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2312.02051
Shuhuai Ren
Shuhuai Ren, Linli Yao, Shicheng Li, Xu Sun, Lu Hou
TimeChat: A Time-sensitive Multimodal Large Language Model for Long Video Understanding
CVPR 2024 camera-ready version, code is available at https://github.com/RenShuhuai-Andy/TimeChat
null
null
null
cs.CV cs.AI cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This work proposes TimeChat, a time-sensitive multimodal large language model specifically designed for long video understanding. Our model incorporates two key architectural contributions: (1) a timestamp-aware frame encoder that binds visual content with the timestamp of each frame, and (2) a sliding video Q-Former...
[ { "created": "Mon, 4 Dec 2023 17:09:52 GMT", "version": "v1" }, { "created": "Thu, 28 Mar 2024 12:41:14 GMT", "version": "v2" } ]
2024-03-29
[ [ "Ren", "Shuhuai", "" ], [ "Yao", "Linli", "" ], [ "Li", "Shicheng", "" ], [ "Sun", "Xu", "" ], [ "Hou", "Lu", "" ] ]
This work proposes TimeChat, a time-sensitive multimodal large language model specifically designed for long video understanding. Our model incorporates two key architectural contributions: (1) a timestamp-aware frame encoder that binds visual content with the timestamp of each frame, and (2) a sliding video Q-Former t...
2202.04270
Kenjiro Tadakuma
Tomoya Takahashi, Masahiro Watanabe, Kenjiro Tadakuma, Naoto Saiki, Kazuki Abe Masashi Konyo and Satoshi Tadokoro
Inflated Bendable Eversion Cantilever Mechanism with Inner Skeleton for Increased Payload Holding
This article is consist of 8 pages and 15 figures
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Inflatable structures used in soft robotics applications exhibit unique characteristics. In particular, the tip-extension structure, which grows from the tip, can grow without friction against the environment. However, these inflatable structures are inferior to rigid mechanisms in terms of their load-bearing capacit...
[ { "created": "Wed, 9 Feb 2022 04:35:40 GMT", "version": "v1" } ]
2022-02-10
[ [ "Takahashi", "Tomoya", "" ], [ "Watanabe", "Masahiro", "" ], [ "Tadakuma", "Kenjiro", "" ], [ "Saiki", "Naoto", "" ], [ "Konyo", "Kazuki Abe Masashi", "" ], [ "Tadokoro", "Satoshi", "" ] ]
Inflatable structures used in soft robotics applications exhibit unique characteristics. In particular, the tip-extension structure, which grows from the tip, can grow without friction against the environment. However, these inflatable structures are inferior to rigid mechanisms in terms of their load-bearing capacity....
2306.09848
Ege Gursoy
Ege Gursoy, Sonny Tarbouriech, Andrea Cherubini
Can robots mold soft plastic materials by shaping depth images?
Accepted to IEEE Transactions on Robotics (T-RO)
null
null
null
cs.RO
http://creativecommons.org/licenses/by/4.0/
Can robots mold soft plastic materials by shaping depth images? The short answer is no: current day robots can't. In this article, we address the problem of shaping plastic material with an anthropomorphic arm/hand robot, which observes the material with a fixed depth camera. Robots capable of molding could assist hu...
[ { "created": "Fri, 16 Jun 2023 13:46:15 GMT", "version": "v1" } ]
2023-06-19
[ [ "Gursoy", "Ege", "" ], [ "Tarbouriech", "Sonny", "" ], [ "Cherubini", "Andrea", "" ] ]
Can robots mold soft plastic materials by shaping depth images? The short answer is no: current day robots can't. In this article, we address the problem of shaping plastic material with an anthropomorphic arm/hand robot, which observes the material with a fixed depth camera. Robots capable of molding could assist huma...
1305.3102
Bart M. P. Jansen
Michael R. Fellows and Bart M. P. Jansen
FPT is Characterized by Useful Obstruction Sets
Extended abstract with appendix, as accepted to WG 2013
null
null
null
cs.CC cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Many graph problems were first shown to be fixed-parameter tractable using the results of Robertson and Seymour on graph minors. We show that the combination of finite, computable, obstruction sets and efficient order tests is not just one way of obtaining strongly uniform FPT algorithms, but that all of FPT may be c...
[ { "created": "Tue, 14 May 2013 10:43:00 GMT", "version": "v1" } ]
2013-05-15
[ [ "Fellows", "Michael R.", "" ], [ "Jansen", "Bart M. P.", "" ] ]
Many graph problems were first shown to be fixed-parameter tractable using the results of Robertson and Seymour on graph minors. We show that the combination of finite, computable, obstruction sets and efficient order tests is not just one way of obtaining strongly uniform FPT algorithms, but that all of FPT may be cap...
2205.08820
Antonio Longa
Antonio Longa, Giulia Cencetti, Sune Lehmann, Andrea Passerini and Bruno Lepri
Generating fine-grained surrogate temporal networks
null
null
null
null
cs.SI cs.CY physics.data-an physics.soc-ph
http://creativecommons.org/licenses/by/4.0/
Temporal networks are essential for modeling and understanding systems whose behavior varies in time, from social interactions to biological systems. Often, however, real-world data are prohibitively expensive to collect in a large scale or unshareable due to privacy concerns. A promising way to bypass the problem co...
[ { "created": "Wed, 18 May 2022 09:38:22 GMT", "version": "v1" }, { "created": "Tue, 22 Aug 2023 17:35:58 GMT", "version": "v2" } ]
2023-08-23
[ [ "Longa", "Antonio", "" ], [ "Cencetti", "Giulia", "" ], [ "Lehmann", "Sune", "" ], [ "Passerini", "Andrea", "" ], [ "Lepri", "Bruno", "" ] ]
Temporal networks are essential for modeling and understanding systems whose behavior varies in time, from social interactions to biological systems. Often, however, real-world data are prohibitively expensive to collect in a large scale or unshareable due to privacy concerns. A promising way to bypass the problem cons...
2309.05352
Rohan V Kashyap
Pavan Karjol, Rohan Kashyap, Prathosh A P
Neural Discovery of Permutation Subgroups
null
In International Conference on Artificial Intelligence and Statistics, pp. 4668-4678. Volume 206. PMLR, 2023
null
null
cs.LG
http://creativecommons.org/licenses/by/4.0/
We consider the problem of discovering subgroup $H$ of permutation group $S_{n}$. Unlike the traditional $H$-invariant networks wherein $H$ is assumed to be known, we present a method to discover the underlying subgroup, given that it satisfies certain conditions. Our results show that one could discover any subgroup...
[ { "created": "Mon, 11 Sep 2023 09:53:28 GMT", "version": "v1" } ]
2023-09-12
[ [ "Karjol", "Pavan", "" ], [ "Kashyap", "Rohan", "" ], [ "P", "Prathosh A", "" ] ]
We consider the problem of discovering subgroup $H$ of permutation group $S_{n}$. Unlike the traditional $H$-invariant networks wherein $H$ is assumed to be known, we present a method to discover the underlying subgroup, given that it satisfies certain conditions. Our results show that one could discover any subgroup o...
2303.10991
Jinyoung Jun
Jinyoung Jun, Jae-Han Lee, and Chang-Su Kim
Versatile Depth Estimator Based on Common Relative Depth Estimation and Camera-Specific Relative-to-Metric Depth Conversion
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A typical monocular depth estimator is trained for a single camera, so its performance drops severely on images taken with different cameras. To address this issue, we propose a versatile depth estimator (VDE), composed of a common relative depth estimator (CRDE) and multiple relative-to-metric converters (R2MCs). Th...
[ { "created": "Mon, 20 Mar 2023 10:19:50 GMT", "version": "v1" } ]
2023-03-21
[ [ "Jun", "Jinyoung", "" ], [ "Lee", "Jae-Han", "" ], [ "Kim", "Chang-Su", "" ] ]
A typical monocular depth estimator is trained for a single camera, so its performance drops severely on images taken with different cameras. To address this issue, we propose a versatile depth estimator (VDE), composed of a common relative depth estimator (CRDE) and multiple relative-to-metric converters (R2MCs). The ...
2309.04782
Feng Zhou
Feng Zhou, Antonio Cicone, Haomin Zhou
RRCNN$^{+}$: An Enhanced Residual Recursive Convolutional Neural Network for Non-stationary Signal Decomposition
8 pages, 4 figure
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Time-frequency analysis is an important and challenging task in many applications. Fourier and wavelet analysis are two classic methods that have achieved remarkable success in many fields. They also exhibit limitations when applied to nonlinear and non-stationary signals. To address this challenge, a series of nonli...
[ { "created": "Sat, 9 Sep 2023 13:00:30 GMT", "version": "v1" } ]
2023-09-12
[ [ "Zhou", "Feng", "" ], [ "Cicone", "Antonio", "" ], [ "Zhou", "Haomin", "" ] ]
Time-frequency analysis is an important and challenging task in many applications. Fourier and wavelet analysis are two classic methods that have achieved remarkable success in many fields. They also exhibit limitations when applied to nonlinear and non-stationary signals. To address this challenge, a series of nonline...
2311.18495
Avery Ma
Avery Ma, Amir-massoud Farahmand, Yangchen Pan, Philip Torr, Jindong Gu
Improving Adversarial Transferability via Model Alignment
Accepted at the European Conference on Computer Vision (ECCV) 2024. Code: https://github.com/averyma/model-alignment
null
null
null
cs.LG cs.CV
http://creativecommons.org/licenses/by/4.0/
Neural networks are susceptible to adversarial perturbations that are transferable across different models. In this paper, we introduce a novel model alignment technique aimed at improving a given source model's ability in generating transferable adversarial perturbations. During the alignment process, the parameters...
[ { "created": "Thu, 30 Nov 2023 12:15:49 GMT", "version": "v1" }, { "created": "Wed, 17 Jul 2024 11:45:09 GMT", "version": "v2" } ]
2024-07-18
[ [ "Ma", "Avery", "" ], [ "Farahmand", "Amir-massoud", "" ], [ "Pan", "Yangchen", "" ], [ "Torr", "Philip", "" ], [ "Gu", "Jindong", "" ] ]
Neural networks are susceptible to adversarial perturbations that are transferable across different models. In this paper, we introduce a novel model alignment technique aimed at improving a given source model's ability in generating transferable adversarial perturbations. During the alignment process, the parameters o...
2102.08628
Essam Rashed
Essam A. Rashed, Sachiko Kodera, Hidenobu Shirakami, Ryotetsu Kawaguchi, Kazuhiro Watanabe, Akimasa Hirata
Knowledge discovery from emergency ambulance dispatch during COVID-19: A case study of Nagoya City, Japan
15 pages, 12 figures, 2 tables
Journal of Biomedical Informatics, 2021
10.1016/j.jbi.2021.103743
null
cs.AI eess.SP
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Accurate forecasting of medical service requirements is an important big data problem that is crucial for resource management in critical times such as natural disasters and pandemics. With the global spread of coronavirus disease 2019 (COVID-19), several concerns have been raised regarding the ability of medical sys...
[ { "created": "Wed, 17 Feb 2021 08:37:05 GMT", "version": "v1" } ]
2021-03-23
[ [ "Rashed", "Essam A.", "" ], [ "Kodera", "Sachiko", "" ], [ "Shirakami", "Hidenobu", "" ], [ "Kawaguchi", "Ryotetsu", "" ], [ "Watanabe", "Kazuhiro", "" ], [ "Hirata", "Akimasa", "" ] ]
Accurate forecasting of medical service requirements is an important big data problem that is crucial for resource management in critical times such as natural disasters and pandemics. With the global spread of coronavirus disease 2019 (COVID-19), several concerns have been raised regarding the ability of medical syste...
2312.10371
Wei Chen
Wei Chen, Gang Zhao, Xiaojin Zhang, Xiang Bai, Xuanjing Huang, Zhongyu Wei
K-ESConv: Knowledge Injection for Emotional Support Dialogue Systems via Prompt Learning
null
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Automatic psychological counseling requires mass of professional knowledge that can be found in online counseling forums. Motivated by this, we propose K-ESConv, a novel prompt learning based knowledge injection method for emotional support dialogue system, transferring forum knowledge to response generation. We eval...
[ { "created": "Sat, 16 Dec 2023 08:10:10 GMT", "version": "v1" } ]
2023-12-19
[ [ "Chen", "Wei", "" ], [ "Zhao", "Gang", "" ], [ "Zhang", "Xiaojin", "" ], [ "Bai", "Xiang", "" ], [ "Huang", "Xuanjing", "" ], [ "Wei", "Zhongyu", "" ] ]
Automatic psychological counseling requires mass of professional knowledge that can be found in online counseling forums. Motivated by this, we propose K-ESConv, a novel prompt learning based knowledge injection method for emotional support dialogue system, transferring forum knowledge to response generation. We evalua...
2405.00154
Aleksandr Katrutsa
Alexander Demin, Yuriy Dorn, Aleksandr Katrutsa, Daniil Kazantsev, Ilgam Latypov, Yulia Maximlyuk, Denis Ponomaryov
EEvA: Fast Expert-Based Algorithms for Buffer Page Replacement
null
null
null
null
cs.DB
http://creativecommons.org/licenses/by/4.0/
Optimal page replacement is an important problem in efficient buffer management. The range of replacement strategies known in the literature varies from simple but efficient FIFO-based algorithms to more accurate but potentially costly methods tailored to specific data access patterns. The principal issue in adopting...
[ { "created": "Tue, 30 Apr 2024 19:04:53 GMT", "version": "v1" } ]
2024-05-02
[ [ "Demin", "Alexander", "" ], [ "Dorn", "Yuriy", "" ], [ "Katrutsa", "Aleksandr", "" ], [ "Kazantsev", "Daniil", "" ], [ "Latypov", "Ilgam", "" ], [ "Maximlyuk", "Yulia", "" ], [ "Ponomaryov", "Denis", "" ]...
Optimal page replacement is an important problem in efficient buffer management. The range of replacement strategies known in the literature varies from simple but efficient FIFO-based algorithms to more accurate but potentially costly methods tailored to specific data access patterns. The principal issue in adopting a...
