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2405.10947
Dinh Tuan Nguyen
Tuan Nguyen, Max Mehltretter, Franz Rottensteiner
Depth-aware Panoptic Segmentation
null
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Panoptic segmentation unifies semantic and instance segmentation and thus delivers a semantic class label and, for so-called thing classes, also an instance label per pixel. The differentiation of distinct objects of the same class with a similar appearance is particularly challenging and frequently causes such objec...
[ { "created": "Thu, 21 Mar 2024 08:06:49 GMT", "version": "v1" } ]
2024-05-21
[ [ "Nguyen", "Tuan", "" ], [ "Mehltretter", "Max", "" ], [ "Rottensteiner", "Franz", "" ] ]
Panoptic segmentation unifies semantic and instance segmentation and thus delivers a semantic class label and, for so-called thing classes, also an instance label per pixel. The differentiation of distinct objects of the same class with a similar appearance is particularly challenging and frequently causes such objects...
2306.00016
Shadi Haj Yahia
Shadi Haj-Yahia, Omar Mansour, Tomer Toledo
Incorporating Domain Knowledge in Deep Neural Networks for Discrete Choice Models
null
null
null
null
cs.LG cs.AI econ.EM
http://creativecommons.org/licenses/by/4.0/
Discrete choice models (DCM) are widely employed in travel demand analysis as a powerful theoretical econometric framework for understanding and predicting choice behaviors. DCMs are formed as random utility models (RUM), with their key advantage of interpretability. However, a core requirement for the estimation of ...
[ { "created": "Tue, 30 May 2023 12:53:55 GMT", "version": "v1" } ]
2023-06-02
[ [ "Haj-Yahia", "Shadi", "" ], [ "Mansour", "Omar", "" ], [ "Toledo", "Tomer", "" ] ]
Discrete choice models (DCM) are widely employed in travel demand analysis as a powerful theoretical econometric framework for understanding and predicting choice behaviors. DCMs are formed as random utility models (RUM), with their key advantage of interpretability. However, a core requirement for the estimation of th...
1209.1406
Patrick Conrad
Patrick R. Conrad and Youssef M. Marzouk
Adaptive Smolyak Pseudospectral Approximations
null
null
null
null
cs.NA math.NA
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Polynomial approximations of computationally intensive models are central to uncertainty quantification. This paper describes an adaptive method for non-intrusive pseudospectral approximation, based on Smolyak's algorithm with generalized sparse grids. We rigorously analyze and extend the non-adaptive method proposed...
[ { "created": "Thu, 6 Sep 2012 20:35:21 GMT", "version": "v1" }, { "created": "Tue, 25 Jun 2013 20:50:25 GMT", "version": "v2" } ]
2013-06-27
[ [ "Conrad", "Patrick R.", "" ], [ "Marzouk", "Youssef M.", "" ] ]
Polynomial approximations of computationally intensive models are central to uncertainty quantification. This paper describes an adaptive method for non-intrusive pseudospectral approximation, based on Smolyak's algorithm with generalized sparse grids. We rigorously analyze and extend the non-adaptive method proposed i...
2006.09090
Walter Morales-Alvarez
Walter Morales Alvarez, Miguel \'Angel de Miguel, Fernando Garc\'ia, Cristina Olaverri-Monreal
Response of Vulnerable Road Users to Visual Information from Autonomous Vehicles in Shared Spaces
Published paper in the IEEE Intelligent Transportation Systems Conference - ITSC 2019
2019 IEEE Intelligent Transportation Systems Conference (ITSC), Auckland, New Zealand, 2019, pp. 3714-3719
10.1109/ITSC.2019.8917501
null
cs.HC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Completely unmanned autonomous vehicles have been anticipated for a while. Initially, these are expected to drive only under certain conditions on some roads, and advanced functionality is required to cope with the ever-increasing challenges of safety. To enhance the public's perception of road safety and trust in ne...
[ { "created": "Tue, 16 Jun 2020 11:54:16 GMT", "version": "v1" }, { "created": "Wed, 17 Jun 2020 10:07:33 GMT", "version": "v2" }, { "created": "Wed, 22 Jul 2020 09:48:54 GMT", "version": "v3" } ]
2020-07-23
[ [ "Alvarez", "Walter Morales", "" ], [ "de Miguel", "Miguel Ángel", "" ], [ "García", "Fernando", "" ], [ "Olaverri-Monreal", "Cristina", "" ] ]
Completely unmanned autonomous vehicles have been anticipated for a while. Initially, these are expected to drive only under certain conditions on some roads, and advanced functionality is required to cope with the ever-increasing challenges of safety. To enhance the public's perception of road safety and trust in new ...
2111.07684
Bo Lyu
Bo Lyu, Shengbo Wang, Shiping Wen, Kaibo Shi, Yin Yang, Lingfang Zeng and Tingwen Huang
AutoGMap: Learning to Map Large-scale Sparse Graphs on Memristive Crossbars
This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible
null
10.1109/TNNLS.2023.3265383
null
cs.LG cs.ET
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The sparse representation of graphs has shown great potential for accelerating the computation of graph applications (e.g., Social Networks, Knowledge Graphs) on traditional computing architectures (CPU, GPU, or TPU). But the exploration of large-scale sparse graph computing on processing-in-memory (PIM) platforms (t...
[ { "created": "Mon, 15 Nov 2021 11:37:47 GMT", "version": "v1" }, { "created": "Tue, 13 Dec 2022 09:15:00 GMT", "version": "v2" }, { "created": "Fri, 3 Mar 2023 04:49:16 GMT", "version": "v3" } ]
2023-06-28
[ [ "Lyu", "Bo", "" ], [ "Wang", "Shengbo", "" ], [ "Wen", "Shiping", "" ], [ "Shi", "Kaibo", "" ], [ "Yang", "Yin", "" ], [ "Zeng", "Lingfang", "" ], [ "Huang", "Tingwen", "" ] ]
The sparse representation of graphs has shown great potential for accelerating the computation of graph applications (e.g., Social Networks, Knowledge Graphs) on traditional computing architectures (CPU, GPU, or TPU). But the exploration of large-scale sparse graph computing on processing-in-memory (PIM) platforms (typ...
2209.01638
Holy Lovenia
Holy Lovenia, Bryan Wilie, Romain Barraud, Samuel Cahyawijaya, Willy Chung, Pascale Fung
Every picture tells a story: Image-grounded controllable stylistic story generation
Accepted in LaTeCH-CLfL 2022 (6th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature), COLING 2022
null
null
null
cs.CL
http://creativecommons.org/licenses/by-sa/4.0/
Generating a short story out of an image is arduous. Unlike image captioning, story generation from an image poses multiple challenges: preserving the story coherence, appropriately assessing the quality of the story, steering the generated story into a certain style, and addressing the scarcity of image-story pair r...
[ { "created": "Sun, 4 Sep 2022 15:07:53 GMT", "version": "v1" }, { "created": "Sun, 11 Sep 2022 06:08:45 GMT", "version": "v2" } ]
2022-09-13
[ [ "Lovenia", "Holy", "" ], [ "Wilie", "Bryan", "" ], [ "Barraud", "Romain", "" ], [ "Cahyawijaya", "Samuel", "" ], [ "Chung", "Willy", "" ], [ "Fung", "Pascale", "" ] ]
Generating a short story out of an image is arduous. Unlike image captioning, story generation from an image poses multiple challenges: preserving the story coherence, appropriately assessing the quality of the story, steering the generated story into a certain style, and addressing the scarcity of image-story pair ref...
1206.4952
Nesreen Ahmed
Nesreen K. Ahmed, Jennifer Neville, Ramana Kompella
Space-Efficient Sampling from Social Activity Streams
BigMine 2012
null
null
null
cs.SI cs.DB physics.soc-ph stat.AP
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In order to efficiently study the characteristics of network domains and support development of network systems (e.g. algorithms, protocols that operate on networks), it is often necessary to sample a representative subgraph from a large complex network. Although recent subgraph sampling methods have been shown to wo...
[ { "created": "Wed, 20 Jun 2012 04:55:20 GMT", "version": "v1" } ]
2012-06-22
[ [ "Ahmed", "Nesreen K.", "" ], [ "Neville", "Jennifer", "" ], [ "Kompella", "Ramana", "" ] ]
In order to efficiently study the characteristics of network domains and support development of network systems (e.g. algorithms, protocols that operate on networks), it is often necessary to sample a representative subgraph from a large complex network. Although recent subgraph sampling methods have been shown to work...
2101.08122
Devis Tuia
Marrit Leenstra, Diego Marcos, Francesca Bovolo, Devis Tuia
Self-supervised pre-training enhances change detection in Sentinel-2 imagery
Presented at the Pattern Recognition and Remote Sensing (PRRS) workshop in ICPR, 2021
Part of the Lecture Notes in Computer Science book series (LNCS, volume 12667), 2021
null
null
cs.CV eess.IV
http://creativecommons.org/licenses/by-nc-sa/4.0/
While annotated images for change detection using satellite imagery are scarce and costly to obtain, there is a wealth of unlabeled images being generated every day. In order to leverage these data to learn an image representation more adequate for change detection, we explore methods that exploit the temporal consis...
[ { "created": "Wed, 20 Jan 2021 13:47:25 GMT", "version": "v1" }, { "created": "Sun, 11 Apr 2021 20:43:10 GMT", "version": "v2" } ]
2021-04-13
[ [ "Leenstra", "Marrit", "" ], [ "Marcos", "Diego", "" ], [ "Bovolo", "Francesca", "" ], [ "Tuia", "Devis", "" ] ]
While annotated images for change detection using satellite imagery are scarce and costly to obtain, there is a wealth of unlabeled images being generated every day. In order to leverage these data to learn an image representation more adequate for change detection, we explore methods that exploit the temporal consiste...
2011.05704
Ragav Sachdeva
Ragav Sachdeva, Filipe R. Cordeiro, Vasileios Belagiannis, Ian Reid, Gustavo Carneiro
EvidentialMix: Learning with Combined Open-set and Closed-set Noisy Labels
Paper accepted at WACV'21: Winter Conference on Applications of Computer Vision
null
null
null
cs.LG cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The efficacy of deep learning depends on large-scale data sets that have been carefully curated with reliable data acquisition and annotation processes. However, acquiring such large-scale data sets with precise annotations is very expensive and time-consuming, and the cheap alternatives often yield data sets that ha...
[ { "created": "Wed, 11 Nov 2020 11:15:32 GMT", "version": "v1" } ]
2020-11-12
[ [ "Sachdeva", "Ragav", "" ], [ "Cordeiro", "Filipe R.", "" ], [ "Belagiannis", "Vasileios", "" ], [ "Reid", "Ian", "" ], [ "Carneiro", "Gustavo", "" ] ]
The efficacy of deep learning depends on large-scale data sets that have been carefully curated with reliable data acquisition and annotation processes. However, acquiring such large-scale data sets with precise annotations is very expensive and time-consuming, and the cheap alternatives often yield data sets that have...
2108.12229
Iftitahu Ni'mah
Iftitahu Ni'mah, Meng Fang, Vlado Menkovski, Mykola Pechenizkiy
ProtoInfoMax: Prototypical Networks with Mutual Information Maximization for Out-of-Domain Detection
This manuscript will be available in ACL Anthology section EMNLP2021-Findings papers
Findings of the Association for Computational Linguistics: EMNLP 2021
10.18653/v1/2021.findings-emnlp.138
2021.findings-emnlp.138
cs.CL
http://creativecommons.org/licenses/by/4.0/
The ability to detect Out-of-Domain (OOD) inputs has been a critical requirement in many real-world NLP applications. For example, intent classification in dialogue systems. The reason is that the inclusion of unsupported OOD inputs may lead to catastrophic failure of systems. However, it remains an empirical questio...
[ { "created": "Fri, 27 Aug 2021 11:55:34 GMT", "version": "v1" }, { "created": "Mon, 30 Aug 2021 12:24:27 GMT", "version": "v2" }, { "created": "Fri, 3 Sep 2021 08:38:03 GMT", "version": "v3" }, { "created": "Wed, 8 Sep 2021 07:53:33 GMT", "version": "v4" }, { "cre...
2022-01-20
[ [ "Ni'mah", "Iftitahu", "" ], [ "Fang", "Meng", "" ], [ "Menkovski", "Vlado", "" ], [ "Pechenizkiy", "Mykola", "" ] ]
The ability to detect Out-of-Domain (OOD) inputs has been a critical requirement in many real-world NLP applications. For example, intent classification in dialogue systems. The reason is that the inclusion of unsupported OOD inputs may lead to catastrophic failure of systems. However, it remains an empirical question ...
2104.03453
Chidera Biringa
Chidera Biringa, Gokhan Kul
Automated User Experience Testing through Multi-Dimensional Performance Impact Analysis
4 pages, 2 figures, Proceedings of the ACM/IEEE 2nd International Conference on Automation of Software Test
null
null
null
cs.SE cs.LG
http://creativecommons.org/licenses/by/4.0/
Although there are many automated software testing suites, they usually focus on unit, system, and interface testing. However, especially software updates such as new security features have the potential to diminish user experience. In this paper, we propose a novel automated user experience testing methodology that ...
[ { "created": "Thu, 8 Apr 2021 01:18:01 GMT", "version": "v1" } ]
2021-04-09
[ [ "Biringa", "Chidera", "" ], [ "Kul", "Gokhan", "" ] ]
Although there are many automated software testing suites, they usually focus on unit, system, and interface testing. However, especially software updates such as new security features have the potential to diminish user experience. In this paper, we propose a novel automated user experience testing methodology that le...
1803.07274
Rajen Chatterjee
Matteo Negri, Marco Turchi, Rajen Chatterjee, Nicola Bertoldi
eSCAPE: a Large-scale Synthetic Corpus for Automatic Post-Editing
Accepted at LREC 2018
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Training models for the automatic correction of machine-translated text usually relies on data consisting of (source, MT, human post- edit) triplets providing, for each source sentence, examples of translation errors with the corresponding corrections made by a human post-editor. Ideally, a large amount of data of th...
[ { "created": "Tue, 20 Mar 2018 06:59:27 GMT", "version": "v1" } ]
2018-03-21
[ [ "Negri", "Matteo", "" ], [ "Turchi", "Marco", "" ], [ "Chatterjee", "Rajen", "" ], [ "Bertoldi", "Nicola", "" ] ]
Training models for the automatic correction of machine-translated text usually relies on data consisting of (source, MT, human post- edit) triplets providing, for each source sentence, examples of translation errors with the corresponding corrections made by a human post-editor. Ideally, a large amount of data of this...
