance segmentation. In this work, we propos...
1903.02639
Keegan Lensink
Eldad Haber, Keegan Lensink, Eran Treister, Lars Ruthotto
IMEXnet: A Forward Stable Deep Neural Network
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Deep convolutional neural networks have revolutionized many machine learning and computer vision tasks, however, some remaining key challenges limit their wider use. These challenges include improving the network's robustness to perturbations of the input image and the limited ``field of view'' of convolution operato...
[ { "created": "Wed, 6 Mar 2019 22:33:06 GMT", "version": "v1" }, { "created": "Fri, 17 May 2019 21:45:28 GMT", "version": "v2" } ]
2019-05-21
[ [ "Haber", "Eldad", "" ], [ "Lensink", "Keegan", "" ], [ "Treister", "Eran", "" ], [ "Ruthotto", "Lars", "" ] ]
Deep convolutional neural networks have revolutionized many machine learning and computer vision tasks, however, some remaining key challenges limit their wider use. These challenges include improving the network's robustness to perturbations of the input image and the limited ``field of view'' of convolution operators...
2404.14779
Cl\'ement Christophe
Cl\'ement Christophe, Praveen K Kanithi, Prateek Munjal, Tathagata Raha, Nasir Hayat, Ronnie Rajan, Ahmed Al-Mahrooqi, Avani Gupta, Muhammad Umar Salman, Gurpreet Gosal, Bhargav Kanakiya, Charles Chen, Natalia Vassilieva, Boulbaba Ben Amor, Marco AF Pimentel, Shadab Khan
Med42 -- Evaluating Fine-Tuning Strategies for Medical LLMs: Full-Parameter vs. Parameter-Efficient Approaches
Published at AAAI 2024 Spring Symposium - Clinical Foundation Models
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
This study presents a comprehensive analysis and comparison of two predominant fine-tuning methodologies - full-parameter fine-tuning and parameter-efficient tuning - within the context of medical Large Language Models (LLMs). We developed and refined a series of LLMs, based on the Llama-2 architecture, specifically ...
[ { "created": "Tue, 23 Apr 2024 06:36:21 GMT", "version": "v1" } ]
2024-04-24
[ [ "Christophe", "Clément", "" ], [ "Kanithi", "Praveen K", "" ], [ "Munjal", "Prateek", "" ], [ "Raha", "Tathagata", "" ], [ "Hayat", "Nasir", "" ], [ "Rajan", "Ronnie", "" ], [ "Al-Mahrooqi", "Ahmed", "" ]...
This study presents a comprehensive analysis and comparison of two predominant fine-tuning methodologies - full-parameter fine-tuning and parameter-efficient tuning - within the context of medical Large Language Models (LLMs). We developed and refined a series of LLMs, based on the Llama-2 architecture, specifically de...
1812.03304
Peiyao Shen
Peiyao Shen, Xuebo Zhang and Yongchun Fang
Real-time Acceleration-continuous Path-constrained Trajectory Planning With Built-in Tradability Between Cruise and Time-optimal Motions
12 pages, 19 figures
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, a novel real-time acceleration-continuous path-constrained trajectory planning algorithm is proposed with an appealing built-in tradability mechanism between cruise motion and time-optimal motion. Different from existing approaches, the proposed approach smoothens time-optimal trajectories with bang-ba...
[ { "created": "Sat, 8 Dec 2018 12:02:49 GMT", "version": "v1" } ]
2018-12-11
[ [ "Shen", "Peiyao", "" ], [ "Zhang", "Xuebo", "" ], [ "Fang", "Yongchun", "" ] ]
In this paper, a novel real-time acceleration-continuous path-constrained trajectory planning algorithm is proposed with an appealing built-in tradability mechanism between cruise motion and time-optimal motion. Different from existing approaches, the proposed approach smoothens time-optimal trajectories with bang-bang...