2403.10338
Priyanka Sukumaran
Priyanka Sukumaran, Conor Houghton, Nina Kazanina
Investigating grammatical abstraction in language models using few-shot learning of novel noun gender
EACL 2024; Findings of the Association for Computational Linguistics
null
null
null
cs.CL
http://creativecommons.org/licenses/by-sa/4.0/
Humans can learn a new word and infer its grammatical properties from very few examples. They have an abstract notion of linguistic properties like grammatical gender and agreement rules that can be applied to novel syntactic contexts and words. Drawing inspiration from psycholinguistics, we conduct a noun learning e...
[ { "created": "Fri, 15 Mar 2024 14:25:59 GMT", "version": "v1" } ]
2024-03-18
[ [ "Sukumaran", "Priyanka", "" ], [ "Houghton", "Conor", "" ], [ "Kazanina", "Nina", "" ] ]
Humans can learn a new word and infer its grammatical properties from very few examples. They have an abstract notion of linguistic properties like grammatical gender and agreement rules that can be applied to novel syntactic contexts and words. Drawing inspiration from psycholinguistics, we conduct a noun learning exp...
2003.10670
Xuesong Li
Xuesong Li, Jose Guivant, Subhan Khan
Real-time 3D object proposal generation and classification under limited processing resources
null
Robotics and Autonomous Systems, 130 (2020) 103557
10.1016/j.robot.2020.103557
2-s2.0-85084829367
cs.CV cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The task of detecting 3D objects is important to various robotic applications. The existing deep learning-based detection techniques have achieved impressive performance. However, these techniques are limited to run with a graphics processing unit (GPU) in a real-time environment. To achieve real-time 3D object detec...
[ { "created": "Tue, 24 Mar 2020 05:36:53 GMT", "version": "v1" } ]
2020-08-14
[ [ "Li", "Xuesong", "" ], [ "Guivant", "Jose", "" ], [ "Khan", "Subhan", "" ] ]
The task of detecting 3D objects is important to various robotic applications. The existing deep learning-based detection techniques have achieved impressive performance. However, these techniques are limited to run with a graphics processing unit (GPU) in a real-time environment. To achieve real-time 3D object detecti...
2310.15642
Andr\'e Silva
Nuno Saavedra, Andr\'e Silva, Martin Monperrus
GitBug-Actions: Building Reproducible Bug-Fix Benchmarks with GitHub Actions
Accepted to ICSE 2024 Demo
Proceedings of ICSE Tool, 2024
10.1145/3639478.3640023
null
cs.SE
http://creativecommons.org/licenses/by-sa/4.0/
Bug-fix benchmarks are fundamental in advancing various sub-fields of software engineering such as automatic program repair (APR) and fault localization (FL). A good benchmark must include recent examples that accurately reflect technologies and development practices of today. To be executable in the long term, a ben...
[ { "created": "Tue, 24 Oct 2023 09:04:14 GMT", "version": "v1" }, { "created": "Tue, 7 Nov 2023 13:25:08 GMT", "version": "v2" }, { "created": "Sun, 21 Jan 2024 12:01:33 GMT", "version": "v3" } ]
2024-03-15
[ [ "Saavedra", "Nuno", "" ], [ "Silva", "André", "" ], [ "Monperrus", "Martin", "" ] ]
Bug-fix benchmarks are fundamental in advancing various sub-fields of software engineering such as automatic program repair (APR) and fault localization (FL). A good benchmark must include recent examples that accurately reflect technologies and development practices of today. To be executable in the long term, a bench...
1507.02531
Robert Koenighofer
Roderick Bloem and Ruediger Ehlers and Robert Koenighofer
Cooperative Reactive Synthesis
18 pages, 3 figures. This is an extended version of [7], featuring an additional appendix
null
null
null
cs.LO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A modern approach to engineering correct-by-construction systems is to synthesize them automatically from formal specifications. Oftentimes, a system can only satisfy its guarantees if certain environment assumptions hold, which motivates their inclusion in the system specification. Experience with modern synthesis a...
[ { "created": "Thu, 9 Jul 2015 14:39:25 GMT", "version": "v1" } ]
2015-07-10
[ [ "Bloem", "Roderick", "" ], [ "Ehlers", "Ruediger", "" ], [ "Koenighofer", "Robert", "" ] ]
A modern approach to engineering correct-by-construction systems is to synthesize them automatically from formal specifications. Oftentimes, a system can only satisfy its guarantees if certain environment assumptions hold, which motivates their inclusion in the system specification. Experience with modern synthesis app...
2404.17094
Yufeng Li
Yufeng Li, Yiwei Ci, Qiusong Yang
TIUP: Effective Processor Verification with Tautology-Induced Universal Properties
Accepted by ASP-DAC 2024, please note that this is not the final camera-ready version
null
10.1109/ASP-DAC58780.2024.10473912.
null
cs.LO cs.AR cs.SY eess.SY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Design verification is a complex and costly task, especially for large and intricate processor projects. Formal verification techniques provide advantages by thoroughly examining design behaviors, but they require extensive labor and expertise in property formulation. Recent research focuses on verifying designs usin...
[ { "created": "Fri, 26 Apr 2024 01:05:36 GMT", "version": "v1" } ]
2024-04-29
[ [ "Li", "Yufeng", "" ], [ "Ci", "Yiwei", "" ], [ "Yang", "Qiusong", "" ] ]
Design verification is a complex and costly task, especially for large and intricate processor projects. Formal verification techniques provide advantages by thoroughly examining design behaviors, but they require extensive labor and expertise in property formulation. Recent research focuses on verifying designs using ...
2007.04118
Xiao Yang
Xiao Yang, Dingcheng Yang, Yinpeng Dong, Hang Su, Wenjian Yu, Jun Zhu
RobFR: Benchmarking Adversarial Robustness on Face Recognition
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Face recognition (FR) has recently made substantial progress and achieved high accuracy on standard benchmarks. However, it has raised security concerns in enormous FR applications because deep CNNs are unusually vulnerable to adversarial examples, and it is still lack of a comprehensive robustness evaluation before ...
[ { "created": "Wed, 8 Jul 2020 13:39:22 GMT", "version": "v1" }, { "created": "Wed, 29 Sep 2021 08:01:13 GMT", "version": "v2" } ]
2021-09-30
[ [ "Yang", "Xiao", "" ], [ "Yang", "Dingcheng", "" ], [ "Dong", "Yinpeng", "" ], [ "Su", "Hang", "" ], [ "Yu", "Wenjian", "" ], [ "Zhu", "Jun", "" ] ]
Face recognition (FR) has recently made substantial progress and achieved high accuracy on standard benchmarks. However, it has raised security concerns in enormous FR applications because deep CNNs are unusually vulnerable to adversarial examples, and it is still lack of a comprehensive robustness evaluation before a ...
1703.07387
Tamal Dey
Tamal K. Dey, Facundo Memoli, Yusu Wang
Topological Analysis of Nerves, Reeb Spaces, Mappers, and Multiscale Mappers
Full version of the paper appearing in International Symposium on Computational Geometry, 2017
null
null
null
cs.CG math.AT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Data analysis often concerns not only the space where data come from, but also various types of maps attached to data. In recent years, several related structures have been used to study maps on data, including Reeb spaces, mappers and multiscale mappers. The construction of these structures also relies on the so-cal...
[ { "created": "Tue, 21 Mar 2017 18:50:24 GMT", "version": "v1" } ]
2017-03-23
[ [ "Dey", "Tamal K.", "" ], [ "Memoli", "Facundo", "" ], [ "Wang", "Yusu", "" ] ]
Data analysis often concerns not only the space where data come from, but also various types of maps attached to data. In recent years, several related structures have been used to study maps on data, including Reeb spaces, mappers and multiscale mappers. The construction of these structures also relies on the so-calle...
1707.02000
Kamesh Madduri
Humayun Kabir, Kamesh Madduri
Shared-memory Graph Truss Decomposition
10 pages, conference submission
null
null
null
cs.DC cs.DS cs.SI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present PKT, a new shared-memory parallel algorithm and OpenMP implementation for the truss decomposition of large sparse graphs. A k-truss is a dense subgraph definition that can be considered a relaxation of a clique. Truss decomposition refers to a partitioning of all the edges in the graph based on their k-tru...
[ { "created": "Fri, 7 Jul 2017 00:09:09 GMT", "version": "v1" } ]
2017-07-10
[ [ "Kabir", "Humayun", "" ], [ "Madduri", "Kamesh", "" ] ]
We present PKT, a new shared-memory parallel algorithm and OpenMP implementation for the truss decomposition of large sparse graphs. A k-truss is a dense subgraph definition that can be considered a relaxation of a clique. Truss decomposition refers to a partitioning of all the edges in the graph based on their k-truss...
1907.07388
Samarth Manoj Brahmbhatt
Samarth Brahmbhatt, Charles C. Kemp and James Hays
Towards Markerless Grasp Capture
Third Workshop on Computer Vision for AR/VR, CVPR 2019
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Humans excel at grasping objects and manipulating them. Capturing human grasps is important for understanding grasping behavior and reconstructing it realistically in Virtual Reality (VR). However, grasp capture - capturing the pose of a hand grasping an object, and orienting it w.r.t. the object - is difficult becau...
[ { "created": "Wed, 17 Jul 2019 08:41:21 GMT", "version": "v1" } ]
2019-07-18
[ [ "Brahmbhatt", "Samarth", "" ], [ "Kemp", "Charles C.", "" ], [ "Hays", "James", "" ] ]
Humans excel at grasping objects and manipulating them. Capturing human grasps is important for understanding grasping behavior and reconstructing it realistically in Virtual Reality (VR). However, grasp capture - capturing the pose of a hand grasping an object, and orienting it w.r.t. the object - is difficult because...
2201.09536
Thang X. Vu
Thang X. Vu, Nicola Maturo, Symeon Chatzinotas, Joel Grotz, Tom Christophory, Bj\"orn Ottersten
Dynamic Bandwidth Allocation and Edge Caching Optimization for Nonlinear Content Delivery through Flexible Multibeam Satellites
Accepted to IEEE ICC 2022
null
null
null
cs.IT math.IT
http://creativecommons.org/licenses/by/4.0/
The next generation multibeam satellites open up a new way to design satellite communication channels with the full flexibility in bandwidth, transmit power and beam coverage management. In this paper, we exploit the flexible multibeam satellite capabilities and the geographical distribution of users to improve the p...
[ { "created": "Mon, 24 Jan 2022 09:07:41 GMT", "version": "v1" } ]
2022-01-25
[ [ "Vu", "Thang X.", "" ], [ "Maturo", "Nicola", "" ], [ "Chatzinotas", "Symeon", "" ], [ "Grotz", "Joel", "" ], [ "Christophory", "Tom", "" ], [ "Ottersten", "Björn", "" ] ]
The next generation multibeam satellites open up a new way to design satellite communication channels with the full flexibility in bandwidth, transmit power and beam coverage management. In this paper, we exploit the flexible multibeam satellite capabilities and the geographical distribution of users to improve the per...
2206.13773
Max Koster
Max Koster
On Relaxation of Dominant Sets
null
null
null
null
cs.DS cs.DM math.CO
http://creativecommons.org/licenses/by/4.0/
In a graph $G = (V,E)$, a k-ruling set $S$ is one in which all vertices $V$ \ $S$ are at most $k$ distance from $S$. Finding a minimum k-ruling set is intrinsically linked to the minimum dominating set problem and maximal independent set problem, which have been extensively studied in graph theory. This paper present...
[ { "created": "Tue, 28 Jun 2022 05:59:51 GMT", "version": "v1" } ]
2022-06-29
[ [ "Koster", "Max", "" ] ]
In a graph $G = (V,E)$, a k-ruling set $S$ is one in which all vertices $V$ \ $S$ are at most $k$ distance from $S$. Finding a minimum k-ruling set is intrinsically linked to the minimum dominating set problem and maximal independent set problem, which have been extensively studied in graph theory. This paper presents ...
2004.11992
Bram Wallace
Bram Wallace, Bharath Hariharan
Extending and Analyzing Self-Supervised Learning Across Domains
null
null
null
null
cs.CV cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Self-supervised representation learning has achieved impressive results in recent years, with experiments primarily coming on ImageNet or other similarly large internet imagery datasets. There has been little to no work with these methods on other smaller domains, such as satellite, textural, or biological imagery. W...
[ { "created": "Fri, 24 Apr 2020 21:18:02 GMT", "version": "v1" }, { "created": "Mon, 17 Aug 2020 16:13:46 GMT", "version": "v2" } ]
2020-08-18
[ [ "Wallace", "Bram", "" ], [ "Hariharan", "Bharath", "" ] ]
Self-supervised representation learning has achieved impressive results in recent years, with experiments primarily coming on ImageNet or other similarly large internet imagery datasets. There has been little to no work with these methods on other smaller domains, such as satellite, textural, or biological imagery. We ...
2110.00821
Elisa Claire Alem\'an Carre\'on
Elisa Claire Alem\'an Carre\'on and Hirofumi Nonaka and Toru Hiraoka
Relation Analysis between Hotel Review Rating Scores and Sentiment Analysis of Reviews by Chinese Tourists Visiting Japan
Translation of the original in Japanese
The Japanese Journal of the Institute of Industrial Applications Engineers (JJIIAE), 2018, Vol. 6, No. 2. pp. 95-99
10.12792/jjiiae.6.2.95
null
cs.IR
http://creativecommons.org/licenses/by-nc-sa/4.0/
In current times, the importance of online hotel review sites has become more and more apparent. Users of these sites reference of reviews strongly influences their purchase behavior and as such, reviews are important to companies and researchers alike. The majority of review sites offer both text reviews and numeric...
[ { "created": "Sat, 2 Oct 2021 15:07:46 GMT", "version": "v1" } ]
2021-10-05
[ [ "Carreón", "Elisa Claire Alemán", "" ], [ "Nonaka", "Hirofumi", "" ], [ "Hiraoka", "Toru", "" ] ]
In current times, the importance of online hotel review sites has become more and more apparent. Users of these sites reference of reviews strongly influences their purchase behavior and as such, reviews are important to companies and researchers alike. The majority of review sites offer both text reviews and numerical...