2404.02530
Jordan Vice
Jordan Vice, Naveed Akhtar, Richard Hartley, and Ajmal Mian
Severity Controlled Text-to-Image Generative Model Bias Manipulation
This research was supported by National Intelligence and Security Discovery Research Grants (project# NS220100007), funded by the Department of Defence Australia
null
null
null
cs.CV cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Text-to-image (T2I) generative models are gaining wide popularity, especially in public domains. However, their intrinsic bias and potential malicious manipulations remain under-explored. Charting the susceptibility of T2I models to such manipulation, we first expose the new possibility of a dynamic and computational...
[ { "created": "Wed, 3 Apr 2024 07:33:30 GMT", "version": "v1" } ]
2024-04-04
[ [ "Vice", "Jordan", "" ], [ "Akhtar", "Naveed", "" ], [ "Hartley", "Richard", "" ], [ "Mian", "Ajmal", "" ] ]
Text-to-image (T2I) generative models are gaining wide popularity, especially in public domains. However, their intrinsic bias and potential malicious manipulations remain under-explored. Charting the susceptibility of T2I models to such manipulation, we first expose the new possibility of a dynamic and computationally...
1808.02254
Sara Kardani Moghaddam
Sara Kardani-Moghaddam, Rajkumar Buyya, and Kotagiri Ramamohanarao
Performance-Aware Management of Cloud Resources: A Taxonomy and Future Directions
null
null
null
null
cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Dynamic nature of the cloud environment has made distributed resource management process a challenge for cloud service providers. The importance of maintaining the quality of service in accordance with customer expectations as well as the highly dynamic nature of cloud-hosted applications add new levels of complexity...
[ { "created": "Tue, 7 Aug 2018 08:27:02 GMT", "version": "v1" } ]
2018-08-08
[ [ "Kardani-Moghaddam", "Sara", "" ], [ "Buyya", "Rajkumar", "" ], [ "Ramamohanarao", "Kotagiri", "" ] ]
Dynamic nature of the cloud environment has made distributed resource management process a challenge for cloud service providers. The importance of maintaining the quality of service in accordance with customer expectations as well as the highly dynamic nature of cloud-hosted applications add new levels of complexity t...
1409.2232
Jim Jing-Yan Wang
Jim Jing-Yan Wang, Xuefeng Cui, Ge Yu, Lili Guo, Xin Gao
When coding meets ranking: A joint framework based on local learning
null
null
null
null
cs.CV cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Sparse coding, which represents a data point as a sparse reconstruction code with regard to a dictionary, has been a popular data representation method. Meanwhile, in database retrieval problems, learning the ranking scores from data points plays an important role. Up to now, these two problems have always been consi...
[ { "created": "Mon, 8 Sep 2014 08:10:37 GMT", "version": "v1" }, { "created": "Wed, 2 Nov 2016 07:33:51 GMT", "version": "v2" } ]
2016-11-03
[ [ "Wang", "Jim Jing-Yan", "" ], [ "Cui", "Xuefeng", "" ], [ "Yu", "Ge", "" ], [ "Guo", "Lili", "" ], [ "Gao", "Xin", "" ] ]
Sparse coding, which represents a data point as a sparse reconstruction code with regard to a dictionary, has been a popular data representation method. Meanwhile, in database retrieval problems, learning the ranking scores from data points plays an important role. Up to now, these two problems have always been conside...
2310.00616
Yijiang Li
Yijiang Li, Ying Gao and Haohan Wang
Understanding Adversarial Transferability in Federated Learning
10 pages of the main paper. 21 pages in total
null
null
null
cs.LG cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We investigate the robustness and security issues from a novel and practical setting: a group of malicious clients has impacted the model during training by disguising their identities and acting as benign clients, and only revealing their adversary position after the training to conduct transferable adversarial atta...
[ { "created": "Sun, 1 Oct 2023 08:35:46 GMT", "version": "v1" } ]
2023-10-03
[ [ "Li", "Yijiang", "" ], [ "Gao", "Ying", "" ], [ "Wang", "Haohan", "" ] ]
We investigate the robustness and security issues from a novel and practical setting: a group of malicious clients has impacted the model during training by disguising their identities and acting as benign clients, and only revealing their adversary position after the training to conduct transferable adversarial attack...
2405.16376
Chuanhao Li
Chuanhao Li, Runhan Yang, Tiankai Li, Milad Bafarassat, Kourosh Sharifi, Dirk Bergemann, and Zhuoran Yang
STRIDE: A Tool-Assisted LLM Agent Framework for Strategic and Interactive Decision-Making
39 pages, 4 figures
null
null
null
cs.CL cs.GT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Large Language Models (LLMs) like GPT-4 have revolutionized natural language processing, showing remarkable linguistic proficiency and reasoning capabilities. However, their application in strategic multi-agent decision-making environments is hampered by significant limitations including poor mathematical reasoning, ...
[ { "created": "Sat, 25 May 2024 23:25:10 GMT", "version": "v1" }, { "created": "Tue, 28 May 2024 01:21:19 GMT", "version": "v2" } ]
2024-05-29
[ [ "Li", "Chuanhao", "" ], [ "Yang", "Runhan", "" ], [ "Li", "Tiankai", "" ], [ "Bafarassat", "Milad", "" ], [ "Sharifi", "Kourosh", "" ], [ "Bergemann", "Dirk", "" ], [ "Yang", "Zhuoran", "" ] ]
Large Language Models (LLMs) like GPT-4 have revolutionized natural language processing, showing remarkable linguistic proficiency and reasoning capabilities. However, their application in strategic multi-agent decision-making environments is hampered by significant limitations including poor mathematical reasoning, di...
cs/9809114
Heribert Vollmer
Clemens Lautemann and Pierre McKenzie and Thomas Schwentick and Heribert Vollmer
The descriptive complexity approach to LOGCFL
10 pages, 1 figure
null
null
null
cs.CC
null
Building upon the known generalized-quantifier-based first-order characterization of LOGCFL, we lay the groundwork for a deeper investigation. Specifically, we examine subclasses of LOGCFL arising from varying the arity and nesting of groupoidal quantifiers. Our work extends the elaborate theory relating monoidal qua...
[ { "created": "Mon, 28 Sep 1998 07:57:32 GMT", "version": "v1" } ]
2007-05-23
[ [ "Lautemann", "Clemens", "" ], [ "McKenzie", "Pierre", "" ], [ "Schwentick", "Thomas", "" ], [ "Vollmer", "Heribert", "" ] ]
Building upon the known generalized-quantifier-based first-order characterization of LOGCFL, we lay the groundwork for a deeper investigation. Specifically, we examine subclasses of LOGCFL arising from varying the arity and nesting of groupoidal quantifiers. Our work extends the elaborate theory relating monoidal quant...
2008.07284
Eiji Uchibe
Eiji Uchibe and Kenji Doya
Forward and inverse reinforcement learning sharing network weights and hyperparameters
Accepted for publication in the Neural Networks
Neural Networks, December 2021, Pages 138-153
10.1016/j.neunet.2021.08.017
null
cs.LG cs.AI cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper proposes model-free imitation learning named Entropy-Regularized Imitation Learning (ERIL) that minimizes the reverse Kullback-Leibler (KL) divergence. ERIL combines forward and inverse reinforcement learning (RL) under the framework of an entropy-regularized Markov decision process. An inverse RL step com...
[ { "created": "Mon, 17 Aug 2020 13:12:44 GMT", "version": "v1" }, { "created": "Tue, 31 May 2022 11:07:58 GMT", "version": "v2" } ]
2022-06-01
[ [ "Uchibe", "Eiji", "" ], [ "Doya", "Kenji", "" ] ]
This paper proposes model-free imitation learning named Entropy-Regularized Imitation Learning (ERIL) that minimizes the reverse Kullback-Leibler (KL) divergence. ERIL combines forward and inverse reinforcement learning (RL) under the framework of an entropy-regularized Markov decision process. An inverse RL step compu...
1703.03305
Umut G\"u\c{c}l\"u
Umut G\"u\c{c}l\"u, Ya\u{g}mur G\"u\c{c}l\"ut\"urk, Meysam Madadi, Sergio Escalera, Xavier Bar\'o, Jordi Gonz\'alez, Rob van Lier, Marcel A. J. van Gerven
End-to-end semantic face segmentation with conditional random fields as convolutional, recurrent and adversarial networks
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recent years have seen a sharp increase in the number of related yet distinct advances in semantic segmentation. Here, we tackle this problem by leveraging the respective strengths of these advances. That is, we formulate a conditional random field over a four-connected graph as end-to-end trainable convolutional and...
[ { "created": "Thu, 9 Mar 2017 15:48:22 GMT", "version": "v1" } ]
2017-03-10
[ [ "Güçlü", "Umut", "" ], [ "Güçlütürk", "Yağmur", "" ], [ "Madadi", "Meysam", "" ], [ "Escalera", "Sergio", "" ], [ "Baró", "Xavier", "" ], [ "González", "Jordi", "" ], [ "van Lier", "Rob", "" ], [ "v...
Recent years have seen a sharp increase in the number of related yet distinct advances in semantic segmentation. Here, we tackle this problem by leveraging the respective strengths of these advances. That is, we formulate a conditional random field over a four-connected graph as end-to-end trainable convolutional and r...
2011.02601
Valentin Buchhold
Valentin Buchhold, Peter Sanders, Dorothea Wagner
Fast, Exact and Scalable Dynamic Ridesharing
Previous version augmented in several ways
null
null
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We study the problem of servicing a set of ride requests by dispatching a set of shared vehicles, which is faced by ridesharing companies such as Uber and Lyft. Solving this problem at a large scale might be crucial in the future for effectively using large fleets of autonomous vehicles. Since finding a solution for ...
[ { "created": "Thu, 5 Nov 2020 01:20:51 GMT", "version": "v1" }, { "created": "Thu, 17 Jun 2021 22:00:39 GMT", "version": "v2" } ]
2021-06-21
[ [ "Buchhold", "Valentin", "" ], [ "Sanders", "Peter", "" ], [ "Wagner", "Dorothea", "" ] ]
We study the problem of servicing a set of ride requests by dispatching a set of shared vehicles, which is faced by ridesharing companies such as Uber and Lyft. Solving this problem at a large scale might be crucial in the future for effectively using large fleets of autonomous vehicles. Since finding a solution for th...
2403.11570
Yuhe Liu
Yuhe Liu, Mengxue Kang, Zengchang Qin, Xiangxiang Chu
LogicalDefender: Discovering, Extracting, and Utilizing Common-Sense Knowledge
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Large text-to-image models have achieved astonishing performance in synthesizing diverse and high-quality images guided by texts. With detail-oriented conditioning control, even finer-grained spatial control can be achieved. However, some generated images still appear unreasonable, even with plentiful object features...
[ { "created": "Mon, 18 Mar 2024 08:43:42 GMT", "version": "v1" } ]
2024-03-19
[ [ "Liu", "Yuhe", "" ], [ "Kang", "Mengxue", "" ], [ "Qin", "Zengchang", "" ], [ "Chu", "Xiangxiang", "" ] ]
Large text-to-image models have achieved astonishing performance in synthesizing diverse and high-quality images guided by texts. With detail-oriented conditioning control, even finer-grained spatial control can be achieved. However, some generated images still appear unreasonable, even with plentiful object features a...
1604.08382
Frederik Ruelens
Bert J. Claessens and Peter Vrancx and Frederik Ruelens
Convolutional Neural Networks For Automatic State-Time Feature Extraction in Reinforcement Learning Applied to Residential Load Control
Submitted to Transactions on Smart Grid
null
null
null
cs.LG cs.SY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Direct load control of a heterogeneous cluster of residential demand flexibility sources is a high-dimensional control problem with partial observability. This work proposes a novel approach that uses a convolutional neural network to extract hidden state-time features to mitigate the curse of partial observability. ...
[ { "created": "Thu, 28 Apr 2016 11:53:47 GMT", "version": "v1" }, { "created": "Tue, 11 Oct 2016 15:52:42 GMT", "version": "v2" } ]
2016-10-12
[ [ "Claessens", "Bert J.", "" ], [ "Vrancx", "Peter", "" ], [ "Ruelens", "Frederik", "" ] ]
Direct load control of a heterogeneous cluster of residential demand flexibility sources is a high-dimensional control problem with partial observability. This work proposes a novel approach that uses a convolutional neural network to extract hidden state-time features to mitigate the curse of partial observability. Mo...
2305.16852
Benjamin Towle
Benjamin Towle and Ke Zhou
Model-Based Simulation for Optimising Smart Reply
This paper has been accepted to appear at ACL 2023
null
null
null
cs.CL cs.AI cs.LG
http://creativecommons.org/licenses/by/4.0/
Smart Reply (SR) systems present a user with a set of replies, of which one can be selected in place of having to type out a response. To perform well at this task, a system should be able to effectively present the user with a diverse set of options, to maximise the chance that at least one of them conveys the user'...
[ { "created": "Fri, 26 May 2023 12:04:33 GMT", "version": "v1" } ]
2023-05-29
[ [ "Towle", "Benjamin", "" ], [ "Zhou", "Ke", "" ] ]
Smart Reply (SR) systems present a user with a set of replies, of which one can be selected in place of having to type out a response. To perform well at this task, a system should be able to effectively present the user with a diverse set of options, to maximise the chance that at least one of them conveys the user's ...
1310.2001
Ryo Nomura
Ryo Nomura
Overflow Probability of Variable-length Codes with Codeword Cost
null
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Lossless variable-length source coding with codeword cost is considered for general sources. The problem setting, where we impose on unequal costs on code symbols, is called the variable-length coding with codeword cost. In this problem, the infimum of average codeword cost have been determined for general sources. O...
[ { "created": "Tue, 8 Oct 2013 04:44:51 GMT", "version": "v1" } ]
2013-10-09
[ [ "Nomura", "Ryo", "" ] ]
Lossless variable-length source coding with codeword cost is considered for general sources. The problem setting, where we impose on unequal costs on code symbols, is called the variable-length coding with codeword cost. In this problem, the infimum of average codeword cost have been determined for general sources. On ...