2107.07771
Yajing Sun
Yajing Sun, Yue Hu, Luxi Xing, Yuqiang Xie, Xiangpeng Wei
Know Deeper: Knowledge-Conversation Cyclic Utilization Mechanism for Open-domain Dialogue Generation
null
null
null
null
cs.CL cs.AI
http://creativecommons.org/licenses/by/4.0/
End-to-End intelligent neural dialogue systems suffer from the problems of generating inconsistent and repetitive responses. Existing dialogue models pay attention to unilaterally incorporating personal knowledge into the dialog while ignoring the fact that incorporating the personality-related conversation informati...
[ { "created": "Fri, 16 Jul 2021 08:59:06 GMT", "version": "v1" } ]
2021-07-19
[ [ "Sun", "Yajing", "" ], [ "Hu", "Yue", "" ], [ "Xing", "Luxi", "" ], [ "Xie", "Yuqiang", "" ], [ "Wei", "Xiangpeng", "" ] ]
End-to-End intelligent neural dialogue systems suffer from the problems of generating inconsistent and repetitive responses. Existing dialogue models pay attention to unilaterally incorporating personal knowledge into the dialog while ignoring the fact that incorporating the personality-related conversation information...
1708.05125
Feiyun Zhu
Feiyun Zhu
Hyperspectral Unmixing: Ground Truth Labeling, Datasets, Benchmark Performances and Survey
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Hyperspectral unmixing (HU) is a very useful and increasingly popular preprocessing step for a wide range of hyperspectral applications. However, the HU research has been constrained a lot by three factors: (a) the number of hyperspectral images (especially the ones with ground truths) are very limited; (b) the groun...
[ { "created": "Thu, 17 Aug 2017 03:35:02 GMT", "version": "v1" }, { "created": "Wed, 11 Oct 2017 16:22:06 GMT", "version": "v2" } ]
2017-10-12
[ [ "Zhu", "Feiyun", "" ] ]
Hyperspectral unmixing (HU) is a very useful and increasingly popular preprocessing step for a wide range of hyperspectral applications. However, the HU research has been constrained a lot by three factors: (a) the number of hyperspectral images (especially the ones with ground truths) are very limited; (b) the ground ...
2308.14404
Forouzan Farzinnejad
Forouzan Farzinnejad, Javad Rasti, Navid Khezrian, Jens Grubert
The Effect of an Exergame on the Shadow Play Skill Based on Muscle Memory for Young Female Participants: The Case of Forehand Drive in Table Tennis
9 pages, 6 figures, The 22nd IEEE International Symposium on Mixed and Augmented Reality (ISMAR)
null
null
null
cs.HC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Learning and practicing table tennis with traditional methods is a long, tedious process and may even lead to the internalization of incorrect techniques if not supervised by a coach. To overcome these issues, the presented study proposes an exergame with the aim of enhancing young female novice players' performance ...
[ { "created": "Mon, 28 Aug 2023 08:39:26 GMT", "version": "v1" } ]
2023-08-29
[ [ "Farzinnejad", "Forouzan", "" ], [ "Rasti", "Javad", "" ], [ "Khezrian", "Navid", "" ], [ "Grubert", "Jens", "" ] ]
Learning and practicing table tennis with traditional methods is a long, tedious process and may even lead to the internalization of incorrect techniques if not supervised by a coach. To overcome these issues, the presented study proposes an exergame with the aim of enhancing young female novice players' performance by...
2204.03503
Nicola Strisciuglio
Stefan Haller, Adina Aldea, Christin Seifert, Nicola Strisciuglio
Survey on Automated Short Answer Grading with Deep Learning: from Word Embeddings to Transformers
Under review
null
null
null
cs.CL cs.AI cs.LG
http://creativecommons.org/licenses/by/4.0/
Automated short answer grading (ASAG) has gained attention in education as a means to scale educational tasks to the growing number of students. Recent progress in Natural Language Processing and Machine Learning has largely influenced the field of ASAG, of which we survey the recent research advancements. We complem...
[ { "created": "Fri, 11 Mar 2022 13:47:08 GMT", "version": "v1" } ]
2022-04-08
[ [ "Haller", "Stefan", "" ], [ "Aldea", "Adina", "" ], [ "Seifert", "Christin", "" ], [ "Strisciuglio", "Nicola", "" ] ]
Automated short answer grading (ASAG) has gained attention in education as a means to scale educational tasks to the growing number of students. Recent progress in Natural Language Processing and Machine Learning has largely influenced the field of ASAG, of which we survey the recent research advancements. We complemen...
2202.05433
Jieyu Zhang
Jieyu Zhang, Cheng-Yu Hsieh, Yue Yu, Chao Zhang, Alexander Ratner
A Survey on Programmatic Weak Supervision
8 pages
null
null
null
cs.LG cs.AI stat.AP
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Labeling training data has become one of the major roadblocks to using machine learning. Among various weak supervision paradigms, programmatic weak supervision (PWS) has achieved remarkable success in easing the manual labeling bottleneck by programmatically synthesizing training labels from multiple potentially noi...
[ { "created": "Fri, 11 Feb 2022 04:05:38 GMT", "version": "v1" }, { "created": "Mon, 14 Feb 2022 05:45:58 GMT", "version": "v2" } ]
2022-02-15
[ [ "Zhang", "Jieyu", "" ], [ "Hsieh", "Cheng-Yu", "" ], [ "Yu", "Yue", "" ], [ "Zhang", "Chao", "" ], [ "Ratner", "Alexander", "" ] ]
Labeling training data has become one of the major roadblocks to using machine learning. Among various weak supervision paradigms, programmatic weak supervision (PWS) has achieved remarkable success in easing the manual labeling bottleneck by programmatically synthesizing training labels from multiple potentially noisy...
1607.03408
Gabriel Martins Dias
Gabriel Martins Dias
Performance Optimization of WSNs using External Information
Published in: IEEE 14th International Symposium and Workshops on a World of Wireless, Mobile and Multimedia Networks (WoWMoM), 2013 (copyright has been transferred to IEEE)
null
10.1109/WoWMoM.2013.6583430
null
cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The goal of this work is to describe a self-management system that correlates data sensed by different Wireless Sensor Networks (WSNs) and adjusts the number of active nodes in each network to provide an appropriate amount of measurements. The architecture considers the factors that make the external data relevant to...
[ { "created": "Tue, 12 Jul 2016 15:35:42 GMT", "version": "v1" } ]
2016-07-13
[ [ "Dias", "Gabriel Martins", "" ] ]
The goal of this work is to describe a self-management system that correlates data sensed by different Wireless Sensor Networks (WSNs) and adjusts the number of active nodes in each network to provide an appropriate amount of measurements. The architecture considers the factors that make the external data relevant to t...
1907.04592
Alexey Potapov
Alexey Potapov, Anatoly Belikov, Vitaly Bogdanov, Alexander Scherbatiy
Differentiable Probabilistic Logic Networks
null
null
null
null
cs.AI cs.LO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Probabilistic logic reasoning is a central component of such cognitive architectures as OpenCog. However, as an integrative architecture, OpenCog facilitates cognitive synergy via hybridization of different inference methods. In this paper, we introduce a differentiable version of Probabilistic Logic networks, which ...
[ { "created": "Wed, 10 Jul 2019 09:44:10 GMT", "version": "v1" } ]
2019-07-11
[ [ "Potapov", "Alexey", "" ], [ "Belikov", "Anatoly", "" ], [ "Bogdanov", "Vitaly", "" ], [ "Scherbatiy", "Alexander", "" ] ]
Probabilistic logic reasoning is a central component of such cognitive architectures as OpenCog. However, as an integrative architecture, OpenCog facilitates cognitive synergy via hybridization of different inference methods. In this paper, we introduce a differentiable version of Probabilistic Logic networks, which ru...
2104.04996
Ran Tamir (Averbuch)
Ran Tamir (Averbuch), Ariel Livshits, and Yonatan Shadmi
Simple Majority Consensus in Networks with Unreliable Communication
null
null
10.3390/e24030333
null
cs.IT cs.DC math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this work, we analyze the performance of a simple majority-rule protocol solving a fundamental coordination problem in distributed systems - \emph{binary majority consensus}, in the presence of probabilistic message loss. Using probabilistic analysis for a large scale, fully-connected, network of $2n$ agents, we p...
[ { "created": "Sun, 11 Apr 2021 11:36:21 GMT", "version": "v1" } ]
2022-03-09
[ [ "Tamir", "Ran", "", "Averbuch" ], [ "Livshits", "Ariel", "" ], [ "Shadmi", "Yonatan", "" ] ]
In this work, we analyze the performance of a simple majority-rule protocol solving a fundamental coordination problem in distributed systems - \emph{binary majority consensus}, in the presence of probabilistic message loss. Using probabilistic analysis for a large scale, fully-connected, network of $2n$ agents, we pro...
2011.00616
Alexander Wolpert
Evgeny Dantsin and Alexander Wolpert
Similarity Between Points in Metric Measure Spaces
10 pages, 2 figures. In: Proceedings of the 13th International Conference on Similarity Search and Applications, SISAP 2020. Vol. 12440. Lecture Notes in Computer Science. Springer, 2020, pp. 177-184
null
null
null
cs.DM
http://creativecommons.org/licenses/by/4.0/
This paper is about similarity between objects that can be represented as points in metric measure spaces. A metric measure space is a metric space that is also equipped with a measure. For example, a network with distances between its nodes and weights assigned to its nodes is a metric measure space. Given points x ...
[ { "created": "Sun, 1 Nov 2020 19:52:54 GMT", "version": "v1" } ]
2020-11-03
[ [ "Dantsin", "Evgeny", "" ], [ "Wolpert", "Alexander", "" ] ]
This paper is about similarity between objects that can be represented as points in metric measure spaces. A metric measure space is a metric space that is also equipped with a measure. For example, a network with distances between its nodes and weights assigned to its nodes is a metric measure space. Given points x an...
2007.15652
Peyman Moghadam
Thomas Lowe, Peyman Moghadam, Everard Edwards, Jason Williams
Canopy Density Estimation in Perennial Horticulture Crops Using 3D Spinning Lidar SLAM
Accepted to Journal of Field Robotics. More information at https://github.com/csiro-robotics/agscan3d
null
10.1002/rob.22006
null
cs.RO eess.IV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We propose a novel, canopy density estimation solution using a 3D ray cloud representation for perennial horticultural crops at the field scale. To attain high spatial and temporal fidelity in field conditions, we propose the application of continuous-time 3D SLAM (Simultaneous Localisation and Mapping) to a spinning...
[ { "created": "Thu, 30 Jul 2020 05:51:38 GMT", "version": "v1" }, { "created": "Tue, 15 Dec 2020 00:56:20 GMT", "version": "v2" } ]
2020-12-16
[ [ "Lowe", "Thomas", "" ], [ "Moghadam", "Peyman", "" ], [ "Edwards", "Everard", "" ], [ "Williams", "Jason", "" ] ]
We propose a novel, canopy density estimation solution using a 3D ray cloud representation for perennial horticultural crops at the field scale. To attain high spatial and temporal fidelity in field conditions, we propose the application of continuous-time 3D SLAM (Simultaneous Localisation and Mapping) to a spinning l...
1803.07724
Jasdeep Singh
Jasdeep Singh, Vincent Ying, Alex Nutkiewicz
Attention on Attention: Architectures for Visual Question Answering (VQA)
Visual Question Answering Project
null
null
null
cs.CL cs.AI cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Visual Question Answering (VQA) is an increasingly popular topic in deep learning research, requiring coordination of natural language processing and computer vision modules into a single architecture. We build upon the model which placed first in the VQA Challenge by developing thirteen new attention mechanisms and ...
[ { "created": "Wed, 21 Mar 2018 03:05:58 GMT", "version": "v1" } ]
2018-03-22
[ [ "Singh", "Jasdeep", "" ], [ "Ying", "Vincent", "" ], [ "Nutkiewicz", "Alex", "" ] ]
Visual Question Answering (VQA) is an increasingly popular topic in deep learning research, requiring coordination of natural language processing and computer vision modules into a single architecture. We build upon the model which placed first in the VQA Challenge by developing thirteen new attention mechanisms and in...
2408.04232
Wei Zhang
Wei Zhang, Peng Tang
Enhanced Traffic Flow Prediction with Multi-Segment Fusion Tensor Graph Convolutional Networks
null
null
null
null
cs.LG cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Accurate traffic Flow Prediction can assist in traffic management, route planning, and congestion mitigation, which holds significant importance in enhancing the efficiency and reliability of intelligent transportation systems (ITS). However, existing traffic flow prediction models suffer from limitations in capturin...
[ { "created": "Thu, 8 Aug 2024 05:37:17 GMT", "version": "v1" } ]
2024-08-09
[ [ "Zhang", "Wei", "" ], [ "Tang", "Peng", "" ] ]
Accurate traffic Flow Prediction can assist in traffic management, route planning, and congestion mitigation, which holds significant importance in enhancing the efficiency and reliability of intelligent transportation systems (ITS). However, existing traffic flow prediction models suffer from limitations in capturing ...
2211.03128
Giuseppe Vietri
Travis Dick, Cynthia Dwork, Michael Kearns, Terrance Liu, Aaron Roth, Giuseppe Vietri, Zhiwei Steven Wu
Confidence-Ranked Reconstruction of Census Microdata from Published Statistics
null
null
10.1073/pnas.2218605120
null
cs.CY cs.CR cs.LG
http://creativecommons.org/licenses/by/4.0/
A reconstruction attack on a private dataset $D$ takes as input some publicly accessible information about the dataset and produces a list of candidate elements of $D$. We introduce a new class of data reconstruction attacks based on randomized methods for non-convex optimization. We empirically demonstrate that our ...
[ { "created": "Sun, 6 Nov 2022 14:08:43 GMT", "version": "v1" }, { "created": "Mon, 6 Feb 2023 17:32:02 GMT", "version": "v2" } ]
2023-03-29
[ [ "Dick", "Travis", "" ], [ "Dwork", "Cynthia", "" ], [ "Kearns", "Michael", "" ], [ "Liu", "Terrance", "" ], [ "Roth", "Aaron", "" ], [ "Vietri", "Giuseppe", "" ], [ "Wu", "Zhiwei Steven", "" ] ]
A reconstruction attack on a private dataset $D$ takes as input some publicly accessible information about the dataset and produces a list of candidate elements of $D$. We introduce a new class of data reconstruction attacks based on randomized methods for non-convex optimization. We empirically demonstrate that our at...
2302.14543
Himanshu .
Himanshu, Jinraj V Pushpangathan and Harikumar Kandath
RRT and Velocity Obstacles-based motion planning for Unmanned Aircraft Systems Traffic Management (UTM)
Currently under review in The 2023 International Conference On Unmanned Aircraft Systems
null
null
null
cs.RO
http://creativecommons.org/licenses/by/4.0/
In this paper, an algorithm for Unmanned Aircraft Systems Traffic Management (UTM) for a finite number of unmanned aerial vehicles (UAVs) is proposed. This algorithm is developed by combining the Rapidly-Exploring Random Trees (RRT) and Velocity Obstacle (VO) algorithms and is referred to as the RRT-VO UTM algorithm....
[ { "created": "Tue, 28 Feb 2023 13:08:11 GMT", "version": "v1" } ]
2023-03-01
[ [ "Himanshu", "", "" ], [ "Pushpangathan", "Jinraj V", "" ], [ "Kandath", "Harikumar", "" ] ]
In this paper, an algorithm for Unmanned Aircraft Systems Traffic Management (UTM) for a finite number of unmanned aerial vehicles (UAVs) is proposed. This algorithm is developed by combining the Rapidly-Exploring Random Trees (RRT) and Velocity Obstacle (VO) algorithms and is referred to as the RRT-VO UTM algorithm. H...
1710.10800
Bharath Ramesh
Bharath Ramesh, Hong Yang, Garrick Orchard, Ngoc Anh Le Thi, Shihao Zhang and Cheng Xiang
DART: Distribution Aware Retinal Transform for Event-based Cameras
12 pages, revision submitted to TPAMI in Nov 2018
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We introduce a generic visual descriptor, termed as distribution aware retinal transform (DART), that encodes the structural context using log-polar grids for event cameras. The DART descriptor is applied to four different problems, namely object classification, tracking, detection and feature matching: (1) The DART ...
[ { "created": "Mon, 30 Oct 2017 08:08:57 GMT", "version": "v1" }, { "created": "Tue, 13 Nov 2018 02:37:41 GMT", "version": "v2" }, { "created": "Wed, 14 Nov 2018 07:40:55 GMT", "version": "v3" } ]
2018-11-15
[ [ "Ramesh", "Bharath", "" ], [ "Yang", "Hong", "" ], [ "Orchard", "Garrick", "" ], [ "Thi", "Ngoc Anh Le", "" ], [ "Zhang", "Shihao", "" ], [ "Xiang", "Cheng", "" ] ]
We introduce a generic visual descriptor, termed as distribution aware retinal transform (DART), that encodes the structural context using log-polar grids for event cameras. The DART descriptor is applied to four different problems, namely object classification, tracking, detection and feature matching: (1) The DART fe...
1008.5189
Anastasia Paparrizou Ms
Thanasis Balafoutis, Anastasia Paparrizou, Kostas Stergiou and Toby Walsh
Improving the Performance of maxRPC
null
null
null
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Max Restricted Path Consistency (maxRPC) is a local consistency for binary constraints that can achieve considerably stronger pruning than arc consistency. However, existing maxRRC algorithms suffer from overheads and redundancies as they can repeatedly perform many constraint checks without triggering any value dele...
[ { "created": "Mon, 30 Aug 2010 23:50:33 GMT", "version": "v1" } ]
2010-09-01
[ [ "Balafoutis", "Thanasis", "" ], [ "Paparrizou", "Anastasia", "" ], [ "Stergiou", "Kostas", "" ], [ "Walsh", "Toby", "" ] ]
Max Restricted Path Consistency (maxRPC) is a local consistency for binary constraints that can achieve considerably stronger pruning than arc consistency. However, existing maxRRC algorithms suffer from overheads and redundancies as they can repeatedly perform many constraint checks without triggering any value deleti...
2110.11155
Luca Traini PhD
Luca Traini, Vittorio Cortellessa
DeLag: Using Multi-Objective Optimization to Enhance the Detection of Latency Degradation Patterns in Service-based Systems
Accepted for publication in IEEE Transactions on Software Engineering (TSE)
null
10.1109/TSE.2023.3266041
null
cs.SE cs.LG cs.PF
http://creativecommons.org/licenses/by/4.0/
Performance debugging in production is a fundamental activity in modern service-based systems. The diagnosis of performance issues is often time-consuming, since it requires thorough inspection of large volumes of traces and performance indices. In this paper we present DeLag, a novel automated search-based approach ...
[ { "created": "Thu, 21 Oct 2021 13:59:32 GMT", "version": "v1" }, { "created": "Fri, 30 Sep 2022 10:58:53 GMT", "version": "v2" }, { "created": "Thu, 29 Dec 2022 18:53:22 GMT", "version": "v3" }, { "created": "Fri, 7 Apr 2023 14:09:42 GMT", "version": "v4" } ]
2023-04-10
[ [ "Traini", "Luca", "" ], [ "Cortellessa", "Vittorio", "" ] ]
Performance debugging in production is a fundamental activity in modern service-based systems. The diagnosis of performance issues is often time-consuming, since it requires thorough inspection of large volumes of traces and performance indices. In this paper we present DeLag, a novel automated search-based approach fo...
2209.03496
Allen Chang
Allen Chang, Lauren Klein, Marcelo R. Rosales, Weiyang Deng, Beth A. Smith, Maja J. Matari\'c
Evaluating Temporal Patterns in Applied Infant Affect Recognition
8 pages, 6 figures, 10th International Conference on Affective Computing and Intelligent Interaction (ACII 2022)
null
null
null
cs.HC cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Agents must monitor their partners' affective states continuously in order to understand and engage in social interactions. However, methods for evaluating affect recognition do not account for changes in classification performance that may occur during occlusions or transitions between affective states. This paper a...
[ { "created": "Wed, 7 Sep 2022 23:29:15 GMT", "version": "v1" } ]
2022-09-09
[ [ "Chang", "Allen", "" ], [ "Klein", "Lauren", "" ], [ "Rosales", "Marcelo R.", "" ], [ "Deng", "Weiyang", "" ], [ "Smith", "Beth A.", "" ], [ "Matarić", "Maja J.", "" ] ]
Agents must monitor their partners' affective states continuously in order to understand and engage in social interactions. However, methods for evaluating affect recognition do not account for changes in classification performance that may occur during occlusions or transitions between affective states. This paper add...
2007.15415
Luca Reggio
Mai Gehrke, Tomas Jakl, Luca Reggio
A Cook's tour of duality in logic: from quantifiers, through Vietoris, to measures
29 pages
null
null
null
cs.LO math.CT math.GN math.LO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We identify and highlight certain landmark results in Samson Abramsky's work which we believe are fundamental to current developments and future trends. In particular, we focus on the use of (i) topological duality methods to solve problems in logic and computer science; (ii) category theory and, more particularly, f...
[ { "created": "Thu, 30 Jul 2020 12:22:10 GMT", "version": "v1" } ]
2020-07-31
[ [ "Gehrke", "Mai", "" ], [ "Jakl", "Tomas", "" ], [ "Reggio", "Luca", "" ] ]
We identify and highlight certain landmark results in Samson Abramsky's work which we believe are fundamental to current developments and future trends. In particular, we focus on the use of (i) topological duality methods to solve problems in logic and computer science; (ii) category theory and, more particularly, fre...
1809.05515
Marko Angjelichinoski
Marko Angjelichinoski, Kasper Fl{\o}e Trillingsgaard and Petar Popovski
A Statistical Learning Approach to Ultra-Reliable Low Latency Communication
Submitted for publication
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Mission-critical applications require Ultra-Reliable Low Latency (URLLC) wireless connections, where the packet error rate (PER) goes down to $10^{-9}$. Fulfillment of the bold reliability figures becomes meaningful only if it can be related to a statistical model in which the URLLC system operates. However, this mod...
[ { "created": "Fri, 14 Sep 2018 17:30:58 GMT", "version": "v1" } ]
2018-09-17
[ [ "Angjelichinoski", "Marko", "" ], [ "Trillingsgaard", "Kasper Fløe", "" ], [ "Popovski", "Petar", "" ] ]
Mission-critical applications require Ultra-Reliable Low Latency (URLLC) wireless connections, where the packet error rate (PER) goes down to $10^{-9}$. Fulfillment of the bold reliability figures becomes meaningful only if it can be related to a statistical model in which the URLLC system operates. However, this model...
2406.11081
Sara Ahmadi
Sara Ahmadi, Peter Desain, Jordy Thielen
A Bayesian dynamic stopping method for evoked response brain-computer interfacing
null
null
null
null
cs.HC
http://creativecommons.org/licenses/by/4.0/
As brain-computer interfacing (BCI) systems transition from assistive technology to more diverse applications, their speed, reliability, and user experience become increasingly important. Dynamic stopping methods enhance BCI system speed by deciding at any moment whether to output a result or wait for more informatio...
[ { "created": "Sun, 16 Jun 2024 21:41:48 GMT", "version": "v1" } ]
2024-06-18
[ [ "Ahmadi", "Sara", "" ], [ "Desain", "Peter", "" ], [ "Thielen", "Jordy", "" ] ]
As brain-computer interfacing (BCI) systems transition from assistive technology to more diverse applications, their speed, reliability, and user experience become increasingly important. Dynamic stopping methods enhance BCI system speed by deciding at any moment whether to output a result or wait for more information....
1506.09075
Byeongkeun Kang
Yuanyuan Wu, Xiaohai He, Byeongkeun Kang, Haiying Song, and Truong Q. Nguyen
Long-Range Motion Trajectories Extraction of Articulated Human Using Mesh Evolution
IEEE Signal Processing Letters
null
10.1109/LSP.2016.2536647
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This letter presents a novel approach to extract reliable dense and long-range motion trajectories of articulated human in a video sequence. Compared with existing approaches that emphasize temporal consistency of each tracked point, we also consider the spatial structure of tracked points on the articulated human. W...
[ { "created": "Tue, 30 Jun 2015 13:18:18 GMT", "version": "v1" }, { "created": "Mon, 29 Feb 2016 17:10:11 GMT", "version": "v2" }, { "created": "Tue, 29 Mar 2016 00:21:40 GMT", "version": "v3" } ]
2016-03-30
[ [ "Wu", "Yuanyuan", "" ], [ "He", "Xiaohai", "" ], [ "Kang", "Byeongkeun", "" ], [ "Song", "Haiying", "" ], [ "Nguyen", "Truong Q.", "" ] ]
This letter presents a novel approach to extract reliable dense and long-range motion trajectories of articulated human in a video sequence. Compared with existing approaches that emphasize temporal consistency of each tracked point, we also consider the spatial structure of tracked points on the articulated human. We ...
2305.19860
Likang Wu
Likang Wu, Zhi Zheng, Zhaopeng Qiu, Hao Wang, Hongchao Gu, Tingjia Shen, Chuan Qin, Chen Zhu, Hengshu Zhu, Qi Liu, Hui Xiong, Enhong Chen
A Survey on Large Language Models for Recommendation
34 pages, 7 figures, 2 tables
null
null
null
cs.IR cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Large Language Models (LLMs) have emerged as powerful tools in the field of Natural Language Processing (NLP) and have recently gained significant attention in the domain of Recommendation Systems (RS). These models, trained on massive amounts of data using self-supervised learning, have demonstrated remarkable succe...
[ { "created": "Wed, 31 May 2023 13:51:26 GMT", "version": "v1" }, { "created": "Thu, 1 Jun 2023 03:22:17 GMT", "version": "v2" }, { "created": "Fri, 4 Aug 2023 02:58:15 GMT", "version": "v3" }, { "created": "Fri, 18 Aug 2023 05:56:05 GMT", "version": "v4" }, { "cre...
2024-06-19
[ [ "Wu", "Likang", "" ], [ "Zheng", "Zhi", "" ], [ "Qiu", "Zhaopeng", "" ], [ "Wang", "Hao", "" ], [ "Gu", "Hongchao", "" ], [ "Shen", "Tingjia", "" ], [ "Qin", "Chuan", "" ], [ "Zhu", "Chen", ...
Large Language Models (LLMs) have emerged as powerful tools in the field of Natural Language Processing (NLP) and have recently gained significant attention in the domain of Recommendation Systems (RS). These models, trained on massive amounts of data using self-supervised learning, have demonstrated remarkable success...
2408.02814
Shaopeng Fu
Shaopeng Fu, Xuexue Sun, Ke Qing, Tianhang Zheng, Di Wang
Pre-trained Encoder Inference: Revealing Upstream Encoders In Downstream Machine Learning Services
null
null
null
null
cs.LG cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Though pre-trained encoders can be easily accessed online to build downstream machine learning (ML) services quickly, various attacks have been designed to compromise the security and privacy of these encoders. While most attacks target encoders on the upstream side, it remains unknown how an encoder could be threate...
[ { "created": "Mon, 5 Aug 2024 20:27:54 GMT", "version": "v1" } ]
2024-08-07
[ [ "Fu", "Shaopeng", "" ], [ "Sun", "Xuexue", "" ], [ "Qing", "Ke", "" ], [ "Zheng", "Tianhang", "" ], [ "Wang", "Di", "" ] ]
Though pre-trained encoders can be easily accessed online to build downstream machine learning (ML) services quickly, various attacks have been designed to compromise the security and privacy of these encoders. While most attacks target encoders on the upstream side, it remains unknown how an encoder could be threatene...
2305.00077
Binnur Gorer
Binnur G\"orer and Fatma Ba\c{s}ak Aydemir
Exploring Emerging Technologies for Requirements Elicitation Interview Training: Empirical Assessment of Robotic and Virtual Tutors
Author submitted manuscript
null
null
null
cs.SE cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Requirements elicitation interviews are a widely adopted technique, where the interview success heavily depends on the interviewer's preparedness and communication skills. Students can enhance these skills through practice interviews. However, organizing practice interviews for many students presents scalability chal...