2304.01064
Chenyang Qi
Chenyang Qi, Xin Yang, Ka Leong Cheng, Ying-Cong Chen, Qifeng Chen
Real-time 6K Image Rescaling with Rate-distortion Optimization
Accepted by CVPR 2023; Github Repository: https://github.com/AbnerVictor/HyperThumbnail
null
null
null
cs.CV eess.IV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Contemporary image rescaling aims at embedding a high-resolution (HR) image into a low-resolution (LR) thumbnail image that contains embedded information for HR image reconstruction. Unlike traditional image super-resolution, this enables high-fidelity HR image restoration faithful to the original one, given the embe...
[ { "created": "Mon, 3 Apr 2023 15:21:56 GMT", "version": "v1" }, { "created": "Fri, 19 May 2023 12:34:17 GMT", "version": "v2" } ]
2023-05-22
[ [ "Qi", "Chenyang", "" ], [ "Yang", "Xin", "" ], [ "Cheng", "Ka Leong", "" ], [ "Chen", "Ying-Cong", "" ], [ "Chen", "Qifeng", "" ] ]
Contemporary image rescaling aims at embedding a high-resolution (HR) image into a low-resolution (LR) thumbnail image that contains embedded information for HR image reconstruction. Unlike traditional image super-resolution, this enables high-fidelity HR image restoration faithful to the original one, given the embedd...
2305.06572
Hailiang Zhao
Hailiang Zhao, Shuiguang Deng, Zhengzhe Xiang, Xueqiang Yan, Jianwei Yin, Schahram Dustdar, Albert Y. Zomaya
Scheduling Multi-Server Jobs with Sublinear Regrets via Online Learning
null
null
null
null
cs.DC
http://creativecommons.org/licenses/by-nc-nd/4.0/
Multi-server jobs that request multiple computing resources and hold onto them during their execution dominate modern computing clusters. When allocating the multi-type resources to several co-located multi-server jobs simultaneously in online settings, it is difficult to make the tradeoff between the parallel comput...
[ { "created": "Thu, 11 May 2023 05:17:02 GMT", "version": "v1" }, { "created": "Sat, 5 Aug 2023 09:13:33 GMT", "version": "v2" } ]
2023-08-08
[ [ "Zhao", "Hailiang", "" ], [ "Deng", "Shuiguang", "" ], [ "Xiang", "Zhengzhe", "" ], [ "Yan", "Xueqiang", "" ], [ "Yin", "Jianwei", "" ], [ "Dustdar", "Schahram", "" ], [ "Zomaya", "Albert Y.", "" ] ]
Multi-server jobs that request multiple computing resources and hold onto them during their execution dominate modern computing clusters. When allocating the multi-type resources to several co-located multi-server jobs simultaneously in online settings, it is difficult to make the tradeoff between the parallel computat...
2403.01089
Nicole Hashemi
Nicholus R. Clinkinbeard, Reza Montazami, Nicole N. Hashemi
Accelerating Hydrodynamic Fabrication of Microstructures using Deep Neural Networks
null
null
null
null
cs.CE
http://creativecommons.org/licenses/by-nc-nd/4.0/
Manufacturing of microstructures using a microfluidic device is a largely empirical effort due to the multi-physical nature of the fabrication process. As such, models are desired that will predict microstructure performance characteristics (e.g., size, porosity, and stiffness) based on known inputs, such as sheath a...
[ { "created": "Sat, 2 Mar 2024 04:17:17 GMT", "version": "v1" } ]
2024-03-05
[ [ "Clinkinbeard", "Nicholus R.", "" ], [ "Montazami", "Reza", "" ], [ "Hashemi", "Nicole N.", "" ] ]
Manufacturing of microstructures using a microfluidic device is a largely empirical effort due to the multi-physical nature of the fabrication process. As such, models are desired that will predict microstructure performance characteristics (e.g., size, porosity, and stiffness) based on known inputs, such as sheath and...
2011.14816
Christian Cachin
Ignacio Amores-Sesar, Christian Cachin, Jovana Mi\'ci\'c
Security Analysis of Ripple Consensus
null
null
null
null
cs.DC cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The Ripple network is one of the most prominent blockchain platforms and its native XRP token currently has one of the highest cryptocurrency market capitalizations. The Ripple consensus protocol powers this network and is generally considered to a Byzantine fault-tolerant agreement protocol, which can reach consensu...
[ { "created": "Mon, 30 Nov 2020 14:11:55 GMT", "version": "v1" } ]
2020-12-01
[ [ "Amores-Sesar", "Ignacio", "" ], [ "Cachin", "Christian", "" ], [ "Mićić", "Jovana", "" ] ]
The Ripple network is one of the most prominent blockchain platforms and its native XRP token currently has one of the highest cryptocurrency market capitalizations. The Ripple consensus protocol powers this network and is generally considered to a Byzantine fault-tolerant agreement protocol, which can reach consensus ...
2402.10693
Alexandre Verine
Florian Le Bronnec, Alexandre Verine, Benjamin Negrevergne, Yann Chevaleyre, Alexandre Allauzen
Exploring Precision and Recall to assess the quality and diversity of LLMs
21 pages, 15 figures, ACL 2024 Main
null
null
null
cs.CL cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We introduce a novel evaluation framework for Large Language Models (LLMs) such as \textsc{Llama-2} and \textsc{Mistral}, focusing on importing Precision and Recall metrics from image generation to text generation. This approach allows for a nuanced assessment of the quality and diversity of generated text without th...
[ { "created": "Fri, 16 Feb 2024 13:53:26 GMT", "version": "v1" }, { "created": "Wed, 28 Feb 2024 10:12:34 GMT", "version": "v2" }, { "created": "Tue, 4 Jun 2024 11:33:27 GMT", "version": "v3" } ]
2024-06-05
[ [ "Bronnec", "Florian Le", "" ], [ "Verine", "Alexandre", "" ], [ "Negrevergne", "Benjamin", "" ], [ "Chevaleyre", "Yann", "" ], [ "Allauzen", "Alexandre", "" ] ]
We introduce a novel evaluation framework for Large Language Models (LLMs) such as \textsc{Llama-2} and \textsc{Mistral}, focusing on importing Precision and Recall metrics from image generation to text generation. This approach allows for a nuanced assessment of the quality and diversity of generated text without the ...
1706.08007
Benjamin Cosman
Benjamin Cosman, Ranjit Jhala
Local Refinement Typing
null
null
null
null
cs.PL
http://creativecommons.org/licenses/by/4.0/
We introduce the Fusion algorithm for local refinement type inference, yielding a new SMT-based method for verifying programs with polymorphic data types and higher-order functions. Fusion is concise as the programmer need only write signatures for (externally exported) top-level functions and places with cyclic (rec...
[ { "created": "Sat, 24 Jun 2017 22:06:23 GMT", "version": "v1" } ]
2017-06-27
[ [ "Cosman", "Benjamin", "" ], [ "Jhala", "Ranjit", "" ] ]
We introduce the Fusion algorithm for local refinement type inference, yielding a new SMT-based method for verifying programs with polymorphic data types and higher-order functions. Fusion is concise as the programmer need only write signatures for (externally exported) top-level functions and places with cyclic (recur...
1507.01490
Michele Borassi
Michele Borassi, Pierluigi Crescenzi, Andrea Marino
Fast and Simple Computation of Top-k Closeness Centralities
null
null
null
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Closeness is an important centrality measure widely used in the analysis of real-world complex networks. In particular, the problem of selecting the k most central nodes with respect to this measure has been deeply analyzed in the last decade. However, even for not very large networks, this problem is computationally...
[ { "created": "Mon, 6 Jul 2015 14:58:24 GMT", "version": "v1" } ]
2015-07-07
[ [ "Borassi", "Michele", "" ], [ "Crescenzi", "Pierluigi", "" ], [ "Marino", "Andrea", "" ] ]
Closeness is an important centrality measure widely used in the analysis of real-world complex networks. In particular, the problem of selecting the k most central nodes with respect to this measure has been deeply analyzed in the last decade. However, even for not very large networks, this problem is computationally i...
2403.09997
Xiang Dai
Xiang Dai and Sarvnaz Karimi and Nathan O'Callaghan
Identifying Health Risks from Family History: A Survey of Natural Language Processing Techniques
Under Review
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
Electronic health records include information on patients' status and medical history, which could cover the history of diseases and disorders that could be hereditary. One important use of family history information is in precision health, where the goal is to keep the population healthy with preventative measures. ...
[ { "created": "Fri, 15 Mar 2024 03:43:07 GMT", "version": "v1" } ]
2024-03-18
[ [ "Dai", "Xiang", "" ], [ "Karimi", "Sarvnaz", "" ], [ "O'Callaghan", "Nathan", "" ] ]
Electronic health records include information on patients' status and medical history, which could cover the history of diseases and disorders that could be hereditary. One important use of family history information is in precision health, where the goal is to keep the population healthy with preventative measures. Na...
1211.4091
EPTCS
Margarita Antonaki (University of Cyprus), Anna Philippou (University of Cyprus)
A Process Calculus for Spatially-explicit Ecological Models
In Proceedings MeCBIC 2012, arXiv:1211.3476
EPTCS 100, 2012, pp. 14-28
10.4204/EPTCS.100.2
null
cs.LO q-bio.PE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We propose PALPS, a Process Algebra with Locations for Population Systems. PALPS allows us to produce spatially-explicit, individual-based models and to reason about their behavior. Our calculus has two levels: at the first level we may define the behavior of an individual of a population while, at the second level, ...
[ { "created": "Sat, 17 Nov 2012 09:14:41 GMT", "version": "v1" } ]
2012-11-20
[ [ "Antonaki", "Margarita", "", "University of Cyprus" ], [ "Philippou", "Anna", "", "University\n of Cyprus" ] ]
We propose PALPS, a Process Algebra with Locations for Population Systems. PALPS allows us to produce spatially-explicit, individual-based models and to reason about their behavior. Our calculus has two levels: at the first level we may define the behavior of an individual of a population while, at the second level, we...
2112.12790
Giampaolo Bella
Giampaolo Bella
Out to Explore the Cybersecurity Planet
null
null
10.1108/JIC-05-2019-0127
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Security ceremonies still fail despite decades of efforts by researchers and practitioners. Attacks are often a cunning amalgam of exploits for technical systems and of forms of human behaviour. For example, this is the case with the recent news headline of a large-scale attack against Electrum Bitcoin wallets, which...
[ { "created": "Sat, 18 Dec 2021 11:52:38 GMT", "version": "v1" } ]
2021-12-28
[ [ "Bella", "Giampaolo", "" ] ]
Security ceremonies still fail despite decades of efforts by researchers and practitioners. Attacks are often a cunning amalgam of exploits for technical systems and of forms of human behaviour. For example, this is the case with the recent news headline of a large-scale attack against Electrum Bitcoin wallets, which m...
2112.02657
Jashanpreet Singh Sraw
Jashanpreet Singh Sraw and Deepak M C
Using Convolutional Neural Networks for fault analysis and alleviation in accelerator systems
null
null
null
null
cs.LG
http://creativecommons.org/licenses/by/4.0/
Today, Neural Networks are the basis of breakthroughs in virtually every technical domain. Their application to accelerators has recently resulted in better performance and efficiency in these systems. At the same time, the increasing hardware failures due to the latest (shrinked) semiconductor technology needs to be...
[ { "created": "Sun, 5 Dec 2021 19:18:42 GMT", "version": "v1" } ]
2021-12-07
[ [ "Sraw", "Jashanpreet Singh", "" ], [ "C", "Deepak M", "" ] ]
Today, Neural Networks are the basis of breakthroughs in virtually every technical domain. Their application to accelerators has recently resulted in better performance and efficiency in these systems. At the same time, the increasing hardware failures due to the latest (shrinked) semiconductor technology needs to be a...
2403.11034
Mithun Goutham
Mithun Goutham and Stephanie Stockar
Resilient Fleet Management for Energy-Aware Intra-Factory Logistics
This manuscript was accepted to the 2024 American Control Conference (ACC) which will be held Wednesday through Friday, July 10-12, 2024 in Toronto, ON, Canada. arXiv admin note: text overlap with arXiv:2304.11444
null
null
null
cs.RO cs.MA cs.SY eess.SY
http://creativecommons.org/licenses/by/4.0/
This paper presents a novel fleet management strategy for battery-powered robot fleets tasked with intra-factory logistics in an autonomous manufacturing facility. In this environment, repetitive material handling operations are subject to real-world uncertainties such as blocked passages, and equipment or robot malf...
[ { "created": "Sat, 16 Mar 2024 22:46:12 GMT", "version": "v1" } ]
2024-03-19
[ [ "Goutham", "Mithun", "" ], [ "Stockar", "Stephanie", "" ] ]
This paper presents a novel fleet management strategy for battery-powered robot fleets tasked with intra-factory logistics in an autonomous manufacturing facility. In this environment, repetitive material handling operations are subject to real-world uncertainties such as blocked passages, and equipment or robot malfun...
1904.05442
Florian Zaruba
Florian Zaruba and Luca Benini
The Cost of Application-Class Processing: Energy and Performance Analysis of a Linux-ready 1.7GHz 64bit RISC-V Core in 22nm FDSOI Technology
11 pages, submitted to IEEE Transaction on Very Large Scale Integration (VLSI) Systems
null
10.1109/TVLSI.2019.2926114
null
cs.AR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The open-source RISC-V ISA is gaining traction, both in industry and academia. The ISA is designed to scale from micro-controllers to server-class processors. Furthermore, openness promotes the availability of various open-source and commercial implementations. Our main contribution in this work is a thorough power, ...
[ { "created": "Wed, 10 Apr 2019 21:07:21 GMT", "version": "v1" } ]
2019-11-26
[ [ "Zaruba", "Florian", "" ], [ "Benini", "Luca", "" ] ]
The open-source RISC-V ISA is gaining traction, both in industry and academia. The ISA is designed to scale from micro-controllers to server-class processors. Furthermore, openness promotes the availability of various open-source and commercial implementations. Our main contribution in this work is a thorough power, pe...
2408.07146
Zhiling Chen
Zhiling Chen, Hanning Chen, Mohsen Imani, Ruimin Chen, and Farhad Imani
Vision Language Model for Interpretable and Fine-grained Detection of Safety Compliance in Diverse Workplaces
20 pages, 7 figures
null
null
null
cs.CV cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Workplace accidents due to personal protective equipment (PPE) non-compliance raise serious safety concerns and lead to legal liabilities, financial penalties, and reputational damage. While object detection models have shown the capability to address this issue by identifying safety items, most existing models, such...
[ { "created": "Tue, 13 Aug 2024 18:32:06 GMT", "version": "v1" } ]
2024-08-15
[ [ "Chen", "Zhiling", "" ], [ "Chen", "Hanning", "" ], [ "Imani", "Mohsen", "" ], [ "Chen", "Ruimin", "" ], [ "Imani", "Farhad", "" ] ]
Workplace accidents due to personal protective equipment (PPE) non-compliance raise serious safety concerns and lead to legal liabilities, financial penalties, and reputational damage. While object detection models have shown the capability to address this issue by identifying safety items, most existing models, such a...
2405.06721
Ziyao Li
Ziyao Li
Kolmogorov-Arnold Networks are Radial Basis Function Networks
null
null
null
null
cs.LG cs.AI
http://creativecommons.org/licenses/by/4.0/
This short paper is a fast proof-of-concept that the 3-order B-splines used in Kolmogorov-Arnold Networks (KANs) can be well approximated by Gaussian radial basis functions. Doing so leads to FastKAN, a much faster implementation of KAN which is also a radial basis function (RBF) network.
[ { "created": "Fri, 10 May 2024 06:03:45 GMT", "version": "v1" } ]
2024-05-14
[ [ "Li", "Ziyao", "" ] ]
This short paper is a fast proof-of-concept that the 3-order B-splines used in Kolmogorov-Arnold Networks (KANs) can be well approximated by Gaussian radial basis functions. Doing so leads to FastKAN, a much faster implementation of KAN which is also a radial basis function (RBF) network.
2007.11192
Ping Wang
Ping Wang, Khushbu Agarwal, Colby Ham, Sutanay Choudhury, Chandan K. Reddy
Self-Supervised Learning of Contextual Embeddings for Link Prediction in Heterogeneous Networks
null
Published in The Web Conference 2021
null
null
cs.LG cs.SI stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Representation learning methods for heterogeneous networks produce a low-dimensional vector embedding for each node that is typically fixed for all tasks involving the node. Many of the existing methods focus on obtaining a static vector representation for a node in a way that is agnostic to the downstream applicatio...
[ { "created": "Wed, 22 Jul 2020 03:48:53 GMT", "version": "v1" }, { "created": "Sun, 23 Aug 2020 03:11:56 GMT", "version": "v2" }, { "created": "Sun, 21 Mar 2021 20:42:38 GMT", "version": "v3" } ]
2021-04-28
[ [ "Wang", "Ping", "" ], [ "Agarwal", "Khushbu", "" ], [ "Ham", "Colby", "" ], [ "Choudhury", "Sutanay", "" ], [ "Reddy", "Chandan K.", "" ] ]
Representation learning methods for heterogeneous networks produce a low-dimensional vector embedding for each node that is typically fixed for all tasks involving the node. Many of the existing methods focus on obtaining a static vector representation for a node in a way that is agnostic to the downstream application ...
1306.1822
Ognjen Arandjelovi\'c PhD
Reza Shoja Ghiass, Ognjen Arandjelovic, Hakim Bendada, Xavier Maldague
Illumination-invariant face recognition from a single image across extreme pose using a dual dimension AAM ensemble in the thermal infrared spectrum
International Joint Conference on Neural Networks, 2013. arXiv admin note: substantial text overlap with arXiv:1306.1609
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Over the course of the last decade, infrared (IR) and particularly thermal IR imaging based face recognition has emerged as a promising complement to conventional, visible spectrum based approaches which continue to struggle when applied in practice. While inherently insensitive to visible spectrum illumination chang...
[ { "created": "Fri, 7 Jun 2013 04:17:25 GMT", "version": "v1" } ]
2013-06-11
[ [ "Ghiass", "Reza Shoja", "" ], [ "Arandjelovic", "Ognjen", "" ], [ "Bendada", "Hakim", "" ], [ "Maldague", "Xavier", "" ] ]
Over the course of the last decade, infrared (IR) and particularly thermal IR imaging based face recognition has emerged as a promising complement to conventional, visible spectrum based approaches which continue to struggle when applied in practice. While inherently insensitive to visible spectrum illumination changes...
1811.06668
You Qiaoben
You Qiaoben, Zheng Wang, Jianguo Li, Yinpeng Dong, Yu-Gang Jiang, Jun Zhu
Composite Binary Decomposition Networks
null
null
null
null
cs.LG cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Binary neural networks have great resource and computing efficiency, while suffer from long training procedure and non-negligible accuracy drops, when comparing to the full-precision counterparts. In this paper, we propose the composite binary decomposition networks (CBDNet), which first compose real-valued tensor of...
[ { "created": "Fri, 16 Nov 2018 03:29:34 GMT", "version": "v1" } ]
2018-11-19
[ [ "Qiaoben", "You", "" ], [ "Wang", "Zheng", "" ], [ "Li", "Jianguo", "" ], [ "Dong", "Yinpeng", "" ], [ "Jiang", "Yu-Gang", "" ], [ "Zhu", "Jun", "" ] ]
Binary neural networks have great resource and computing efficiency, while suffer from long training procedure and non-negligible accuracy drops, when comparing to the full-precision counterparts. In this paper, we propose the composite binary decomposition networks (CBDNet), which first compose real-valued tensor of e...
1712.06496
Huan Li
Yi Qi, Zhongzhi Zhang, Yuhao Yi, Huan Li
Consensus in Self-similar Hierarchical Graphs and Sierpi\'nski Graphs: Convergence Speed, Delay Robustness, and Coherence
To be published on IEEE Transactions on Cybernetics
null
null
null
cs.SY cs.SI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The hierarchical graphs and Sierpi\'nski graphs are constructed iteratively, which have the same number of vertices and edges at any iteration, but exhibit quite different structural properties: the hierarchical graphs are non-fractal and small-world, while the Sierpi\'nski graphs are fractal and "large-world". Both ...
[ { "created": "Mon, 18 Dec 2017 16:14:33 GMT", "version": "v1" } ]
2017-12-19
[ [ "Qi", "Yi", "" ], [ "Zhang", "Zhongzhi", "" ], [ "Yi", "Yuhao", "" ], [ "Li", "Huan", "" ] ]
The hierarchical graphs and Sierpi\'nski graphs are constructed iteratively, which have the same number of vertices and edges at any iteration, but exhibit quite different structural properties: the hierarchical graphs are non-fractal and small-world, while the Sierpi\'nski graphs are fractal and "large-world". Both gr...
1905.13196
Peter Bubenik
Peter Bubenik, Michael Hull, Dhruv Patel, and Benjamin Whittle
Persistent homology detects curvature
22 pages, corrections thanks to anonymous referees
Inverse Problems, 36, 025008 (2020)
10.1088/1361-6420/ab4ac0
null
cs.CG cs.LG math.AT stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In topological data analysis, persistent homology is used to study the "shape of data". Persistent homology computations are completely characterized by a set of intervals called a bar code. It is often said that the long intervals represent the "topological signal" and the short intervals represent "noise". We give ...
[ { "created": "Thu, 30 May 2019 17:36:58 GMT", "version": "v1" }, { "created": "Wed, 12 Jun 2019 13:49:29 GMT", "version": "v2" }, { "created": "Thu, 19 Sep 2019 16:04:05 GMT", "version": "v3" } ]
2020-04-21
[ [ "Bubenik", "Peter", "" ], [ "Hull", "Michael", "" ], [ "Patel", "Dhruv", "" ], [ "Whittle", "Benjamin", "" ] ]
In topological data analysis, persistent homology is used to study the "shape of data". Persistent homology computations are completely characterized by a set of intervals called a bar code. It is often said that the long intervals represent the "topological signal" and the short intervals represent "noise". We give ev...
2305.15340
Arnau Quera-Bofarull
Arnau Quera-Bofarull, Ayush Chopra, Anisoara Calinescu, Michael Wooldridge, Joel Dyer
Bayesian calibration of differentiable agent-based models
Accepted for Oral Presentation at the AI4ABM Workshop at ICLR 2023
null
null
null
cs.MA cs.AI stat.ML
http://creativecommons.org/licenses/by/4.0/
Agent-based modelling (ABMing) is a powerful and intuitive approach to modelling complex systems; however, the intractability of ABMs' likelihood functions and the non-differentiability of the mathematical operations comprising these models present a challenge to their use in the real world. These difficulties have i...
[ { "created": "Wed, 24 May 2023 16:52:32 GMT", "version": "v1" } ]
2023-05-25
[ [ "Quera-Bofarull", "Arnau", "" ], [ "Chopra", "Ayush", "" ], [ "Calinescu", "Anisoara", "" ], [ "Wooldridge", "Michael", "" ], [ "Dyer", "Joel", "" ] ]
Agent-based modelling (ABMing) is a powerful and intuitive approach to modelling complex systems; however, the intractability of ABMs' likelihood functions and the non-differentiability of the mathematical operations comprising these models present a challenge to their use in the real world. These difficulties have in ...
2407.07099
Ziqi Zhang
Ziqi Zhang, Cunxiang Wang, Xiong Xiao, Yue Zhang, Donglin Wang
Nash CoT: Multi-Path Inference with Preference Equilibrium
null
null
null
null
cs.CL cs.AI cs.GT cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Chain-of-thought (CoT) prompting has emerged as a powerful technique for enhancing the reasoning capabilities of Large Language Models (LLMs) on complex problems. Among CoT-related studies, self-consistency (Multi-path inference with answer filtering through voting) involves generating multiple reasoning paths using ...
[ { "created": "Tue, 18 Jun 2024 07:46:13 GMT", "version": "v1" } ]
2024-07-11
[ [ "Zhang", "Ziqi", "" ], [ "Wang", "Cunxiang", "" ], [ "Xiao", "Xiong", "" ], [ "Zhang", "Yue", "" ], [ "Wang", "Donglin", "" ] ]
Chain-of-thought (CoT) prompting has emerged as a powerful technique for enhancing the reasoning capabilities of Large Language Models (LLMs) on complex problems. Among CoT-related studies, self-consistency (Multi-path inference with answer filtering through voting) involves generating multiple reasoning paths using th...
2010.08402
Xiao Liu
Xiao Liu, Jiajie Zhang, Siting Li, Zuotong Wu, Yang Yu
Difference-in-Differences: Bridging Normalization and Disentanglement in PG-GAN
null
null
null
null
cs.CV cs.LG
http://creativecommons.org/licenses/by-nc-sa/4.0/
What mechanisms causes GAN's entanglement? Although developing disentangled GAN has attracted sufficient attention, it is unclear how entanglement is originated by GAN transformation. We in this research propose a difference-in-difference (DID) counterfactual framework to design experiments for analyzing the entangle...
[ { "created": "Fri, 16 Oct 2020 14:02:53 GMT", "version": "v1" } ]
2020-10-19
[ [ "Liu", "Xiao", "" ], [ "Zhang", "Jiajie", "" ], [ "Li", "Siting", "" ], [ "Wu", "Zuotong", "" ], [ "Yu", "Yang", "" ] ]
What mechanisms causes GAN's entanglement? Although developing disentangled GAN has attracted sufficient attention, it is unclear how entanglement is originated by GAN transformation. We in this research propose a difference-in-difference (DID) counterfactual framework to design experiments for analyzing the entangleme...
2312.13316
Rongsheng Wang
Rongsheng Wang, Qingsong Yao, Haoran Lai, Zhiyang He, Xiaodong Tao, Zihang Jiang, S.Kevin Zhou
ECAMP: Entity-centered Context-aware Medical Vision Language Pre-training
null
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Despite significant advancements in medical vision-language pre-training, existing methods have largely overlooked the inherent entity-specific context within radiology reports and the complex cross-modality contextual relationships between text and images. To close this gap, we propose a novel Entity-centered Contex...
[ { "created": "Wed, 20 Dec 2023 11:00:54 GMT", "version": "v1" }, { "created": "Mon, 18 Mar 2024 10:54:03 GMT", "version": "v2" }, { "created": "Tue, 19 Mar 2024 11:01:35 GMT", "version": "v3" } ]
2024-03-20
[ [ "Wang", "Rongsheng", "" ], [ "Yao", "Qingsong", "" ], [ "Lai", "Haoran", "" ], [ "He", "Zhiyang", "" ], [ "Tao", "Xiaodong", "" ], [ "Jiang", "Zihang", "" ], [ "Zhou", "S. Kevin", "" ] ]
Despite significant advancements in medical vision-language pre-training, existing methods have largely overlooked the inherent entity-specific context within radiology reports and the complex cross-modality contextual relationships between text and images. To close this gap, we propose a novel Entity-centered Context-...
2209.06243
Chrysoula Zerva
Ricardo Rei, Marcos Treviso, Nuno M. Guerreiro, Chrysoula Zerva, Ana C. Farinha, Christine Maroti, Jos\'e G. C. de Souza, Taisiya Glushkova, Duarte M. Alves, Alon Lavie, Luisa Coheur, Andr\'e F. T. Martins
CometKiwi: IST-Unbabel 2022 Submission for the Quality Estimation Shared Task
WMT 2022 Quality Estimation shared task
null
null
null
cs.CL cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present the joint contribution of IST and Unbabel to the WMT 2022 Shared Task on Quality Estimation (QE). Our team participated on all three subtasks: (i) Sentence and Word-level Quality Prediction; (ii) Explainable QE; and (iii) Critical Error Detection. For all tasks we build on top of the COMET framework, conne...
[ { "created": "Tue, 13 Sep 2022 18:05:12 GMT", "version": "v1" } ]
2022-09-15
[ [ "Rei", "Ricardo", "" ], [ "Treviso", "Marcos", "" ], [ "Guerreiro", "Nuno M.", "" ], [ "Zerva", "Chrysoula", "" ], [ "Farinha", "Ana C.", "" ], [ "Maroti", "Christine", "" ], [ "de Souza", "José G. C.", "" ...
We present the joint contribution of IST and Unbabel to the WMT 2022 Shared Task on Quality Estimation (QE). Our team participated on all three subtasks: (i) Sentence and Word-level Quality Prediction; (ii) Explainable QE; and (iii) Critical Error Detection. For all tasks we build on top of the COMET framework, connect...