[ { "created": "Fri, 28 Apr 2023 20:03:48 GMT", "version": "v1" }, { "created": "Thu, 24 Aug 2023 23:21:20 GMT", "version": "v2" }, { "created": "Wed, 30 Aug 2023 14:39:22 GMT", "version": "v3" } ]
2023-08-31
[ [ "Görer", "Binnur", "" ], [ "Aydemir", "Fatma Başak", "" ] ]
Requirements elicitation interviews are a widely adopted technique, where the interview success heavily depends on the interviewer's preparedness and communication skills. Students can enhance these skills through practice interviews. However, organizing practice interviews for many students presents scalability challe...
2103.02270
Dian Fan
Dian Fan, Xiaojun Yuan, Ying-Jun Angela Zhang
Temporal-Structure-Assisted Gradient Aggregation for Over-the-Air Federated Edge Learning
null
null
null
null
cs.IT cs.LG math.IT
http://creativecommons.org/licenses/by/4.0/
In this paper, we investigate over-the-air model aggregation in a federated edge learning (FEEL) system. We introduce a Markovian probability model to characterize the intrinsic temporal structure of the model aggregation series. With this temporal probability model, we formulate the model aggregation problem as to i...
[ { "created": "Wed, 3 Mar 2021 09:13:27 GMT", "version": "v1" } ]
2021-03-04
[ [ "Fan", "Dian", "" ], [ "Yuan", "Xiaojun", "" ], [ "Zhang", "Ying-Jun Angela", "" ] ]
In this paper, we investigate over-the-air model aggregation in a federated edge learning (FEEL) system. We introduce a Markovian probability model to characterize the intrinsic temporal structure of the model aggregation series. With this temporal probability model, we formulate the model aggregation problem as to inf...
2406.08164
Muhammad Jehanzeb Mirza
Irene Huang, Wei Lin, M. Jehanzeb Mirza, Jacob A. Hansen, Sivan Doveh, Victor Ion Butoi, Roei Herzig, Assaf Arbelle, Hilde Kuhene, Trevor Darrel, Chuang Gan, Aude Oliva, Rogerio Feris, Leonid Karlinsky
ConMe: Rethinking Evaluation of Compositional Reasoning for Modern VLMs
The first three authors contributed equally
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Compositional Reasoning (CR) entails grasping the significance of attributes, relations, and word order. Recent Vision-Language Models (VLMs), comprising a visual encoder and a Large Language Model (LLM) decoder, have demonstrated remarkable proficiency in such reasoning tasks. This prompts a crucial question: have V...
[ { "created": "Wed, 12 Jun 2024 12:54:27 GMT", "version": "v1" } ]
2024-06-13
[ [ "Huang", "Irene", "" ], [ "Lin", "Wei", "" ], [ "Mirza", "M. Jehanzeb", "" ], [ "Hansen", "Jacob A.", "" ], [ "Doveh", "Sivan", "" ], [ "Butoi", "Victor Ion", "" ], [ "Herzig", "Roei", "" ], [ "Arbe...
Compositional Reasoning (CR) entails grasping the significance of attributes, relations, and word order. Recent Vision-Language Models (VLMs), comprising a visual encoder and a Large Language Model (LLM) decoder, have demonstrated remarkable proficiency in such reasoning tasks. This prompts a crucial question: have VLM...
2111.00610
Anurag Katakkar
Anurag Katakkar, Alan W Black
Towards Language Modelling in the Speech Domain Using Sub-word Linguistic Units
null
null
null
null
cs.CL cs.LG cs.SD eess.AS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Language models (LMs) for text data have been studied extensively for their usefulness in language generation and other downstream tasks. However, language modelling purely in the speech domain is still a relatively unexplored topic, with traditional speech LMs often depending on auxiliary text LMs for learning distr...
[ { "created": "Sun, 31 Oct 2021 22:48:30 GMT", "version": "v1" } ]
2021-11-02
[ [ "Katakkar", "Anurag", "" ], [ "Black", "Alan W", "" ] ]
Language models (LMs) for text data have been studied extensively for their usefulness in language generation and other downstream tasks. However, language modelling purely in the speech domain is still a relatively unexplored topic, with traditional speech LMs often depending on auxiliary text LMs for learning distrib...
2009.01229
Marialejandra Garcia-Corretjer
Marialejandra Garcia Corretjer, David Miralles, and Raquel Ros
A Theoretical Approach for a Novel Model to Realizing Empathy
47 pages, 11 figures
null
null
null
cs.CY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The first objective of this paper are to introduce a strong theoretical concept as a proposed model that visualizes the process of realizing empathy, based on the ample analysis of the collected work in the survey. Secondly, the intended purpose of this proposed model, is to create an initial blueprint that may be ap...
[ { "created": "Thu, 3 Sep 2020 17:21:49 GMT", "version": "v1" } ]
2020-09-04
[ [ "Corretjer", "Marialejandra Garcia", "" ], [ "Miralles", "David", "" ], [ "Ros", "Raquel", "" ] ]
The first objective of this paper are to introduce a strong theoretical concept as a proposed model that visualizes the process of realizing empathy, based on the ample analysis of the collected work in the survey. Secondly, the intended purpose of this proposed model, is to create an initial blueprint that may be appl...
1712.00811
Hamoon Mousavi
Hamoon Mousavi
Lower Bounds on Regular Expression Size
29 pages
null
null
null
cs.FL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We introduce linear programs encoding regular expressions of finite languages. We show that, given a language, the optimum value of the associated linear program is a lower bound on the size of any regular expression of the language. Moreover we show that any regular expression can be turned into a dual feasible solu...
[ { "created": "Sun, 3 Dec 2017 18:35:48 GMT", "version": "v1" }, { "created": "Wed, 6 Dec 2017 22:05:17 GMT", "version": "v2" } ]
2017-12-08
[ [ "Mousavi", "Hamoon", "" ] ]
We introduce linear programs encoding regular expressions of finite languages. We show that, given a language, the optimum value of the associated linear program is a lower bound on the size of any regular expression of the language. Moreover we show that any regular expression can be turned into a dual feasible soluti...
1808.07712
Gurkirt Singh
Gurkirt Singh and Suman Saha and Fabio Cuzzolin
Predicting Action Tubes
ECCV workshop; Anticipating Human Behaviour 2018; 16 page 7 figures
null
null
null
cs.CV cs.AI cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this work, we present a method to predict an entire `action tube' (a set of temporally linked bounding boxes) in a trimmed video just by observing a smaller subset of it. Predicting where an action is going to take place in the near future is essential to many computer vision based applications such as autonomous ...
[ { "created": "Thu, 23 Aug 2018 12:11:06 GMT", "version": "v1" } ]
2018-08-24
[ [ "Singh", "Gurkirt", "" ], [ "Saha", "Suman", "" ], [ "Cuzzolin", "Fabio", "" ] ]
In this work, we present a method to predict an entire `action tube' (a set of temporally linked bounding boxes) in a trimmed video just by observing a smaller subset of it. Predicting where an action is going to take place in the near future is essential to many computer vision based applications such as autonomous dr...
2303.12696
Zhiyuan Hu
Zhiyuan Hu, Yunsheng Li, Jiancheng Lyu, Dashan Gao, Nuno Vasconcelos
Dense Network Expansion for Class Incremental Learning
Accepted by CVPR2023
null
null
null
cs.CV cs.AI
http://creativecommons.org/licenses/by-nc-nd/4.0/
The problem of class incremental learning (CIL) is considered. State-of-the-art approaches use a dynamic architecture based on network expansion (NE), in which a task expert is added per task. While effective from a computational standpoint, these methods lead to models that grow quickly with the number of tasks. A n...
[ { "created": "Wed, 22 Mar 2023 16:42:26 GMT", "version": "v1" } ]
2023-03-23
[ [ "Hu", "Zhiyuan", "" ], [ "Li", "Yunsheng", "" ], [ "Lyu", "Jiancheng", "" ], [ "Gao", "Dashan", "" ], [ "Vasconcelos", "Nuno", "" ] ]
The problem of class incremental learning (CIL) is considered. State-of-the-art approaches use a dynamic architecture based on network expansion (NE), in which a task expert is added per task. While effective from a computational standpoint, these methods lead to models that grow quickly with the number of tasks. A new...
2401.10338
Jingchao Ni
Jingchao Ni, Gauthier Guinet, Peihong Jiang, Laurent Callot, Andrey Kan
MELODY: Robust Semi-Supervised Hybrid Model for Entity-Level Online Anomaly Detection with Multivariate Time Series
null
null
null
null
cs.LG
http://creativecommons.org/licenses/by/4.0/
In large IT systems, software deployment is a crucial process in online services as their code is regularly updated. However, a faulty code change may degrade the target service's performance and cause cascading outages in downstream services. Thus, software deployments should be comprehensively monitored, and their ...
[ { "created": "Thu, 18 Jan 2024 19:02:41 GMT", "version": "v1" }, { "created": "Thu, 6 Jun 2024 04:35:00 GMT", "version": "v2" } ]
2024-06-07
[ [ "Ni", "Jingchao", "" ], [ "Guinet", "Gauthier", "" ], [ "Jiang", "Peihong", "" ], [ "Callot", "Laurent", "" ], [ "Kan", "Andrey", "" ] ]
In large IT systems, software deployment is a crucial process in online services as their code is regularly updated. However, a faulty code change may degrade the target service's performance and cause cascading outages in downstream services. Thus, software deployments should be comprehensively monitored, and their an...
1705.01143
Shih-Chieh Su
Shih-Chieh Su
Summarized Network Behavior Prediction
null
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This work studies the entity-wise topical behavior from massive network logs. Both the temporal and the spatial relationships of the behavior are explored with the learning architectures combing the recurrent neural network (RNN) and the convolutional neural network (CNN). To make the behavioral data appropriate for ...
[ { "created": "Tue, 2 May 2017 19:12:23 GMT", "version": "v1" } ]
2017-05-04
[ [ "Su", "Shih-Chieh", "" ] ]
This work studies the entity-wise topical behavior from massive network logs. Both the temporal and the spatial relationships of the behavior are explored with the learning architectures combing the recurrent neural network (RNN) and the convolutional neural network (CNN). To make the behavioral data appropriate for th...
2010.03110
Sumedh Sontakke
Sumedh A. Sontakke, Arash Mehrjou, Laurent Itti, Bernhard Sch\"olkopf
Causal Curiosity: RL Agents Discovering Self-supervised Experiments for Causal Representation Learning
International Conference on Machine Learning, PMLR 139, 2021
null
null
null
cs.LG cs.AI cs.RO
http://creativecommons.org/licenses/by/4.0/
Animals exhibit an innate ability to learn regularities of the world through interaction. By performing experiments in their environment, they are able to discern the causal factors of variation and infer how they affect the world's dynamics. Inspired by this, we attempt to equip reinforcement learning agents with th...
[ { "created": "Wed, 7 Oct 2020 02:07:51 GMT", "version": "v1" }, { "created": "Wed, 14 Apr 2021 23:59:04 GMT", "version": "v2" }, { "created": "Wed, 9 Jun 2021 01:19:39 GMT", "version": "v3" }, { "created": "Fri, 6 Aug 2021 21:53:05 GMT", "version": "v4" } ]
2021-08-10
[ [ "Sontakke", "Sumedh A.", "" ], [ "Mehrjou", "Arash", "" ], [ "Itti", "Laurent", "" ], [ "Schölkopf", "Bernhard", "" ] ]
Animals exhibit an innate ability to learn regularities of the world through interaction. By performing experiments in their environment, they are able to discern the causal factors of variation and infer how they affect the world's dynamics. Inspired by this, we attempt to equip reinforcement learning agents with the ...
1602.00251
Kaveh Bakhtiyari
Kaveh Bakhtiyari
Do we have privacy in the digital world?
null
null
10.13140/RG.2.1.2492.5203/2
null
cs.CR cs.HC cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Not really.
[ { "created": "Sun, 31 Jan 2016 14:22:47 GMT", "version": "v1" }, { "created": "Thu, 26 Jan 2017 15:53:55 GMT", "version": "v2" } ]
2017-01-27
[ [ "Bakhtiyari", "Kaveh", "" ] ]
Not really.
2312.00220
Linzi Xing
Linzi Xing, Quan Tran, Fabian Caba, Franck Dernoncourt, Seunghyun Yoon, Zhaowen Wang, Trung Bui, Giuseppe Carenini
Multi-Modal Video Topic Segmentation with Dual-Contrastive Domain Adaptation
Accepted at the 30th International Conference on Multimedia Modeling (MMM 2024)
null
null
null
cs.MM cs.CL cs.CV
http://creativecommons.org/licenses/by/4.0/
Video topic segmentation unveils the coarse-grained semantic structure underlying videos and is essential for other video understanding tasks. Given the recent surge in multi-modal, relying solely on a single modality is arguably insufficient. On the other hand, prior solutions for similar tasks like video scene/shot...
[ { "created": "Thu, 30 Nov 2023 21:59:05 GMT", "version": "v1" } ]
2023-12-04
[ [ "Xing", "Linzi", "" ], [ "Tran", "Quan", "" ], [ "Caba", "Fabian", "" ], [ "Dernoncourt", "Franck", "" ], [ "Yoon", "Seunghyun", "" ], [ "Wang", "Zhaowen", "" ], [ "Bui", "Trung", "" ], [ "Carenini"...
Video topic segmentation unveils the coarse-grained semantic structure underlying videos and is essential for other video understanding tasks. Given the recent surge in multi-modal, relying solely on a single modality is arguably insufficient. On the other hand, prior solutions for similar tasks like video scene/shot s...
2004.14793
Gal Mendelson
Gal Mendelson
A Lower Bound on the stability region of Redundancy-d with FIFO service discipline
null
null
null
null
cs.PF cs.SY eess.SY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Redundancy-d (R(d)) is a load balancing method used to route incoming jobs to K servers, each with its own queue. Every arriving job is replicated into 2<=d<=K tasks, which are then routed to d servers chosen uniformly at random. When the first task finishes service, the remaining d-1 tasks are cancelled and the job ...
[ { "created": "Thu, 30 Apr 2020 14:07:25 GMT", "version": "v1" }, { "created": "Thu, 21 May 2020 18:15:06 GMT", "version": "v2" } ]
2020-05-25
[ [ "Mendelson", "Gal", "" ] ]
Redundancy-d (R(d)) is a load balancing method used to route incoming jobs to K servers, each with its own queue. Every arriving job is replicated into 2<=d<=K tasks, which are then routed to d servers chosen uniformly at random. When the first task finishes service, the remaining d-1 tasks are cancelled and the job de...
2404.00492
Lijie Hu
Keyuan Cheng, Gang Lin, Haoyang Fei, Yuxuan zhai, Lu Yu, Muhammad Asif Ali, Lijie Hu, and Di Wang
Multi-hop Question Answering under Temporal Knowledge Editing
23 pages
null
null
null
cs.CL cs.AI cs.LG
http://creativecommons.org/licenses/by/4.0/
Multi-hop question answering (MQA) under knowledge editing (KE) has garnered significant attention in the era of large language models. However, existing models for MQA under KE exhibit poor performance when dealing with questions containing explicit temporal contexts. To address this limitation, we propose a novel f...
[ { "created": "Sat, 30 Mar 2024 23:22:51 GMT", "version": "v1" } ]
2024-04-02
[ [ "Cheng", "Keyuan", "" ], [ "Lin", "Gang", "" ], [ "Fei", "Haoyang", "" ], [ "zhai", "Yuxuan", "" ], [ "Yu", "Lu", "" ], [ "Ali", "Muhammad Asif", "" ], [ "Hu", "Lijie", "" ], [ "Wang", "Di", ...
Multi-hop question answering (MQA) under knowledge editing (KE) has garnered significant attention in the era of large language models. However, existing models for MQA under KE exhibit poor performance when dealing with questions containing explicit temporal contexts. To address this limitation, we propose a novel fra...
1706.02499
Burak Benligiray
Burak Benligiray, Cihan Topal, Cuneyt Akinlar
SliceType: Fast Gaze Typing with a Merging Keyboard
null
Journal on Multimodal User Interfaces, 2018
10.1007/s12193-018-0285-z
null
cs.HC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Jitter is an inevitable by-product of gaze detection. Because of this, gaze typing tends to be a slow and frustrating process. In this paper, we propose SliceType, a soft keyboard that is optimized for gaze input. Our main design objective is to use the screen area more efficiently by allocating a larger area to the ...
[ { "created": "Thu, 8 Jun 2017 10:06:52 GMT", "version": "v1" }, { "created": "Thu, 8 Mar 2018 13:39:05 GMT", "version": "v2" }, { "created": "Sun, 18 Mar 2018 19:14:36 GMT", "version": "v3" }, { "created": "Thu, 27 Dec 2018 13:59:19 GMT", "version": "v4" } ]
2018-12-31
[ [ "Benligiray", "Burak", "" ], [ "Topal", "Cihan", "" ], [ "Akinlar", "Cuneyt", "" ] ]
Jitter is an inevitable by-product of gaze detection. Because of this, gaze typing tends to be a slow and frustrating process. In this paper, we propose SliceType, a soft keyboard that is optimized for gaze input. Our main design objective is to use the screen area more efficiently by allocating a larger area to the ta...
2405.07456
ABDELLAH Zakaria Sellam
Zakaria Abdellah Sellam, Cosimo Distante, Abdelmalik Taleb-Ahmed, Pier Luigi Mazzeo
Boosting House Price Estimations with Multi-Head Gated Attention
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Evaluating house prices is crucial for various stakeholders, including homeowners, investors, and policymakers. However, traditional spatial interpolation methods have limitations in capturing the complex spatial relationships that affect property values. To address these challenges, we have developed a new method ca...
[ { "created": "Mon, 13 May 2024 04:12:03 GMT", "version": "v1" } ]
2024-05-14
[ [ "Sellam", "Zakaria Abdellah", "" ], [ "Distante", "Cosimo", "" ], [ "Taleb-Ahmed", "Abdelmalik", "" ], [ "Mazzeo", "Pier Luigi", "" ] ]
Evaluating house prices is crucial for various stakeholders, including homeowners, investors, and policymakers. However, traditional spatial interpolation methods have limitations in capturing the complex spatial relationships that affect property values. To address these challenges, we have developed a new method call...
2204.07333
Prabhat Kumar
Prabhat Kumar, Eduardo Fern\'andez
Topology optimization for additive manufacturing with length scale, overhang, and building orientation constraints
null
null
null
null
cs.CE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper presents a density-based topology optimization approach considering additive manufacturing limitations. The presented method considers the minimum size of parts, the minimum size of cavities, the inability of printing overhanging parts without the use of sacrificial supporting structures, and the printing ...
[ { "created": "Fri, 15 Apr 2022 05:16:58 GMT", "version": "v1" } ]
2022-04-18
[ [ "Kumar", "Prabhat", "" ], [ "Fernández", "Eduardo", "" ] ]
This paper presents a density-based topology optimization approach considering additive manufacturing limitations. The presented method considers the minimum size of parts, the minimum size of cavities, the inability of printing overhanging parts without the use of sacrificial supporting structures, and the printing di...
2304.10512
Orchid Chetia Phukan
Usha Lokala, Orchid Chetia Phukan, Triyasha Ghosh Dastidar, Francois Lamy, Raminta Daniulaityte, Amit Sheth
"Can We Detect Substance Use Disorder?": Knowledge and Time Aware Classification on Social Media from Darkweb
null
null
null
null
cs.LG cs.CL cs.SI
http://creativecommons.org/licenses/by/4.0/
Opioid and substance misuse is rampant in the United States today, with the phenomenon known as the "opioid crisis". The relationship between substance use and mental health has been extensively studied, with one possible relationship being: substance misuse causes poor mental health. However, the lack of evidence on...
[ { "created": "Thu, 20 Apr 2023 17:47:13 GMT", "version": "v1" } ]
2023-04-21
[ [ "Lokala", "Usha", "" ], [ "Phukan", "Orchid Chetia", "" ], [ "Dastidar", "Triyasha Ghosh", "" ], [ "Lamy", "Francois", "" ], [ "Daniulaityte", "Raminta", "" ], [ "Sheth", "Amit", "" ] ]
Opioid and substance misuse is rampant in the United States today, with the phenomenon known as the "opioid crisis". The relationship between substance use and mental health has been extensively studied, with one possible relationship being: substance misuse causes poor mental health. However, the lack of evidence on t...
1604.03178
Luca de Alfaro
Luca de Alfaro, Michael Shavlovsky, Vassilis Polychronopoulos
Incentives for Truthful Peer Grading
26 pages
null
null
UCSC-SOE-15-19
cs.GT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Peer grading systems work well only if users have incentives to grade truthfully. An example of non-truthful grading, that we observed in classrooms, consists in students assigning the maximum grade to all submissions. With a naive grading scheme, such as averaging the assigned grades, all students would receive the ...
[ { "created": "Mon, 11 Apr 2016 23:56:21 GMT", "version": "v1" } ]
2016-04-13
[ [ "de Alfaro", "Luca", "" ], [ "Shavlovsky", "Michael", "" ], [ "Polychronopoulos", "Vassilis", "" ] ]
Peer grading systems work well only if users have incentives to grade truthfully. An example of non-truthful grading, that we observed in classrooms, consists in students assigning the maximum grade to all submissions. With a naive grading scheme, such as averaging the assigned grades, all students would receive the ma...
2303.00871
Lorenzo Mur-Labadia
Lorenzo Mur-Labadia, Ruben Martinez-Cantin and Jose J. Guerrero
Bayesian Deep Learning for Affordance Segmentation in images
2023 IEEE International Conference on Robotics and Automation (ICRA)
null
null
null
cs.CV cs.AI cs.LG cs.RO
http://creativecommons.org/licenses/by-nc-sa/4.0/
Affordances are a fundamental concept in robotics since they relate available actions for an agent depending on its sensory-motor capabilities and the environment. We present a novel Bayesian deep network to detect affordances in images, at the same time that we quantify the distribution of the aleatoric and epistemi...
[ { "created": "Thu, 2 Mar 2023 00:01:13 GMT", "version": "v1" } ]
2023-03-03
[ [ "Mur-Labadia", "Lorenzo", "" ], [ "Martinez-Cantin", "Ruben", "" ], [ "Guerrero", "Jose J.", "" ] ]
Affordances are a fundamental concept in robotics since they relate available actions for an agent depending on its sensory-motor capabilities and the environment. We present a novel Bayesian deep network to detect affordances in images, at the same time that we quantify the distribution of the aleatoric and epistemic ...
2211.13720
Sachit Rao
Wayne Paul Martis and Sachit Rao
Cooperative Collision Avoidance in Mobile Robots using Dynamic Vortex Potential Fields
null
null
null
null
cs.RO
http://creativecommons.org/licenses/by/4.0/
In this paper, the collision avoidance problem for non-holonomic robots moving at constant linear speeds in the 2-D plane is considered. The maneuvers to avoid collisions are designed using dynamic vortex potential fields (PFs) and their negative gradients; this formulation leads to a reciprocal behaviour between the...
[ { "created": "Thu, 24 Nov 2022 17:16:01 GMT", "version": "v1" } ]
2022-11-28
[ [ "Martis", "Wayne Paul", "" ], [ "Rao", "Sachit", "" ] ]
In this paper, the collision avoidance problem for non-holonomic robots moving at constant linear speeds in the 2-D plane is considered. The maneuvers to avoid collisions are designed using dynamic vortex potential fields (PFs) and their negative gradients; this formulation leads to a reciprocal behaviour between the r...
2101.10488
EPTCS
Paul Wilson (University of Southampton), Fabio Zanasi (University College London)
Reverse Derivative Ascent: A Categorical Approach to Learning Boolean Circuits
In Proceedings ACT 2020, arXiv:2101.07888
EPTCS 333, 2021, pp. 247-260
10.4204/EPTCS.333.17
null
cs.LO cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We introduce Reverse Derivative Ascent: a categorical analogue of gradient based methods for machine learning. Our algorithm is defined at the level of so-called reverse differential categories. It can be used to learn the parameters of models which are expressed as morphisms of such categories. Our motivating exampl...
[ { "created": "Tue, 26 Jan 2021 00:07:20 GMT", "version": "v1" } ]
2021-01-27
[ [ "Wilson", "Paul", "", "University of Southampton" ], [ "Zanasi", "Fabio", "", "University\n College London" ] ]
We introduce Reverse Derivative Ascent: a categorical analogue of gradient based methods for machine learning. Our algorithm is defined at the level of so-called reverse differential categories. It can be used to learn the parameters of models which are expressed as morphisms of such categories. Our motivating example ...
1511.03532
Ali Keles
Ali Keles, Ayturk Keles
IBMMS Decision Support Tool For Management of Bank Telemarketing Campaigns
15 pages, 4 figures, 4 tables, journal in International Journal of Database Management Systems, Vol.7, No.5, October 2015
null
10.5121/ijdms.2015.7501
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Although direct marketing is a good method for banks to utilize in the face of global competition and the financial crisis, it has been shown to exhibit poor performance. However, there are some drawbacks to direct campaigns, such as those related to improving the negative attributes that customers ascribe to banks. ...
[ { "created": "Wed, 11 Nov 2015 15:26:08 GMT", "version": "v1" }, { "created": "Thu, 12 Nov 2015 14:14:01 GMT", "version": "v2" } ]
2015-11-13
[ [ "Keles", "Ali", "" ], [ "Keles", "Ayturk", "" ] ]
Although direct marketing is a good method for banks to utilize in the face of global competition and the financial crisis, it has been shown to exhibit poor performance. However, there are some drawbacks to direct campaigns, such as those related to improving the negative attributes that customers ascribe to banks. To...
1808.08106
Joseph Schuchart
Joseph Schuchart, Daniel Hackenberg, Robert Sch\"one, Thomas Ilsche, Ramkumar Nagappan, Michael K. Patterson
The Shift from Processor Power Consumption to Performance Variations: Fundamental Implications at Scale
null
Computer Science - Research and Development, Vol. 31, pp. 197--205, Nov 2016
10.1007/s00450-016-0327-2
null
cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The Intel Haswell-EP processor generation introduces several major advancements of power control and energy-efficiency features. For computationally intense applications using advanced vector extension (AVX) instructions, the processor cannot continuously operate at full speed but instead reduces its frequency below ...
[ { "created": "Fri, 24 Aug 2018 12:40:03 GMT", "version": "v1" } ]
2018-08-27
[ [ "Schuchart", "Joseph", "" ], [ "Hackenberg", "Daniel", "" ], [ "Schöne", "Robert", "" ], [ "Ilsche", "Thomas", "" ], [ "Nagappan", "Ramkumar", "" ], [ "Patterson", "Michael K.", "" ] ]
The Intel Haswell-EP processor generation introduces several major advancements of power control and energy-efficiency features. For computationally intense applications using advanced vector extension (AVX) instructions, the processor cannot continuously operate at full speed but instead reduces its frequency below th...
2012.08483
Valerio Perrone
Piali Das, Valerio Perrone, Nikita Ivkin, Tanya Bansal, Zohar Karnin, Huibin Shen, Iaroslav Shcherbatyi, Yotam Elor, Wilton Wu, Aida Zolic, Thibaut Lienart, Alex Tang, Amr Ahmed, Jean Baptiste Faddoul, Rodolphe Jenatton, Fela Winkelmolen, Philip Gautier, Leo Dirac, Andre Perunicic, Miroslav Miladinovic, Giovann...
Amazon SageMaker Autopilot: a white box AutoML solution at scale
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
AutoML systems provide a black-box solution to machine learning problems by selecting the right way of processing features, choosing an algorithm and tuning the hyperparameters of the entire pipeline. Although these systems perform well on many datasets, there is still a non-negligible number of datasets for which th...