2403.01888
Shuhei Watanabe
Shuhei Watanabe and Neeratyoy Mallik and Edward Bergman and Frank Hutter
Fast Benchmarking of Asynchronous Multi-Fidelity Optimization on Zero-Cost Benchmarks
Submitted to AutoML Conference 2024 ABCD Track
null
null
null
cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
While deep learning has celebrated many successes, its results often hinge on the meticulous selection of hyperparameters (HPs). However, the time-consuming nature of deep learning training makes HP optimization (HPO) a costly endeavor, slowing down the development of efficient HPO tools. While zero-cost benchmarks, ...
[ { "created": "Mon, 4 Mar 2024 09:49:35 GMT", "version": "v1" }, { "created": "Thu, 18 Apr 2024 01:56:05 GMT", "version": "v2" } ]
2024-04-19
[ [ "Watanabe", "Shuhei", "" ], [ "Mallik", "Neeratyoy", "" ], [ "Bergman", "Edward", "" ], [ "Hutter", "Frank", "" ] ]
While deep learning has celebrated many successes, its results often hinge on the meticulous selection of hyperparameters (HPs). However, the time-consuming nature of deep learning training makes HP optimization (HPO) a costly endeavor, slowing down the development of efficient HPO tools. While zero-cost benchmarks, wh...
2406.05224
Zihao Chen
Zihao Chen, Zhili Xiao, Mahmoud Akl, Johannes Leugring, Omowuyi Olajide, Adil Malik, Nik Dennler, Chad Harper, Subhankar Bose, Hector A. Gonzalez, Jason Eshraghian, Riccardo Pignari, Gianvito Urgese, Andreas G. Andreou, Sadasivan Shankar, Christian Mayr, Gert Cauwenberghs, Shantanu Chakrabartty
ON-OFF Neuromorphic ISING Machines using Fowler-Nordheim Annealers
36 pages, 8 figures
null
null
null
cs.NE
http://creativecommons.org/licenses/by-nc-sa/4.0/
We introduce NeuroSA, a neuromorphic architecture specifically designed to ensure asymptotic convergence to the ground state of an Ising problem using an annealing process that is governed by the physics of quantum mechanical tunneling using Fowler-Nordheim (FN). The core component of NeuroSA consists of a pair of as...
[ { "created": "Fri, 7 Jun 2024 19:18:09 GMT", "version": "v1" } ]
2024-06-11
[ [ "Chen", "Zihao", "" ], [ "Xiao", "Zhili", "" ], [ "Akl", "Mahmoud", "" ], [ "Leugring", "Johannes", "" ], [ "Olajide", "Omowuyi", "" ], [ "Malik", "Adil", "" ], [ "Dennler", "Nik", "" ], [ "Harper",...
We introduce NeuroSA, a neuromorphic architecture specifically designed to ensure asymptotic convergence to the ground state of an Ising problem using an annealing process that is governed by the physics of quantum mechanical tunneling using Fowler-Nordheim (FN). The core component of NeuroSA consists of a pair of asyn...
1209.0053
Nilanjan Dey
Nilanjan Dey, Moumita Pal, Achintya Das
A Session Based Blind Watermarking Technique within the NROI of Retinal Fundus Images for Authentication Using DWT, Spread Spectrum and Harris Corner Detection
9 pages, 10 figures
International Journal of Modern Engineering Research (IJMER),Vol.2, Issue.3,May-June 2012 pp-749-757,ISSN: 2249-6645
null
null
cs.CV cs.CY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Digital Retinal Fundus Images helps to detect various ophthalmic diseases by detecting morphological changes in optical cup, optical disc and macula. Present work proposes a method for the authentication of medical images based on Discrete Wavelet Transformation (DWT) and Spread Spectrum. Proper selection of the Non ...
[ { "created": "Sat, 1 Sep 2012 04:17:39 GMT", "version": "v1" } ]
2012-09-04
[ [ "Dey", "Nilanjan", "" ], [ "Pal", "Moumita", "" ], [ "Das", "Achintya", "" ] ]
Digital Retinal Fundus Images helps to detect various ophthalmic diseases by detecting morphological changes in optical cup, optical disc and macula. Present work proposes a method for the authentication of medical images based on Discrete Wavelet Transformation (DWT) and Spread Spectrum. Proper selection of the Non Re...
2110.11331
Hanrui Wang
Hanrui Wang, Jiaqi Gu, Yongshan Ding, Zirui Li, Frederic T. Chong, David Z. Pan, Song Han
QuantumNAT: Quantum Noise-Aware Training with Noise Injection, Quantization and Normalization
Published as a conference paper at DAC 2022; 10 pages, 9 figures; TorchQuantum open-source at https://github.com/mit-han-lab/torchquantum
null
10.1145/3489517.3530400
null
cs.LG cs.AI quant-ph
http://creativecommons.org/licenses/by/4.0/
Parameterized Quantum Circuits (PQC) are promising towards quantum advantage on near-term quantum hardware. However, due to the large quantum noises (errors), the performance of PQC models has a severe degradation on real quantum devices. Take Quantum Neural Network (QNN) as an example, the accuracy gap between noise...
[ { "created": "Thu, 21 Oct 2021 17:59:19 GMT", "version": "v1" }, { "created": "Sat, 26 Feb 2022 22:23:50 GMT", "version": "v2" }, { "created": "Fri, 22 Apr 2022 20:14:44 GMT", "version": "v3" }, { "created": "Tue, 13 Jun 2023 19:56:10 GMT", "version": "v4" } ]
2024-04-05
[ [ "Wang", "Hanrui", "" ], [ "Gu", "Jiaqi", "" ], [ "Ding", "Yongshan", "" ], [ "Li", "Zirui", "" ], [ "Chong", "Frederic T.", "" ], [ "Pan", "David Z.", "" ], [ "Han", "Song", "" ] ]
Parameterized Quantum Circuits (PQC) are promising towards quantum advantage on near-term quantum hardware. However, due to the large quantum noises (errors), the performance of PQC models has a severe degradation on real quantum devices. Take Quantum Neural Network (QNN) as an example, the accuracy gap between noise-f...
2303.02733
Alexander Detkov
Alexander Detkov, Mohammad Salameh, Muhammad Fetrat Qharabagh, Jialin Zhang, Wei Lui, Shangling Jui, Di Niu
Reparameterization through Spatial Gradient Scaling
Published at ICLR 2023. Code available at https://github.com/Ascend-Research/Reparameterization
null
null
null
cs.LG cs.AI cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Reparameterization aims to improve the generalization of deep neural networks by transforming convolutional layers into equivalent multi-branched structures during training. However, there exists a gap in understanding how reparameterization may change and benefit the learning process of neural networks. In this pape...
[ { "created": "Sun, 5 Mar 2023 17:57:33 GMT", "version": "v1" }, { "created": "Tue, 7 Mar 2023 02:07:01 GMT", "version": "v2" } ]
2023-03-08
[ [ "Detkov", "Alexander", "" ], [ "Salameh", "Mohammad", "" ], [ "Qharabagh", "Muhammad Fetrat", "" ], [ "Zhang", "Jialin", "" ], [ "Lui", "Wei", "" ], [ "Jui", "Shangling", "" ], [ "Niu", "Di", "" ] ]
Reparameterization aims to improve the generalization of deep neural networks by transforming convolutional layers into equivalent multi-branched structures during training. However, there exists a gap in understanding how reparameterization may change and benefit the learning process of neural networks. In this paper,...
1701.02444
Rajshekhar Bhat Vishweshwar
Rajshekhar Vishweshwar Bhat, Mehul Motani and Teng Joon Lim
Energy Harvesting Communication Using Finite-Capacity Batteries with Internal Resistance
30 single column pages
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Modern systems will increasingly rely on energy harvested from their environment. Such systems utilize batteries to smoothen out the random fluctuations in harvested energy. These fluctuations induce highly variable battery charge and discharge rates, which affect the efficiencies of practical batteries that typicall...
[ { "created": "Tue, 10 Jan 2017 06:16:37 GMT", "version": "v1" } ]
2017-01-11
[ [ "Bhat", "Rajshekhar Vishweshwar", "" ], [ "Motani", "Mehul", "" ], [ "Lim", "Teng Joon", "" ] ]
Modern systems will increasingly rely on energy harvested from their environment. Such systems utilize batteries to smoothen out the random fluctuations in harvested energy. These fluctuations induce highly variable battery charge and discharge rates, which affect the efficiencies of practical batteries that typically ...
1904.08559
Vishnu Raj
Vishnu Raj, Sheetal Kalyani
Design of Communication Systems using Deep Learning: A Variational Inference Perspective
null
null
null
null
cs.IT cs.LG math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recent research in the design of end to end communication system using deep learning has produced models which can outperform traditional communication schemes. Most of these architectures leveraged autoencoders to design the encoder at the transmitter and decoder at the receiver and train them jointly by modeling tr...
[ { "created": "Thu, 18 Apr 2019 01:41:13 GMT", "version": "v1" }, { "created": "Fri, 2 Aug 2019 01:22:10 GMT", "version": "v2" }, { "created": "Sat, 25 Jan 2020 01:43:10 GMT", "version": "v3" } ]
2020-01-28
[ [ "Raj", "Vishnu", "" ], [ "Kalyani", "Sheetal", "" ] ]
Recent research in the design of end to end communication system using deep learning has produced models which can outperform traditional communication schemes. Most of these architectures leveraged autoencoders to design the encoder at the transmitter and decoder at the receiver and train them jointly by modeling tran...
2207.10284
Zhanpeng Zeng
Zhanpeng Zeng, Sourav Pal, Jeffery Kline, Glenn M Fung, Vikas Singh
Multi Resolution Analysis (MRA) for Approximate Self-Attention
ICML2022
null
null
null
cs.LG cs.CL eess.SP
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Transformers have emerged as a preferred model for many tasks in natural langugage processing and vision. Recent efforts on training and deploying Transformers more efficiently have identified many strategies to approximate the self-attention matrix, a key module in a Transformer architecture. Effective ideas include...
[ { "created": "Thu, 21 Jul 2022 03:36:30 GMT", "version": "v1" } ]
2022-07-22
[ [ "Zeng", "Zhanpeng", "" ], [ "Pal", "Sourav", "" ], [ "Kline", "Jeffery", "" ], [ "Fung", "Glenn M", "" ], [ "Singh", "Vikas", "" ] ]
Transformers have emerged as a preferred model for many tasks in natural langugage processing and vision. Recent efforts on training and deploying Transformers more efficiently have identified many strategies to approximate the self-attention matrix, a key module in a Transformer architecture. Effective ideas include v...
1706.09274
Haosheng Zou
Haosheng Zou, Kun Xu, Jialian Li, Jun Zhu
The YouTube-8M Kaggle Competition: Challenges and Methods
accepted to CVPR'17 Workshop on YouTube-8M Large-Scale Video Understanding (oral presentation); code is at https://github.com/taufikxu/youtube on branches kunxu and zhs
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We took part in the YouTube-8M Video Understanding Challenge hosted on Kaggle, and achieved the 10th place within less than one month's time. In this paper, we present an extensive analysis and solution to the underlying machine-learning problem based on frame-level data, where major challenges are identified and cor...
[ { "created": "Wed, 28 Jun 2017 13:20:51 GMT", "version": "v1" }, { "created": "Thu, 13 Jul 2017 05:30:37 GMT", "version": "v2" } ]
2017-07-14
[ [ "Zou", "Haosheng", "" ], [ "Xu", "Kun", "" ], [ "Li", "Jialian", "" ], [ "Zhu", "Jun", "" ] ]
We took part in the YouTube-8M Video Understanding Challenge hosted on Kaggle, and achieved the 10th place within less than one month's time. In this paper, we present an extensive analysis and solution to the underlying machine-learning problem based on frame-level data, where major challenges are identified and corre...
2407.00009
Xinshi Zang
Xinshi Zang, Wenhao Lin, Shiju Lin, Jinwei Liu, Evangeline F.Y. Young
An Open-Source Fast Parallel Routing Approach for Commercial FPGAs
null
null
null
null
cs.DC cs.NI
http://creativecommons.org/licenses/by/4.0/
In the face of escalating complexity and size of contemporary FPGAs and circuits, routing emerges as a pivotal and time-intensive phase in FPGA compilation flows. In response to this challenge, we present an open-source parallel routing methodology designed to expedite routing procedures for commercial FPGAs. Our app...
[ { "created": "Thu, 25 Apr 2024 09:27:33 GMT", "version": "v1" } ]
2024-07-02
[ [ "Zang", "Xinshi", "" ], [ "Lin", "Wenhao", "" ], [ "Lin", "Shiju", "" ], [ "Liu", "Jinwei", "" ], [ "Young", "Evangeline F. Y.", "" ] ]
In the face of escalating complexity and size of contemporary FPGAs and circuits, routing emerges as a pivotal and time-intensive phase in FPGA compilation flows. In response to this challenge, we present an open-source parallel routing methodology designed to expedite routing procedures for commercial FPGAs. Our appro...
1604.04724
Shanmuganathan Raman
Sri Raghu Malireddi, Shanmuganathan Raman
Automatic Segmentation of Dynamic Objects from an Image Pair
8 pages
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Automatic segmentation of objects from a single image is a challenging problem which generally requires training on large number of images. We consider the problem of automatically segmenting only the dynamic objects from a given pair of images of a scene captured from different positions. We exploit dense correspond...
[ { "created": "Sat, 16 Apr 2016 11:00:24 GMT", "version": "v1" } ]
2016-04-19
[ [ "Malireddi", "Sri Raghu", "" ], [ "Raman", "Shanmuganathan", "" ] ]
Automatic segmentation of objects from a single image is a challenging problem which generally requires training on large number of images. We consider the problem of automatically segmenting only the dynamic objects from a given pair of images of a scene captured from different positions. We exploit dense corresponden...
2006.14223
Alex Sokolov
Alex Sokolov, Denis Filimonov
Neural Machine Translation For Paraphrase Generation
Published in NIPS 2018: 2nd Conversational AI workshop
null
null
null
cs.CL cs.AI cs.LG
http://creativecommons.org/licenses/by-sa/4.0/
Training a spoken language understanding system, as the one in Alexa, typically requires a large human-annotated corpus of data. Manual annotations are expensive and time consuming. In Alexa Skill Kit (ASK) user experience with the skill greatly depends on the amount of data provided by skill developer. In this work,...
[ { "created": "Thu, 25 Jun 2020 07:38:00 GMT", "version": "v1" } ]
2020-06-30
[ [ "Sokolov", "Alex", "" ], [ "Filimonov", "Denis", "" ] ]
Training a spoken language understanding system, as the one in Alexa, typically requires a large human-annotated corpus of data. Manual annotations are expensive and time consuming. In Alexa Skill Kit (ASK) user experience with the skill greatly depends on the amount of data provided by skill developer. In this work, w...
2203.05266
Donadel Denis
Mauro Conti, Denis Donadel, Radha Poovendran, Federico Turrin
EVExchange: A Relay Attack on Electric Vehicle Charging System
20 pages, 6 figures
null
null
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
To support the increasing spread of Electric Vehicles (EVs), Charging Stations (CSs) are being installed worldwide. The new generation of CSs employs the Vehicle-To-Grid (V2G) paradigm by implementing novel standards such as the ISO 15118. This standard enables high-level communication between the vehicle and the cha...
[ { "created": "Thu, 10 Mar 2022 09:54:12 GMT", "version": "v1" }, { "created": "Thu, 7 Jul 2022 14:09:33 GMT", "version": "v2" } ]
2022-07-08
[ [ "Conti", "Mauro", "" ], [ "Donadel", "Denis", "" ], [ "Poovendran", "Radha", "" ], [ "Turrin", "Federico", "" ] ]
To support the increasing spread of Electric Vehicles (EVs), Charging Stations (CSs) are being installed worldwide. The new generation of CSs employs the Vehicle-To-Grid (V2G) paradigm by implementing novel standards such as the ISO 15118. This standard enables high-level communication between the vehicle and the charg...
1610.07100
Matthew Hastings
M. B. Hastings
Local Maxima and Improved Exact Algorithm for MAX-2-SAT
17 pages, no figures
null
null
null
cs.DS cond-mat.stat-mech
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Given a MAX-2-SAT instance, we define a local maximum to be an assignment such that changing any single variable reduces the number of satisfied clauses. We consider the question of the number of local maxima that an instance of MAX-2-SAT can have. We give upper bounds in both the sparse and nonsparse case, where the...
[ { "created": "Sat, 22 Oct 2016 22:48:43 GMT", "version": "v1" } ]
2016-11-01
[ [ "Hastings", "M. B.", "" ] ]
Given a MAX-2-SAT instance, we define a local maximum to be an assignment such that changing any single variable reduces the number of satisfied clauses. We consider the question of the number of local maxima that an instance of MAX-2-SAT can have. We give upper bounds in both the sparse and nonsparse case, where the s...
2108.10095
Sophie Zinser
Sophie Zinser and Hannah Thinyane
Organizational Resilience between Competing Networks of Infomediaries: A Case Study in Civil Society Resilience in Hong Kong
In proceedings of the 1st Virtual Conference on Implications of Information and Digital Technologies for Development, 2021
null
null
null
cs.CY
http://creativecommons.org/licenses/by-nc-sa/4.0/
This study explores how non-governmental organizations (NGOs) in Hong Kong can be considered as 'infomediaries' (UNDP, 2003) in their use of information and communication technologies (ICTs) to support resilience-building across a growing population of migrant domestic workers (MDWs). It also acknowledges MDWs effect...
[ { "created": "Mon, 23 Aug 2021 11:51:53 GMT", "version": "v1" } ]
2021-08-24
[ [ "Zinser", "Sophie", "" ], [ "Thinyane", "Hannah", "" ] ]
This study explores how non-governmental organizations (NGOs) in Hong Kong can be considered as 'infomediaries' (UNDP, 2003) in their use of information and communication technologies (ICTs) to support resilience-building across a growing population of migrant domestic workers (MDWs). It also acknowledges MDWs effectiv...
2210.16644
Anchit Gupta
Darshan Singh S, Anchit Gupta, C. V. Jawahar, Makarand Tapaswi
Unsupervised Audio-Visual Lecture Segmentation
17 pages, 14 figures, 14 tables, Accepted to WACV 2023. Project page: https://cvit.iiit.ac.in/research/projects/cvit-projects/avlectures
null
null
null
cs.CV
http://creativecommons.org/licenses/by-nc-sa/4.0/
Over the last decade, online lecture videos have become increasingly popular and have experienced a meteoric rise during the pandemic. However, video-language research has primarily focused on instructional videos or movies, and tools to help students navigate the growing online lectures are lacking. Our first contri...
[ { "created": "Sat, 29 Oct 2022 16:26:34 GMT", "version": "v1" } ]
2022-11-01
[ [ "S", "Darshan Singh", "" ], [ "Gupta", "Anchit", "" ], [ "Jawahar", "C. V.", "" ], [ "Tapaswi", "Makarand", "" ] ]
Over the last decade, online lecture videos have become increasingly popular and have experienced a meteoric rise during the pandemic. However, video-language research has primarily focused on instructional videos or movies, and tools to help students navigate the growing online lectures are lacking. Our first contribu...
2305.03850
Alexander Mariona
Alexander Mariona, Homa Esfahanizadeh, Rafael G. L. D'Oliveira, Muriel M\'edard
A Non-Asymptotic Analysis of Mismatched Guesswork
7 pages, 1 figure. Accepted to ISIT 2023
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The problem of mismatched guesswork considers the additional cost incurred by using a guessing function which is optimal for a distribution $q$ when the random variable to be guessed is actually distributed according to a different distribution $p$. This problem has been well-studied from an asymptotic perspective, b...
[ { "created": "Fri, 5 May 2023 21:09:23 GMT", "version": "v1" } ]
2023-05-09
[ [ "Mariona", "Alexander", "" ], [ "Esfahanizadeh", "Homa", "" ], [ "D'Oliveira", "Rafael G. L.", "" ], [ "Médard", "Muriel", "" ] ]
The problem of mismatched guesswork considers the additional cost incurred by using a guessing function which is optimal for a distribution $q$ when the random variable to be guessed is actually distributed according to a different distribution $p$. This problem has been well-studied from an asymptotic perspective, but...
2405.08419
Haiyong Xu
Meisheng Guan, Haiyong Xu, Gangyi Jiang, Mei Yu, Yeyao Chen, Ting Luo, Yang Song
WaterMamba: Visual State Space Model for Underwater Image Enhancement
arXiv admin note: substantial text overlap with arXiv:2403.06098
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Underwater imaging often suffers from low quality due to factors affecting light propagation and absorption in water. To improve image quality, some underwater image enhancement (UIE) methods based on convolutional neural networks (CNN) and Transformer have been proposed. However, CNN-based UIE methods are limited in...
[ { "created": "Tue, 14 May 2024 08:26:29 GMT", "version": "v1" } ]
2024-05-15
[ [ "Guan", "Meisheng", "" ], [ "Xu", "Haiyong", "" ], [ "Jiang", "Gangyi", "" ], [ "Yu", "Mei", "" ], [ "Chen", "Yeyao", "" ], [ "Luo", "Ting", "" ], [ "Song", "Yang", "" ] ]
Underwater imaging often suffers from low quality due to factors affecting light propagation and absorption in water. To improve image quality, some underwater image enhancement (UIE) methods based on convolutional neural networks (CNN) and Transformer have been proposed. However, CNN-based UIE methods are limited in m...
2205.07562
Vieri Giuliano Santucci
Alejandro Romero, Gianluca Baldassarre, Richard J. Duro, Vieri Giuliano Santucci
Autonomous Open-Ended Learning of Tasks with Non-Stationary Interdependencies
Submitted and accepted to "The Multi-disciplinary Conference on Reinforcement Learning and Decision Making" RLDM 2022
null
null
null
cs.LG cs.AI cs.RO
http://creativecommons.org/licenses/by/4.0/
Autonomous open-ended learning is a relevant approach in machine learning and robotics, allowing the design of artificial agents able to acquire goals and motor skills without the necessity of user assigned tasks. A crucial issue for this approach is to develop strategies to ensure that agents can maximise their comp...
[ { "created": "Mon, 16 May 2022 10:43:01 GMT", "version": "v1" } ]
2022-05-17
[ [ "Romero", "Alejandro", "" ], [ "Baldassarre", "Gianluca", "" ], [ "Duro", "Richard J.", "" ], [ "Santucci", "Vieri Giuliano", "" ] ]
Autonomous open-ended learning is a relevant approach in machine learning and robotics, allowing the design of artificial agents able to acquire goals and motor skills without the necessity of user assigned tasks. A crucial issue for this approach is to develop strategies to ensure that agents can maximise their compet...
1901.08397
Zhiyong Yuan
Xuejie Mai, Zhiyong Yuan, Qianqian Tong, Tianchen Yuan, and Jianhui Zhao
Periodic-corrected data driven coupling of blood flow and vessel wall for virtual surgery
null
null
null
null
cs.GR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Fast and realistic coupling of blood flow and vessel wall is of great importance to virtual surgery. In this paper, we propose a novel data-driven coupling method that formulates physics-based blood flow simulation as a regression problem, using an improved periodic-corrected neural network (PcNet), estimating the ac...
[ { "created": "Thu, 24 Jan 2019 13:32:03 GMT", "version": "v1" } ]
2019-01-25
[ [ "Mai", "Xuejie", "" ], [ "Yuan", "Zhiyong", "" ], [ "Tong", "Qianqian", "" ], [ "Yuan", "Tianchen", "" ], [ "Zhao", "Jianhui", "" ] ]
Fast and realistic coupling of blood flow and vessel wall is of great importance to virtual surgery. In this paper, we propose a novel data-driven coupling method that formulates physics-based blood flow simulation as a regression problem, using an improved periodic-corrected neural network (PcNet), estimating the acce...
1409.1148
Hatem Abou-zeid
Hatem Abou-zeid and Hosssam S. Hassenein
Toward Green Media Delivery: Location-Aware Opportunities and Approaches
null
null
null
null
cs.MM cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Mobile media has undoubtedly become the predominant source of traffic in wireless networks. The result is not only congestion and poor Quality-of-Experience, but also an unprecedented energy drain at both the network and user devices. In order to sustain this continued growth, novel disruptive paradigms of media deli...
[ { "created": "Wed, 3 Sep 2014 16:28:36 GMT", "version": "v1" } ]
2014-09-04
[ [ "Abou-zeid", "Hatem", "" ], [ "Hassenein", "Hosssam S.", "" ] ]
Mobile media has undoubtedly become the predominant source of traffic in wireless networks. The result is not only congestion and poor Quality-of-Experience, but also an unprecedented energy drain at both the network and user devices. In order to sustain this continued growth, novel disruptive paradigms of media delive...
1902.02636
Bita Azari
Bita Azari, Angelica Lim and Richard T. Vaughan
Commodifying Pointing in HRI: Simple and Fast Pointing Gesture Detection from RGB-D Images
null
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present and characterize a simple method for detecting pointing gestures suitable for human-robot interaction applications using a commodity RGB-D camera. We exploit a state-of-the-art Deep CNN-based detector to find hands and faces in RGB images, then examine the corresponding depth channel pixels to obtain full ...
[ { "created": "Thu, 7 Feb 2019 14:28:13 GMT", "version": "v1" } ]
2019-02-08
[ [ "Azari", "Bita", "" ], [ "Lim", "Angelica", "" ], [ "Vaughan", "Richard T.", "" ] ]
We present and characterize a simple method for detecting pointing gestures suitable for human-robot interaction applications using a commodity RGB-D camera. We exploit a state-of-the-art Deep CNN-based detector to find hands and faces in RGB images, then examine the corresponding depth channel pixels to obtain full 3D...
2106.08187
Zehong Hu Mr.
Long Yang, Zhao Li, Zehong Hu, Shasha Ruan, Shijian Li, Gang Pan, Hongyang Chen
Thompson Sampling for Unimodal Bandits
There are some technical parts need to be improved. We will fix these places and provide an updated version
null
null
null
cs.LG cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we propose a Thompson Sampling algorithm for \emph{unimodal} bandits, where the expected reward is unimodal over the partially ordered arms. To exploit the unimodal structure better, at each step, instead of exploration from the entire decision space, our algorithm makes decision according to posterior...
[ { "created": "Tue, 15 Jun 2021 14:40:34 GMT", "version": "v1" }, { "created": "Wed, 16 Jun 2021 04:51:04 GMT", "version": "v2" } ]
2021-06-17
[ [ "Yang", "Long", "" ], [ "Li", "Zhao", "" ], [ "Hu", "Zehong", "" ], [ "Ruan", "Shasha", "" ], [ "Li", "Shijian", "" ], [ "Pan", "Gang", "" ], [ "Chen", "Hongyang", "" ] ]
In this paper, we propose a Thompson Sampling algorithm for \emph{unimodal} bandits, where the expected reward is unimodal over the partially ordered arms. To exploit the unimodal structure better, at each step, instead of exploration from the entire decision space, our algorithm makes decision according to posterior d...
2204.09151
Pha Nguyen
Pha Nguyen, Kha Gia Quach, Chi Nhan Duong, Ngan Le, Xuan-Bac Nguyen, Khoa Luu
Multi-Camera Multiple 3D Object Tracking on the Move for Autonomous Vehicles
Accepted at CVPRW 2022
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The development of autonomous vehicles provides an opportunity to have a complete set of camera sensors capturing the environment around the car. Thus, it is important for object detection and tracking to address new challenges, such as achieving consistent results across views of cameras. To address these challenges...
[ { "created": "Tue, 19 Apr 2022 22:50:36 GMT", "version": "v1" } ]
2022-04-21
[ [ "Nguyen", "Pha", "" ], [ "Quach", "Kha Gia", "" ], [ "Duong", "Chi Nhan", "" ], [ "Le", "Ngan", "" ], [ "Nguyen", "Xuan-Bac", "" ], [ "Luu", "Khoa", "" ] ]
The development of autonomous vehicles provides an opportunity to have a complete set of camera sensors capturing the environment around the car. Thus, it is important for object detection and tracking to address new challenges, such as achieving consistent results across views of cameras. To address these challenges, ...
2211.02175
Bing Shuai
Bing Shuai, Alessandro Bergamo, Uta Buechler, Andrew Berneshawi, Alyssa Boden, Joseph Tighe
Large Scale Real-World Multi-Person Tracking
ECCV 2022
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper presents a new large scale multi-person tracking dataset -- \texttt{PersonPath22}, which is over an order of magnitude larger than currently available high quality multi-object tracking datasets such as MOT17, HiEve, and MOT20 datasets. The lack of large scale training and test data for this task has limit...