[ { "created": "Tue, 15 Dec 2020 18:29:04 GMT", "version": "v1" }, { "created": "Wed, 16 Dec 2020 18:51:27 GMT", "version": "v2" } ]
2020-12-17
[ [ "Das", "Piali", "" ], [ "Perrone", "Valerio", "" ], [ "Ivkin", "Nikita", "" ], [ "Bansal", "Tanya", "" ], [ "Karnin", "Zohar", "" ], [ "Shen", "Huibin", "" ], [ "Shcherbatyi", "Iaroslav", "" ], [ "E...
AutoML systems provide a black-box solution to machine learning problems by selecting the right way of processing features, choosing an algorithm and tuning the hyperparameters of the entire pipeline. Although these systems perform well on many datasets, there is still a non-negligible number of datasets for which the ...
1905.06641
Lumin Liu
Lumin Liu, Jun Zhang, S. H. Song, Khaled B. Letaief
Client-Edge-Cloud Hierarchical Federated Learning
6 pages, 4 figures
null
null
null
cs.NI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Federated Learning is a collaborative machine learning framework to train a deep learning model without accessing clients' private data. Previous works assume one central parameter server either at the cloud or at the edge. The cloud server can access more data but with excessive communication overhead and long laten...
[ { "created": "Thu, 16 May 2019 10:23:36 GMT", "version": "v1" }, { "created": "Thu, 31 Oct 2019 14:45:01 GMT", "version": "v2" } ]
2019-11-01
[ [ "Liu", "Lumin", "" ], [ "Zhang", "Jun", "" ], [ "Song", "S. H.", "" ], [ "Letaief", "Khaled B.", "" ] ]
Federated Learning is a collaborative machine learning framework to train a deep learning model without accessing clients' private data. Previous works assume one central parameter server either at the cloud or at the edge. The cloud server can access more data but with excessive communication overhead and long latency...
1810.08313
Jianyu Wang
Jianyu Wang, Gauri Joshi
Adaptive Communication Strategies to Achieve the Best Error-Runtime Trade-off in Local-Update SGD
Accepted to SysML 2019
null
null
null
cs.LG cs.DC stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Large-scale machine learning training, in particular distributed stochastic gradient descent, needs to be robust to inherent system variability such as node straggling and random communication delays. This work considers a distributed training framework where each worker node is allowed to perform local model updates...
[ { "created": "Fri, 19 Oct 2018 00:04:05 GMT", "version": "v1" }, { "created": "Thu, 7 Mar 2019 16:45:02 GMT", "version": "v2" } ]
2019-03-08
[ [ "Wang", "Jianyu", "" ], [ "Joshi", "Gauri", "" ] ]
Large-scale machine learning training, in particular distributed stochastic gradient descent, needs to be robust to inherent system variability such as node straggling and random communication delays. This work considers a distributed training framework where each worker node is allowed to perform local model updates a...
1311.5058
EPTCS
Sebastian Maneth (University of Edinburgh)
Proceedings Second International Workshop on Trends in Tree Automata and Tree Transducers
null
EPTCS 134, 2013
10.4204/EPTCS.134
null
cs.FL cs.LO cs.PL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This volume contains the papers that were presented at the second international workshop on Trends in Tree Automata and Transducers (TTATT 2013) which took place on October 19th, 2013 in Hanoi/Vietnam. The workshop was colocated with the verification conference ATVA. The first edition of the workshop was colocated wi...
[ { "created": "Wed, 20 Nov 2013 14:11:27 GMT", "version": "v1" } ]
2013-11-21
[ [ "Maneth", "Sebastian", "", "University of Edinburgh" ] ]
This volume contains the papers that were presented at the second international workshop on Trends in Tree Automata and Transducers (TTATT 2013) which took place on October 19th, 2013 in Hanoi/Vietnam. The workshop was colocated with the verification conference ATVA. The first edition of the workshop was colocated with...
1711.03588
Carroll Morgan
Annabelle McIver, Carroll Morgan, Benjamin Lucien Kaminski, Joost-Pieter Katoen
A New Proof Rule for Almost-Sure Termination
V1 to appear in PoPL18. This version collects some existing text into new example subsection 5.5 and adds a new example 5.6 and makes further remarks about uncountable branching. The new example 5.6 relates to work on lexicographic termination methods, also to appear in PoPL18 [Agrawal et al, 2018]
null
null
null
cs.PL cs.LO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
An important question for a probabilistic program is whether the probability mass of all its diverging runs is zero, that is that it terminates "almost surely". Proving that can be hard, and this paper presents a new method for doing so; it is expressed in a program logic, and so applies directly to source code. The ...
[ { "created": "Thu, 9 Nov 2017 20:29:00 GMT", "version": "v1" }, { "created": "Tue, 26 Dec 2017 01:09:43 GMT", "version": "v2" } ]
2017-12-27
[ [ "McIver", "Annabelle", "" ], [ "Morgan", "Carroll", "" ], [ "Kaminski", "Benjamin Lucien", "" ], [ "Katoen", "Joost-Pieter", "" ] ]
An important question for a probabilistic program is whether the probability mass of all its diverging runs is zero, that is that it terminates "almost surely". Proving that can be hard, and this paper presents a new method for doing so; it is expressed in a program logic, and so applies directly to source code. The pr...
2209.15149
Alexandros Hollender
Argyrios Deligkas, John Fearnley, Alexandros Hollender, Themistoklis Melissourgos
Pure-Circuit: Strong Inapproximability for PPAD
Improved inapproximability result for approximate NE in polymatrix games
null
null
null
cs.CC cs.GT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The current state-of-the-art methods for showing inapproximability in PPAD arise from the $\varepsilon$-Generalized-Circuit ($\varepsilon$-GCircuit) problem. Rubinstein (2018) showed that there exists a small unknown constant $\varepsilon$ for which $\varepsilon$-GCircuit is PPAD-hard, and subsequent work has shown h...
[ { "created": "Fri, 30 Sep 2022 00:25:04 GMT", "version": "v1" }, { "created": "Fri, 3 Mar 2023 15:41:21 GMT", "version": "v2" } ]
2023-03-06
[ [ "Deligkas", "Argyrios", "" ], [ "Fearnley", "John", "" ], [ "Hollender", "Alexandros", "" ], [ "Melissourgos", "Themistoklis", "" ] ]
The current state-of-the-art methods for showing inapproximability in PPAD arise from the $\varepsilon$-Generalized-Circuit ($\varepsilon$-GCircuit) problem. Rubinstein (2018) showed that there exists a small unknown constant $\varepsilon$ for which $\varepsilon$-GCircuit is PPAD-hard, and subsequent work has shown har...
1804.07899
Markus Freitag
Markus Freitag, Scott Roy
Unsupervised Natural Language Generation with Denoising Autoencoders
Accepted at EMNLP 2018
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Generating text from structured data is important for various tasks such as question answering and dialog systems. We show that in at least one domain, without any supervision and only based on unlabeled text, we are able to build a Natural Language Generation (NLG) system with higher performance than supervised appr...
[ { "created": "Sat, 21 Apr 2018 06:16:57 GMT", "version": "v1" }, { "created": "Fri, 24 Aug 2018 19:53:33 GMT", "version": "v2" } ]
2018-08-28
[ [ "Freitag", "Markus", "" ], [ "Roy", "Scott", "" ] ]
Generating text from structured data is important for various tasks such as question answering and dialog systems. We show that in at least one domain, without any supervision and only based on unlabeled text, we are able to build a Natural Language Generation (NLG) system with higher performance than supervised approa...
2404.10789
Dipkamal Bhusal
Dipkamal Bhusal, Md Tanvirul Alam, Monish K. Veerabhadran, Michael Clifford, Sara Rampazzi, Nidhi Rastogi
PASA: Attack Agnostic Unsupervised Adversarial Detection using Prediction & Attribution Sensitivity Analysis
9th IEEE European Symposium on Security and Privacy
null
null
null
cs.CR cs.AI cs.LG
http://creativecommons.org/licenses/by/4.0/
Deep neural networks for classification are vulnerable to adversarial attacks, where small perturbations to input samples lead to incorrect predictions. This susceptibility, combined with the black-box nature of such networks, limits their adoption in critical applications like autonomous driving. Feature-attribution...
[ { "created": "Fri, 12 Apr 2024 21:22:21 GMT", "version": "v1" } ]
2024-04-18
[ [ "Bhusal", "Dipkamal", "" ], [ "Alam", "Md Tanvirul", "" ], [ "Veerabhadran", "Monish K.", "" ], [ "Clifford", "Michael", "" ], [ "Rampazzi", "Sara", "" ], [ "Rastogi", "Nidhi", "" ] ]
Deep neural networks for classification are vulnerable to adversarial attacks, where small perturbations to input samples lead to incorrect predictions. This susceptibility, combined with the black-box nature of such networks, limits their adoption in critical applications like autonomous driving. Feature-attribution-b...
2308.08302
Ribhu Chopra
Ashish Pratap Singh, Ribhu Chopra
PSA Based Power Control for Cell-Free Massive MIMO under LoS/NLoS Channels
10 pages, 10 figures
null
null
null
cs.IT eess.SP math.IT
http://creativecommons.org/licenses/by/4.0/
A primary design goal of the cell-free~(CF) massive MIMO architecture is to provide uniformly good coverage to all the user equipments~(UEs) connected to the network. However, it has been found that this requirement may not be satisfied in case the channels between the access points~(APs) and the UEs are mixed LoS/NL...
[ { "created": "Wed, 16 Aug 2023 12:05:16 GMT", "version": "v1" } ]
2023-08-17
[ [ "Singh", "Ashish Pratap", "" ], [ "Chopra", "Ribhu", "" ] ]
A primary design goal of the cell-free~(CF) massive MIMO architecture is to provide uniformly good coverage to all the user equipments~(UEs) connected to the network. However, it has been found that this requirement may not be satisfied in case the channels between the access points~(APs) and the UEs are mixed LoS/NLoS...
2106.00934
Nada Almarwani
Nada Almarwani and Mona Diab
Discrete Cosine Transform as Universal Sentence Encoder
to be published in ACL-IJCNLP 2021
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Modern sentence encoders are used to generate dense vector representations that capture the underlying linguistic characteristics for a sequence of words, including phrases, sentences, or paragraphs. These kinds of representations are ideal for training a classifier for an end task such as sentiment analysis, questio...
[ { "created": "Wed, 2 Jun 2021 04:43:54 GMT", "version": "v1" } ]
2021-06-03
[ [ "Almarwani", "Nada", "" ], [ "Diab", "Mona", "" ] ]
Modern sentence encoders are used to generate dense vector representations that capture the underlying linguistic characteristics for a sequence of words, including phrases, sentences, or paragraphs. These kinds of representations are ideal for training a classifier for an end task such as sentiment analysis, question ...
2011.08463
R\'emy Portelas
R\'emy Portelas, Cl\'ement Romac, Katja Hofmann, Pierre-Yves Oudeyer
Meta Automatic Curriculum Learning
This paper extends and generalizes work in arXiv:2004.03168
null
null
null
cs.LG cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A major challenge in the Deep RL (DRL) community is to train agents able to generalize their control policy over situations never seen in training. Training on diverse tasks has been identified as a key ingredient for good generalization, which pushed researchers towards using rich procedural task generation systems ...
[ { "created": "Mon, 16 Nov 2020 14:56:42 GMT", "version": "v1" }, { "created": "Thu, 4 Mar 2021 16:19:46 GMT", "version": "v2" }, { "created": "Wed, 1 Sep 2021 15:41:34 GMT", "version": "v3" } ]
2021-09-02
[ [ "Portelas", "Rémy", "" ], [ "Romac", "Clément", "" ], [ "Hofmann", "Katja", "" ], [ "Oudeyer", "Pierre-Yves", "" ] ]
A major challenge in the Deep RL (DRL) community is to train agents able to generalize their control policy over situations never seen in training. Training on diverse tasks has been identified as a key ingredient for good generalization, which pushed researchers towards using rich procedural task generation systems co...
2302.03640
Junwen Huang
Junwen Huang, Alexey Artemov, Yujin Chen, Shuaifeng Zhi, Kai Xu, Matthias Nie{\ss}ner
SSR-2D: Semantic 3D Scene Reconstruction from 2D Images
null
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Most deep learning approaches to comprehensive semantic modeling of 3D indoor spaces require costly dense annotations in the 3D domain. In this work, we explore a central 3D scene modeling task, namely, semantic scene reconstruction without using any 3D annotations. The key idea of our approach is to design a trainab...
[ { "created": "Tue, 7 Feb 2023 17:47:52 GMT", "version": "v1" }, { "created": "Tue, 21 Feb 2023 20:50:33 GMT", "version": "v2" }, { "created": "Thu, 20 Apr 2023 19:20:30 GMT", "version": "v3" }, { "created": "Wed, 5 Jun 2024 12:02:12 GMT", "version": "v4" } ]
2024-06-06
[ [ "Huang", "Junwen", "" ], [ "Artemov", "Alexey", "" ], [ "Chen", "Yujin", "" ], [ "Zhi", "Shuaifeng", "" ], [ "Xu", "Kai", "" ], [ "Nießner", "Matthias", "" ] ]
Most deep learning approaches to comprehensive semantic modeling of 3D indoor spaces require costly dense annotations in the 3D domain. In this work, we explore a central 3D scene modeling task, namely, semantic scene reconstruction without using any 3D annotations. The key idea of our approach is to design a trainable...
1212.2450
Salem Benferhat
Salem Benferhat, Sylvain Lagrue, Odile Papini
A possibilistic handling of partially ordered information
Appears in Proceedings of the Nineteenth Conference on Uncertainty in Artificial Intelligence (UAI2003)
null
null
UAI-P-2003-PG-29-36
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In a standard possibilistic logic, prioritized information are encoded by means of weighted knowledge base. This paper proposes an extension of possibilistic logic for dealing with partially ordered information. We Show that all basic notions of standard possibilitic logic (sumbsumption, syntactic and semantic infere...
[ { "created": "Fri, 19 Oct 2012 15:03:38 GMT", "version": "v1" } ]
2012-12-12
[ [ "Benferhat", "Salem", "" ], [ "Lagrue", "Sylvain", "" ], [ "Papini", "Odile", "" ] ]
In a standard possibilistic logic, prioritized information are encoded by means of weighted knowledge base. This paper proposes an extension of possibilistic logic for dealing with partially ordered information. We Show that all basic notions of standard possibilitic logic (sumbsumption, syntactic and semantic inferenc...