[ { "created": "Thu, 3 Nov 2022 23:03:13 GMT", "version": "v1" } ]
2022-11-07
[ [ "Shuai", "Bing", "" ], [ "Bergamo", "Alessandro", "" ], [ "Buechler", "Uta", "" ], [ "Berneshawi", "Andrew", "" ], [ "Boden", "Alyssa", "" ], [ "Tighe", "Joseph", "" ] ]
This paper presents a new large scale multi-person tracking dataset -- \texttt{PersonPath22}, which is over an order of magnitude larger than currently available high quality multi-object tracking datasets such as MOT17, HiEve, and MOT20 datasets. The lack of large scale training and test data for this task has limited...
2004.04933
Yukun Huang
Yukun Huang, Zheng-Jun Zha, Xueyang Fu, Richang Hong, Liang Li
Real-world Person Re-Identification via Degradation Invariance Learning
To appear in CVPR2020
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Person re-identification (Re-ID) in real-world scenarios usually suffers from various degradation factors, e.g., low-resolution, weak illumination, blurring and adverse weather. On the one hand, these degradations lead to severe discriminative information loss, which significantly obstructs identity representation le...
[ { "created": "Fri, 10 Apr 2020 07:58:50 GMT", "version": "v1" } ]
2020-04-13
[ [ "Huang", "Yukun", "" ], [ "Zha", "Zheng-Jun", "" ], [ "Fu", "Xueyang", "" ], [ "Hong", "Richang", "" ], [ "Li", "Liang", "" ] ]
Person re-identification (Re-ID) in real-world scenarios usually suffers from various degradation factors, e.g., low-resolution, weak illumination, blurring and adverse weather. On the one hand, these degradations lead to severe discriminative information loss, which significantly obstructs identity representation lear...
1709.05871
Vinod Muthusamy
Bishwaranjan Bhattacharjee, Scott Boag, Chandani Doshi, Parijat Dube, Ben Herta, Vatche Ishakian, K. R. Jayaram, Rania Khalaf, Avesh Krishna, Yu Bo Li, Vinod Muthusamy, Ruchir Puri, Yufei Ren, Florian Rosenberg, Seetharami R. Seelam, Yandong Wang, Jian Ming Zhang, Li Zhang
IBM Deep Learning Service
null
null
null
null
cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Deep learning driven by large neural network models is overtaking traditional machine learning methods for understanding unstructured and perceptual data domains such as speech, text, and vision. At the same time, the "as-a-Service"-based business model on the cloud is fundamentally transforming the information techn...
[ { "created": "Mon, 18 Sep 2017 11:40:48 GMT", "version": "v1" } ]
2017-09-19
[ [ "Bhattacharjee", "Bishwaranjan", "" ], [ "Boag", "Scott", "" ], [ "Doshi", "Chandani", "" ], [ "Dube", "Parijat", "" ], [ "Herta", "Ben", "" ], [ "Ishakian", "Vatche", "" ], [ "Jayaram", "K. R.", "" ], ...
Deep learning driven by large neural network models is overtaking traditional machine learning methods for understanding unstructured and perceptual data domains such as speech, text, and vision. At the same time, the "as-a-Service"-based business model on the cloud is fundamentally transforming the information technol...
1705.07728
Svyatoslav Covanov
Svyatoslav Covanov (CARAMBA)
Improved method for finding optimal formulae for bilinear maps in a finite field
null
null
null
null
cs.DS cs.CC cs.DM cs.SC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In 2012, Barbulescu, Detrey, Estibals and Zimmermann proposed a new framework to exhaustively search for optimal formulae for evaluating bilinear maps, such as Strassen or Karatsuba formulae. The main contribution of this work is a new criterion to aggressively prune useless branches in the exhaustive search, thus le...
[ { "created": "Tue, 9 May 2017 06:20:33 GMT", "version": "v1" }, { "created": "Wed, 29 Nov 2017 13:39:12 GMT", "version": "v2" }, { "created": "Fri, 7 Dec 2018 16:10:46 GMT", "version": "v3" } ]
2018-12-10
[ [ "Covanov", "Svyatoslav", "", "CARAMBA" ] ]
In 2012, Barbulescu, Detrey, Estibals and Zimmermann proposed a new framework to exhaustively search for optimal formulae for evaluating bilinear maps, such as Strassen or Karatsuba formulae. The main contribution of this work is a new criterion to aggressively prune useless branches in the exhaustive search, thus lead...
2108.08421
Mingjun Yin
Mingjun Yin, Shasha Li, Zikui Cai, Chengyu Song, M. Salman Asif, Amit K. Roy-Chowdhury, and Srikanth V. Krishnamurthy
Exploiting Multi-Object Relationships for Detecting Adversarial Attacks in Complex Scenes
ICCV'21 Accepted
null
null
null
cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Vision systems that deploy Deep Neural Networks (DNNs) are known to be vulnerable to adversarial examples. Recent research has shown that checking the intrinsic consistencies in the input data is a promising way to detect adversarial attacks (e.g., by checking the object co-occurrence relationships in complex scenes)...
[ { "created": "Thu, 19 Aug 2021 00:52:10 GMT", "version": "v1" } ]
2021-08-20
[ [ "Yin", "Mingjun", "" ], [ "Li", "Shasha", "" ], [ "Cai", "Zikui", "" ], [ "Song", "Chengyu", "" ], [ "Asif", "M. Salman", "" ], [ "Roy-Chowdhury", "Amit K.", "" ], [ "Krishnamurthy", "Srikanth V.", "" ] ]
Vision systems that deploy Deep Neural Networks (DNNs) are known to be vulnerable to adversarial examples. Recent research has shown that checking the intrinsic consistencies in the input data is a promising way to detect adversarial attacks (e.g., by checking the object co-occurrence relationships in complex scenes). ...
2009.03534
Hyungjun Kim
Eunho Koo and Hyungjun Kim
Empirical Strategy for Stretching Probability Distribution in Neural-network-based Regression
13 pages, 4 figures, to be submitted to Neural Networks
null
null
null
cs.LG cs.AI stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In regression analysis under artificial neural networks, the prediction performance depends on determining the appropriate weights between layers. As randomly initialized weights are updated during back-propagation using the gradient descent procedure under a given loss function, the loss function structure can affec...
[ { "created": "Tue, 8 Sep 2020 06:08:14 GMT", "version": "v1" } ]
2020-09-09
[ [ "Koo", "Eunho", "" ], [ "Kim", "Hyungjun", "" ] ]
In regression analysis under artificial neural networks, the prediction performance depends on determining the appropriate weights between layers. As randomly initialized weights are updated during back-propagation using the gradient descent procedure under a given loss function, the loss function structure can affect ...
2212.02035
Yuki Osumi
Yuki Osumi, Naotaka Umekawa, Hitomi Komata, Shinpei Hayashi
Empirical Study of Co-Renamed Identifiers
10 pages, APSEC 2022
Proceedings of the 29th Asia-Pacific Software Engineering Conference, 71-80, 2022
10.1109/APSEC57359.2022.00019
null
cs.SE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Background: The renaming of program identifiers is the most common refactoring operation. Because some identifiers are related to each other, developers may need to rename related identifiers together. Aims: To understand how developers rename multiple identifiers simultaneously, it is necessary to consider the relat...
[ { "created": "Mon, 5 Dec 2022 05:08:43 GMT", "version": "v1" } ]
2022-12-07
[ [ "Osumi", "Yuki", "" ], [ "Umekawa", "Naotaka", "" ], [ "Komata", "Hitomi", "" ], [ "Hayashi", "Shinpei", "" ] ]
Background: The renaming of program identifiers is the most common refactoring operation. Because some identifiers are related to each other, developers may need to rename related identifiers together. Aims: To understand how developers rename multiple identifiers simultaneously, it is necessary to consider the relatio...
1208.0318
Saptarshi Das
Saptarshi Das, Indranil Pan, Khrist Sur, Shantanu Das
Artificial Neural Network Based Prediction of Optimal Pseudo-Damping and Meta-Damping in Oscillatory Fractional Order Dynamical Systems
7 pages, 9 figures
2012 International Conference on Advances in Engineering, Science and Management (ICAESM), art. no. 6216029 , pp. 350-356
null
null
cs.SY cs.NE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper investigates typical behaviors like damped oscillations in fractional order (FO) dynamical systems. Such response occurs due to the presence of, what is conceived as, pseudo-damping and meta-damping in some special class of FO systems. Here, approximation of such damped oscillation in FO systems with the c...
[ { "created": "Wed, 1 Aug 2012 18:54:07 GMT", "version": "v1" } ]
2012-08-02
[ [ "Das", "Saptarshi", "" ], [ "Pan", "Indranil", "" ], [ "Sur", "Khrist", "" ], [ "Das", "Shantanu", "" ] ]
This paper investigates typical behaviors like damped oscillations in fractional order (FO) dynamical systems. Such response occurs due to the presence of, what is conceived as, pseudo-damping and meta-damping in some special class of FO systems. Here, approximation of such damped oscillation in FO systems with the con...
2310.15758
Dominic Petrak
Dominic Petrak, Nafise Sadat Moosavi, Ye Tian, Nikolai Rozanov, Iryna Gurevych
Learning From Free-Text Human Feedback -- Collect New Datasets Or Extend Existing Ones?
Accepted to be presented at EMNLP 2023
null
null
null
cs.CL
http://creativecommons.org/licenses/by-nc-sa/4.0/
Learning from free-text human feedback is essential for dialog systems, but annotated data is scarce and usually covers only a small fraction of error types known in conversational AI. Instead of collecting and annotating new datasets from scratch, recent advances in synthetic dialog generation could be used to augme...
[ { "created": "Tue, 24 Oct 2023 12:01:11 GMT", "version": "v1" } ]
2023-10-25
[ [ "Petrak", "Dominic", "" ], [ "Moosavi", "Nafise Sadat", "" ], [ "Tian", "Ye", "" ], [ "Rozanov", "Nikolai", "" ], [ "Gurevych", "Iryna", "" ] ]
Learning from free-text human feedback is essential for dialog systems, but annotated data is scarce and usually covers only a small fraction of error types known in conversational AI. Instead of collecting and annotating new datasets from scratch, recent advances in synthetic dialog generation could be used to augment...
1907.06005
Xiang Zhang
Yu Gu, Xiang Zhang, Zhi Liu and Fuji Ren
BeSense: Leveraging WiFi Channel Data and Computational Intelligence for Behavior Analysis
11 pages accepted by IEEE Computational Intelligence Magazine
null
10.1109/MCI.2019.2937610
null
cs.HC cs.AI eess.SP
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The ever evolving informatics technology has gradually bounded human and computer in a compact way. Understanding user behavior becomes a key enabler in many fields such as sedentary-related healthcare, human-computer interaction (HCI) and affective computing. Traditional sensor-based and vision-based user behavior a...
[ { "created": "Sat, 13 Jul 2019 03:31:14 GMT", "version": "v1" }, { "created": "Mon, 23 Mar 2020 10:48:13 GMT", "version": "v2" } ]
2020-05-25
[ [ "Gu", "Yu", "" ], [ "Zhang", "Xiang", "" ], [ "Liu", "Zhi", "" ], [ "Ren", "Fuji", "" ] ]
The ever evolving informatics technology has gradually bounded human and computer in a compact way. Understanding user behavior becomes a key enabler in many fields such as sedentary-related healthcare, human-computer interaction (HCI) and affective computing. Traditional sensor-based and vision-based user behavior ana...
2010.03133
Zhiyu Zhang
Zhiyu Zhang, Ioannis Paschalidis
Provable Hierarchical Imitation Learning via EM
To appear in AISTATS 2021
null
null
null
cs.LG stat.ML
http://creativecommons.org/licenses/by/4.0/
Due to recent empirical successes, the options framework for hierarchical reinforcement learning is gaining increasing popularity. Rather than learning from rewards which suffers from the curse of dimensionality, we consider learning an options-type hierarchical policy from expert demonstrations. Such a problem is re...
[ { "created": "Wed, 7 Oct 2020 03:21:57 GMT", "version": "v1" }, { "created": "Sun, 14 Feb 2021 04:01:16 GMT", "version": "v2" } ]
2021-02-16
[ [ "Zhang", "Zhiyu", "" ], [ "Paschalidis", "Ioannis", "" ] ]
Due to recent empirical successes, the options framework for hierarchical reinforcement learning is gaining increasing popularity. Rather than learning from rewards which suffers from the curse of dimensionality, we consider learning an options-type hierarchical policy from expert demonstrations. Such a problem is refe...
2405.15743
Nolan Dey
Nolan Dey and Shane Bergsma and Joel Hestness
Sparse maximal update parameterization: A holistic approach to sparse training dynamics
9 pages main text, 11 pages reference and appendix, 11 figures
null
null
null
cs.LG
http://creativecommons.org/licenses/by/4.0/
Several challenges make it difficult for sparse neural networks to compete with dense models. First, setting a large fraction of weights to zero impairs forward and gradient signal propagation. Second, sparse studies often need to test multiple sparsity levels, while also introducing new hyperparameters (HPs), leadin...
[ { "created": "Fri, 24 May 2024 17:39:26 GMT", "version": "v1" } ]
2024-05-27
[ [ "Dey", "Nolan", "" ], [ "Bergsma", "Shane", "" ], [ "Hestness", "Joel", "" ] ]
Several challenges make it difficult for sparse neural networks to compete with dense models. First, setting a large fraction of weights to zero impairs forward and gradient signal propagation. Second, sparse studies often need to test multiple sparsity levels, while also introducing new hyperparameters (HPs), leading ...
2312.08747
Dat Thanh Nguyen
Dat Thanh Nguyen
Dissecting vocabulary biases datasets through statistical testing and automated data augmentation for artifact mitigation in Natural Language Inference
null
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
In recent years, the availability of large-scale annotated datasets, such as the Stanford Natural Language Inference and the Multi-Genre Natural Language Inference, coupled with the advent of pre-trained language models, has significantly contributed to the development of the natural language inference domain. Howeve...
[ { "created": "Thu, 14 Dec 2023 08:46:26 GMT", "version": "v1" } ]
2023-12-15
[ [ "Nguyen", "Dat Thanh", "" ] ]
In recent years, the availability of large-scale annotated datasets, such as the Stanford Natural Language Inference and the Multi-Genre Natural Language Inference, coupled with the advent of pre-trained language models, has significantly contributed to the development of the natural language inference domain. However,...
2208.09285
Andrew Wang
Andrew Wang, Wyatt Mayor, Ryan Smith, Gopal Nookula, Gregory Ditzler
Shadows Aren't So Dangerous After All: A Fast and Robust Defense Against Shadow-Based Adversarial Attacks
This is a draft version - our core results are reported, but additional experiments for journal submission are still being run
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Robust classification is essential in tasks like autonomous vehicle sign recognition, where the downsides of misclassification can be grave. Adversarial attacks threaten the robustness of neural network classifiers, causing them to consistently and confidently misidentify road signs. One such class of attack, shadow-...
[ { "created": "Thu, 18 Aug 2022 00:19:01 GMT", "version": "v1" }, { "created": "Thu, 29 Sep 2022 03:22:02 GMT", "version": "v2" } ]
2022-10-03
[ [ "Wang", "Andrew", "" ], [ "Mayor", "Wyatt", "" ], [ "Smith", "Ryan", "" ], [ "Nookula", "Gopal", "" ], [ "Ditzler", "Gregory", "" ] ]
Robust classification is essential in tasks like autonomous vehicle sign recognition, where the downsides of misclassification can be grave. Adversarial attacks threaten the robustness of neural network classifiers, causing them to consistently and confidently misidentify road signs. One such class of attack, shadow-ba...
0909.5119
Marios Kountouris
Jeffrey G. Andrews, Steven Weber, Marios Kountouris, Martin Haenggi
Random Access Transport Capacity
Submitted to IEEE Trans. on Wireless Communications, Sept. 2009
null
10.1109/TWC.2010.06.091432
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We develop a new metric for quantifying end-to-end throughput in multihop wireless networks, which we term random access transport capacity, since the interference model presumes uncoordinated transmissions. The metric quantifies the average maximum rate of successful end-to-end transmissions, multiplied by the commu...
[ { "created": "Mon, 28 Sep 2009 16:34:00 GMT", "version": "v1" } ]
2016-11-18
[ [ "Andrews", "Jeffrey G.", "" ], [ "Weber", "Steven", "" ], [ "Kountouris", "Marios", "" ], [ "Haenggi", "Martin", "" ] ]
We develop a new metric for quantifying end-to-end throughput in multihop wireless networks, which we term random access transport capacity, since the interference model presumes uncoordinated transmissions. The metric quantifies the average maximum rate of successful end-to-end transmissions, multiplied by the communi...
2202.02294
Yue Cao
Yue Cao, Fatemeh H. Fard
Pre-Trained Neural Language Models for Automatic Mobile App User Feedback Answer Generation
6 pages, published in the 2021 ASE RAISE workshop
null
null
null
cs.CL cs.LG cs.SE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Studies show that developers' answers to the mobile app users' feedbacks on app stores can increase the apps' star rating. To help app developers generate answers that are related to the users' issues, recent studies develop models to generate the answers automatically. Aims: The app response generation models use de...
[ { "created": "Fri, 4 Feb 2022 18:26:55 GMT", "version": "v1" } ]
2022-02-07
[ [ "Cao", "Yue", "" ], [ "Fard", "Fatemeh H.", "" ] ]
Studies show that developers' answers to the mobile app users' feedbacks on app stores can increase the apps' star rating. To help app developers generate answers that are related to the users' issues, recent studies develop models to generate the answers automatically. Aims: The app response generation models use deep...
2408.04142
Ruben Castro Ornelas
Rub\'en Castro Ornelas, Tom\'as Cant\'u, Isabel Sperandio, Alexander H. Slocum, and Pulkit Agrawal
Everyday Finger: A Robotic Finger that Meets the Needs of Everyday Interactive Manipulation
9.5 pages + references, 14 figures, extended/updated version of article to appear in IEEE ICRA 2024 proceedings
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We provide the mechanical and dynamical requirements for a robotic finger capable of performing thirty diverse everyday tasks. To match these requirements, we present a finger design based on series-elastic actuation that we call the everyday finger. Our focus is to make the fingers as compact as possible while achie...
[ { "created": "Thu, 8 Aug 2024 01:00:45 GMT", "version": "v1" } ]
2024-08-09
[ [ "Ornelas", "Rubén Castro", "" ], [ "Cantú", "Tomás", "" ], [ "Sperandio", "Isabel", "" ], [ "Slocum", "Alexander H.", "" ], [ "Agrawal", "Pulkit", "" ] ]
We provide the mechanical and dynamical requirements for a robotic finger capable of performing thirty diverse everyday tasks. To match these requirements, we present a finger design based on series-elastic actuation that we call the everyday finger. Our focus is to make the fingers as compact as possible while achievi...
1303.6867
Bang Ye Wu
Bang Ye Wu and Li-Hsuan Chen
Parameterized algorithms for the 2-clustering problem with minimum sum and minimum sum of squares objective functions
journal version
null
10.1007/s00453-014-9874-8
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In the {\sc Min-Sum 2-Clustering} problem, we are given a graph and a parameter $k$, and the goal is to determine if there exists a 2-partition of the vertex set such that the total conflict number is at most $k$, where the conflict number of a vertex is the number of its non-neighbors in the same cluster and neighbo...
[ { "created": "Wed, 27 Mar 2013 15:57:58 GMT", "version": "v1" }, { "created": "Thu, 6 Feb 2014 04:35:17 GMT", "version": "v2" } ]
2014-04-11
[ [ "Wu", "Bang Ye", "" ], [ "Chen", "Li-Hsuan", "" ] ]
In the {\sc Min-Sum 2-Clustering} problem, we are given a graph and a parameter $k$, and the goal is to determine if there exists a 2-partition of the vertex set such that the total conflict number is at most $k$, where the conflict number of a vertex is the number of its non-neighbors in the same cluster and neighbors...
2309.13216
Aadhar Chauhan
Aadhar Chauhan, Isaac Remy, Danny Broyles, and Karen Leung
MISFIT-V: Misaligned Image Synthesis and Fusion using Information from Thermal and Visual
null
null
null
null
cs.CV cs.AI cs.HC cs.RO
http://creativecommons.org/licenses/by-sa/4.0/
Detecting humans from airborne visual and thermal imagery is a fundamental challenge for Wilderness Search-and-Rescue (WiSAR) teams, who must perform this function accurately in the face of immense pressure. The ability to fuse these two sensor modalities can potentially reduce the cognitive load on human operators a...
[ { "created": "Fri, 22 Sep 2023 23:41:24 GMT", "version": "v1" } ]
2023-09-26
[ [ "Chauhan", "Aadhar", "" ], [ "Remy", "Isaac", "" ], [ "Broyles", "Danny", "" ], [ "Leung", "Karen", "" ] ]
Detecting humans from airborne visual and thermal imagery is a fundamental challenge for Wilderness Search-and-Rescue (WiSAR) teams, who must perform this function accurately in the face of immense pressure. The ability to fuse these two sensor modalities can potentially reduce the cognitive load on human operators and...
0802.2862
Pascal Weil
Dietrich Kuske
Compatibility of Shelah and Stupp's and Muchnik's iteration with fragments of monadic second order logic
null
Dans Proceedings of the 25th Annual Symposium on the Theoretical Aspects of Computer Science - STACS 2008, Bordeaux : France (2008)
null
null
cs.LO
null
We investigate the relation between the theory of the iterations in the sense of Shelah-Stupp and of Muchnik, resp., and the theory of the base structure for several logics. These logics are obtained from the restriction of set quantification in monadic second order logic to certain subsets like, e.g., finite sets, c...
[ { "created": "Wed, 20 Feb 2008 14:33:04 GMT", "version": "v1" } ]
2008-02-21
[ [ "Kuske", "Dietrich", "" ] ]
We investigate the relation between the theory of the iterations in the sense of Shelah-Stupp and of Muchnik, resp., and the theory of the base structure for several logics. These logics are obtained from the restriction of set quantification in monadic second order logic to certain subsets like, e.g., finite sets, cha...
2002.11614
Adrian Korban
Steven T. Dougherty, Joe Gildea, Adrian Korban and Abidin Kaya
Composite Matrices from Group Rings, Composite G-Codes and Constructions of Self-Dual Codes
33 pages
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this work, we define composite matrices which are derived from group rings. We extend the idea of G-codes to composite G-codes. We show that these codes are ideals in a group ring, where the ring is a finite commutative Frobenius ring and G is an arbitrary finite group. We prove that the dual of a composite G-code...
[ { "created": "Wed, 26 Feb 2020 16:55:46 GMT", "version": "v1" } ]
2020-02-27
[ [ "Dougherty", "Steven T.", "" ], [ "Gildea", "Joe", "" ], [ "Korban", "Adrian", "" ], [ "Kaya", "Abidin", "" ] ]
In this work, we define composite matrices which are derived from group rings. We extend the idea of G-codes to composite G-codes. We show that these codes are ideals in a group ring, where the ring is a finite commutative Frobenius ring and G is an arbitrary finite group. We prove that the dual of a composite G-code i...
2405.21044
Houston Claure
Houston Claure
Designing for Fairness in Human-Robot Interactions
null
null
null
null
cs.RO cs.HC
http://creativecommons.org/licenses/by/4.0/
The foundation of successful human collaboration is deeply rooted in the principles of fairness. As robots are increasingly prevalent in various parts of society where they are working alongside groups and teams of humans, their ability to understand and act according to principles of fairness becomes crucial for the...
[ { "created": "Fri, 31 May 2024 17:38:19 GMT", "version": "v1" } ]
2024-06-03
[ [ "Claure", "Houston", "" ] ]
The foundation of successful human collaboration is deeply rooted in the principles of fairness. As robots are increasingly prevalent in various parts of society where they are working alongside groups and teams of humans, their ability to understand and act according to principles of fairness becomes crucial for their...
2008.10150
Daniel Hsu
Christopher Tosh, Akshay Krishnamurthy, Daniel Hsu
Contrastive learning, multi-view redundancy, and linear models
null
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Self-supervised learning is an empirically successful approach to unsupervised learning based on creating artificial supervised learning problems. A popular self-supervised approach to representation learning is contrastive learning, which leverages naturally occurring pairs of similar and dissimilar data points, or ...
[ { "created": "Mon, 24 Aug 2020 01:31:47 GMT", "version": "v1" }, { "created": "Wed, 14 Apr 2021 19:19:55 GMT", "version": "v2" } ]
2021-04-16
[ [ "Tosh", "Christopher", "" ], [ "Krishnamurthy", "Akshay", "" ], [ "Hsu", "Daniel", "" ] ]
Self-supervised learning is an empirically successful approach to unsupervised learning based on creating artificial supervised learning problems. A popular self-supervised approach to representation learning is contrastive learning, which leverages naturally occurring pairs of similar and dissimilar data points, or mu...
2404.02696
Behrooz Razeghi
Behrooz Razeghi, Parsa Rahimi, S\'ebastien Marcel
Deep Privacy Funnel Model: From a Discriminative to a Generative Approach with an Application to Face Recognition
null
null
null
null
cs.LG
http://creativecommons.org/licenses/by/4.0/
In this study, we apply the information-theoretic Privacy Funnel (PF) model to the domain of face recognition, developing a novel method for privacy-preserving representation learning within an end-to-end training framework. Our approach addresses the trade-off between obfuscation and utility in data protection, quan...
[ { "created": "Wed, 3 Apr 2024 12:50:45 GMT", "version": "v1" } ]
2024-04-04
[ [ "Razeghi", "Behrooz", "" ], [ "Rahimi", "Parsa", "" ], [ "Marcel", "Sébastien", "" ] ]
In this study, we apply the information-theoretic Privacy Funnel (PF) model to the domain of face recognition, developing a novel method for privacy-preserving representation learning within an end-to-end training framework. Our approach addresses the trade-off between obfuscation and utility in data protection, quanti...
1904.02461
Inigo Jauregi Unanue
Inigo Jauregi Unanue, Ehsan Zare Borzeshi, Nazanin Esmaili, Massimo Piccardi
ReWE: Regressing Word Embeddings for Regularization of Neural Machine Translation Systems
Accepted at NAACL-HLT 2019
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Regularization of neural machine translation is still a significant problem, especially in low-resource settings. To mollify this problem, we propose regressing word embeddings (ReWE) as a new regularization technique in a system that is jointly trained to predict the next word in the translation (categorical value) ...
[ { "created": "Thu, 4 Apr 2019 10:30:52 GMT", "version": "v1" } ]
2019-04-05
[ [ "Unanue", "Inigo Jauregi", "" ], [ "Borzeshi", "Ehsan Zare", "" ], [ "Esmaili", "Nazanin", "" ], [ "Piccardi", "Massimo", "" ] ]
Regularization of neural machine translation is still a significant problem, especially in low-resource settings. To mollify this problem, we propose regressing word embeddings (ReWE) as a new regularization technique in a system that is jointly trained to predict the next word in the translation (categorical value) an...
2307.00618
Leonard Papenmeier
Leonard Papenmeier, Luigi Nardi, Matthias Poloczek
Bounce: Reliable High-Dimensional Bayesian Optimization for Combinatorial and Mixed Spaces
30 pages, 22 figures
Advances in Neural Information Processing Systems 36 (NeurIPS 2023)
null
null
cs.LG
http://creativecommons.org/licenses/by/4.0/
Impactful applications such as materials discovery, hardware design, neural architecture search, or portfolio optimization require optimizing high-dimensional black-box functions with mixed and combinatorial input spaces. While Bayesian optimization has recently made significant progress in solving such problems, an ...
[ { "created": "Sun, 2 Jul 2023 17:18:17 GMT", "version": "v1" }, { "created": "Wed, 20 Mar 2024 15:17:43 GMT", "version": "v2" } ]
2024-03-21
[ [ "Papenmeier", "Leonard", "" ], [ "Nardi", "Luigi", "" ], [ "Poloczek", "Matthias", "" ] ]
Impactful applications such as materials discovery, hardware design, neural architecture search, or portfolio optimization require optimizing high-dimensional black-box functions with mixed and combinatorial input spaces. While Bayesian optimization has recently made significant progress in solving such problems, an in...