1801.01615
Hanbyul Joo
Hanbyul Joo, Tomas Simon, Yaser Sheikh
Total Capture: A 3D Deformation Model for Tracking Faces, Hands, and Bodies
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present a unified deformation model for the markerless capture of multiple scales of human movement, including facial expressions, body motion, and hand gestures. An initial model is generated by locally stitching together models of the individual parts of the human body, which we refer to as the "Frankenstein" mo...
[ { "created": "Fri, 5 Jan 2018 02:41:54 GMT", "version": "v1" } ]
2018-01-08
[ [ "Joo", "Hanbyul", "" ], [ "Simon", "Tomas", "" ], [ "Sheikh", "Yaser", "" ] ]
We present a unified deformation model for the markerless capture of multiple scales of human movement, including facial expressions, body motion, and hand gestures. An initial model is generated by locally stitching together models of the individual parts of the human body, which we refer to as the "Frankenstein" mode...
2404.15980
Ali Ebnenasir
Ali Ebnenasir and Kieran Young
Minimizing the Number of Teleportations in Distributed Quantum Computing Using Alloy
null
null
null
null
cs.ET cs.DC quant-ph
http://creativecommons.org/licenses/by-nc-sa/4.0/
This paper presents a novel approach for minimizing the number of teleportations in Distributed Quantum Computing (DQC) using formal methods. Quantum teleportation plays a major role in communicating quantum information. As such, it is desirable to perform as few teleportations as possible when distributing a quantum...
[ { "created": "Wed, 24 Apr 2024 16:55:29 GMT", "version": "v1" } ]
2024-04-25
[ [ "Ebnenasir", "Ali", "" ], [ "Young", "Kieran", "" ] ]
This paper presents a novel approach for minimizing the number of teleportations in Distributed Quantum Computing (DQC) using formal methods. Quantum teleportation plays a major role in communicating quantum information. As such, it is desirable to perform as few teleportations as possible when distributing a quantum a...
2105.00572
Alexis Conneau
Naman Goyal, Jingfei Du, Myle Ott, Giri Anantharaman, Alexis Conneau
Larger-Scale Transformers for Multilingual Masked Language Modeling
4 pages
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
Recent work has demonstrated the effectiveness of cross-lingual language model pretraining for cross-lingual understanding. In this study, we present the results of two larger multilingual masked language models, with 3.5B and 10.7B parameters. Our two new models dubbed XLM-R XL and XLM-R XXL outperform XLM-R by 1.8%...
[ { "created": "Sun, 2 May 2021 23:15:02 GMT", "version": "v1" } ]
2021-05-04
[ [ "Goyal", "Naman", "" ], [ "Du", "Jingfei", "" ], [ "Ott", "Myle", "" ], [ "Anantharaman", "Giri", "" ], [ "Conneau", "Alexis", "" ] ]
Recent work has demonstrated the effectiveness of cross-lingual language model pretraining for cross-lingual understanding. In this study, we present the results of two larger multilingual masked language models, with 3.5B and 10.7B parameters. Our two new models dubbed XLM-R XL and XLM-R XXL outperform XLM-R by 1.8% a...
1803.10815
Piotr Mardziel
Shayak Sen and Piotr Mardziel and Anupam Datta and Matthew Fredrikson
Supervising Feature Influence
null
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Causal influence measures for machine learnt classifiers shed light on the reasons behind classification, and aid in identifying influential input features and revealing their biases. However, such analyses involve evaluating the classifier using datapoints that may be atypical of its training distribution. Standard ...
[ { "created": "Wed, 28 Mar 2018 19:16:39 GMT", "version": "v1" }, { "created": "Sat, 7 Apr 2018 23:46:15 GMT", "version": "v2" } ]
2018-04-10
[ [ "Sen", "Shayak", "" ], [ "Mardziel", "Piotr", "" ], [ "Datta", "Anupam", "" ], [ "Fredrikson", "Matthew", "" ] ]
Causal influence measures for machine learnt classifiers shed light on the reasons behind classification, and aid in identifying influential input features and revealing their biases. However, such analyses involve evaluating the classifier using datapoints that may be atypical of its training distribution. Standard me...
2312.14030
Erik Frisk
Fatemeh Hashemniya, Beno\"it Caillaud, Erik Frisk, Mattias Krysander, Mathias Malandain
Fault Diagnosability Analysis of Multi-Mode Systems
null
null
null
null
cs.LO cs.SY eess.SY
http://creativecommons.org/licenses/by-nc-nd/4.0/
Multi-mode systems can operate in different modes, leading to large numbers of different dynamics. Consequently, applying traditional structural diagnostics to such systems is often untractable. To address this challenge, we present a multi-mode diagnostics algorithm that relies on a multi-mode extension of the Dulma...
[ { "created": "Thu, 21 Dec 2023 17:00:37 GMT", "version": "v1" } ]
2023-12-22
[ [ "Hashemniya", "Fatemeh", "" ], [ "Caillaud", "Benoït", "" ], [ "Frisk", "Erik", "" ], [ "Krysander", "Mattias", "" ], [ "Malandain", "Mathias", "" ] ]
Multi-mode systems can operate in different modes, leading to large numbers of different dynamics. Consequently, applying traditional structural diagnostics to such systems is often untractable. To address this challenge, we present a multi-mode diagnostics algorithm that relies on a multi-mode extension of the Dulmage...
2302.00089
Hussein Hazimeh
Hussein Hazimeh, Natalia Ponomareva
Mind the (optimality) Gap: A Gap-Aware Learning Rate Scheduler for Adversarial Nets
Accepted to AISTATS 2023
null
null
null
cs.LG cs.AI
http://creativecommons.org/licenses/by/4.0/
Adversarial nets have proved to be powerful in various domains including generative modeling (GANs), transfer learning, and fairness. However, successfully training adversarial nets using first-order methods remains a major challenge. Typically, careful choices of the learning rates are needed to maintain the delicat...
[ { "created": "Tue, 31 Jan 2023 20:36:40 GMT", "version": "v1" } ]
2023-02-02
[ [ "Hazimeh", "Hussein", "" ], [ "Ponomareva", "Natalia", "" ] ]
Adversarial nets have proved to be powerful in various domains including generative modeling (GANs), transfer learning, and fairness. However, successfully training adversarial nets using first-order methods remains a major challenge. Typically, careful choices of the learning rates are needed to maintain the delicate ...
2209.01211
Yaping Zhao
Yaping Zhao, Haitian Zheng, Mengqi Ji, Ruqi Huang
Cross-Camera Deep Colorization
12 pages, 6 figures
null
null
null
cs.CV eess.IV
http://creativecommons.org/licenses/by/4.0/
In this paper, we consider the color-plus-mono dual-camera system and propose an end-to-end convolutional neural network to align and fuse images from it in an efficient and cost-effective way. Our method takes cross-domain and cross-scale images as input, and consequently synthesizes HR colorization results to facil...
[ { "created": "Fri, 26 Aug 2022 11:02:14 GMT", "version": "v1" }, { "created": "Wed, 7 Sep 2022 04:00:27 GMT", "version": "v2" } ]
2022-09-08
[ [ "Zhao", "Yaping", "" ], [ "Zheng", "Haitian", "" ], [ "Ji", "Mengqi", "" ], [ "Huang", "Ruqi", "" ] ]
In this paper, we consider the color-plus-mono dual-camera system and propose an end-to-end convolutional neural network to align and fuse images from it in an efficient and cost-effective way. Our method takes cross-domain and cross-scale images as input, and consequently synthesizes HR colorization results to facilit...
2404.06721
Norrathep Rattanavipanon
Norrathep Rattanavipanon and Ivan De Oliveira Nunes
Poisoning Prevention in Federated Learning and Differential Privacy via Stateful Proofs of Execution
null
null
null
null
cs.CR
http://creativecommons.org/licenses/by/4.0/
The rise in IoT-driven distributed data analytics, coupled with increasing privacy concerns, has led to a demand for effective privacy-preserving and federated data collection/model training mechanisms. In response, approaches such as Federated Learning (FL) and Local Differential Privacy (LDP) have been proposed and...
[ { "created": "Wed, 10 Apr 2024 04:18:26 GMT", "version": "v1" }, { "created": "Thu, 11 Apr 2024 12:05:52 GMT", "version": "v2" }, { "created": "Wed, 19 Jun 2024 03:01:31 GMT", "version": "v3" } ]
2024-06-21
[ [ "Rattanavipanon", "Norrathep", "" ], [ "Nunes", "Ivan De Oliveira", "" ] ]
The rise in IoT-driven distributed data analytics, coupled with increasing privacy concerns, has led to a demand for effective privacy-preserving and federated data collection/model training mechanisms. In response, approaches such as Federated Learning (FL) and Local Differential Privacy (LDP) have been proposed and a...
1910.03126
Jiunn-Kai Huang
Jiunn-Kai Huang and Jessy W. Grizzle
Improvements to Target-Based 3D LiDAR to Camera Calibration
null
IEEE Access, vol. 8, 2020, pp. 134101-134110
10.1109/ACCESS.2020.3010734
null
cs.RO cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The homogeneous transformation between a LiDAR and monocular camera is required for sensor fusion tasks, such as SLAM. While determining such a transformation is not considered glamorous in any sense of the word, it is nonetheless crucial for many modern autonomous systems. Indeed, an error of a few degrees in rotati...
[ { "created": "Mon, 7 Oct 2019 23:03:16 GMT", "version": "v1" }, { "created": "Wed, 11 Mar 2020 20:05:04 GMT", "version": "v2" }, { "created": "Sat, 18 Jul 2020 15:07:13 GMT", "version": "v3" } ]
2020-07-30
[ [ "Huang", "Jiunn-Kai", "" ], [ "Grizzle", "Jessy W.", "" ] ]
The homogeneous transformation between a LiDAR and monocular camera is required for sensor fusion tasks, such as SLAM. While determining such a transformation is not considered glamorous in any sense of the word, it is nonetheless crucial for many modern autonomous systems. Indeed, an error of a few degrees in rotation...
1710.07096
Ribana Roscher
Anika Bettge, Ribana Roscher, Susanne Wenzel
Deep Self-taught Learning for Remote Sensing Image Classification
This is a corrected version of the final paper published in the proceedings
Proceedings of the 2017 conference on Big Data from Space
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper addresses the land cover classification task for remote sensing images by deep self-taught learning. Our self-taught learning approach learns suitable feature representations of the input data using sparse representation and undercomplete dictionary learning. We propose a deep learning framework which extr...
[ { "created": "Thu, 19 Oct 2017 11:32:53 GMT", "version": "v1" }, { "created": "Tue, 19 Dec 2017 20:55:12 GMT", "version": "v2" } ]
2017-12-21
[ [ "Bettge", "Anika", "" ], [ "Roscher", "Ribana", "" ], [ "Wenzel", "Susanne", "" ] ]
This paper addresses the land cover classification task for remote sensing images by deep self-taught learning. Our self-taught learning approach learns suitable feature representations of the input data using sparse representation and undercomplete dictionary learning. We propose a deep learning framework which extrac...
cs/0509002
Zsolt I. L\'az\'ar
Zsolt I. L\'az\'ar, Jouke R. Heringa, Bazil P\^arv, Simon W. de Leeuw
Component Based Programming in Scientific Computing: The Viable Approach
null
null
null
null
cs.CE
null
Computational scientists are facing a new era where the old ways of developing and reusing code have to be left behind and a few daring steps are to be made towards new horizons. The present work analyzes the needs that drive this change, the factors that contribute to the inertia of the community and slow the transi...
[ { "created": "Wed, 31 Aug 2005 21:57:04 GMT", "version": "v1" } ]
2021-08-23
[ [ "Lázár", "Zsolt I.", "" ], [ "Heringa", "Jouke R.", "" ], [ "Pârv", "Bazil", "" ], [ "de Leeuw", "Simon W.", "" ] ]
Computational scientists are facing a new era where the old ways of developing and reusing code have to be left behind and a few daring steps are to be made towards new horizons. The present work analyzes the needs that drive this change, the factors that contribute to the inertia of the community and slow the transiti...
1103.4875
Isabelle Stanton
Isabelle Stanton and Ali Pinar
Constructing and Sampling Graphs with a Prescribed Joint Degree Distribution
null
null
null
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
One of the most influential recent results in network analysis is that many natural networks exhibit a power-law or log-normal degree distribution. This has inspired numerous generative models that match this property. However, more recent work has shown that while these generative models do have the right degree dis...
[ { "created": "Thu, 24 Mar 2011 21:05:17 GMT", "version": "v1" }, { "created": "Wed, 31 Aug 2011 18:41:54 GMT", "version": "v2" } ]
2011-09-01
[ [ "Stanton", "Isabelle", "" ], [ "Pinar", "Ali", "" ] ]
One of the most influential recent results in network analysis is that many natural networks exhibit a power-law or log-normal degree distribution. This has inspired numerous generative models that match this property. However, more recent work has shown that while these generative models do have the right degree distr...
1401.7583
Daniel Kulesz
Daniel Kulesz, Jan-Peter Ostberg
Practical Challenges with Spreadsheet Auditing Tools
13 Pages. 3 Detailed Colour Figures, Proc. European Spreadsheet Risks Int. Grp. (EuSpRIG) 2013, ISBN: 978-1-9054045-1-3
null
null
null
cs.SE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Just like other software, spreadsheets can contain significant faults. Static analysis is an accepted and well-established technique in software engineering known for its capability to discover faults. In recent years, a growing number of tool vendors started offering tools that allow casual end-users to run various ...
[ { "created": "Tue, 28 Jan 2014 20:51:32 GMT", "version": "v1" } ]
2014-01-30
[ [ "Kulesz", "Daniel", "" ], [ "Ostberg", "Jan-Peter", "" ] ]
Just like other software, spreadsheets can contain significant faults. Static analysis is an accepted and well-established technique in software engineering known for its capability to discover faults. In recent years, a growing number of tool vendors started offering tools that allow casual end-users to run various st...