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1304.7392
John Kieffer
Jie Zhang, En-hui Yang, John C. Kieffer
A Universal Grammar-Based Code For Lossless Compression of Binary Trees
null
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We consider the problem of lossless compression of binary trees, with the aim of reducing the number of code bits needed to store or transmit such trees. A lossless grammar-based code is presented which encodes each binary tree into a binary codeword in two steps. In the first step, the tree is transformed into a con...
[ { "created": "Sat, 27 Apr 2013 18:02:53 GMT", "version": "v1" } ]
2013-04-30
[ [ "Zhang", "Jie", "" ], [ "Yang", "En-hui", "" ], [ "Kieffer", "John C.", "" ] ]
We consider the problem of lossless compression of binary trees, with the aim of reducing the number of code bits needed to store or transmit such trees. A lossless grammar-based code is presented which encodes each binary tree into a binary codeword in two steps. In the first step, the tree is transformed into a conte...
2112.10356
Roland Croft
Roland Croft, M. Ali Babar, Li Li
An Investigation into Inconsistency of Software Vulnerability Severity across Data Sources
Accepted for publication in SANER 22
null
null
null
cs.SE cs.CR
http://creativecommons.org/licenses/by/4.0/
Software Vulnerability (SV) severity assessment is a vital task for informing SV remediation and triage. Ranking of SV severity scores is often used to advise prioritization of patching efforts. However, severity assessment is a difficult and subjective manual task that relies on expertise, knowledge, and standardize...
[ { "created": "Mon, 20 Dec 2021 06:36:19 GMT", "version": "v1" }, { "created": "Sun, 16 Jan 2022 09:22:37 GMT", "version": "v2" } ]
2022-01-19
[ [ "Croft", "Roland", "" ], [ "Babar", "M. Ali", "" ], [ "Li", "Li", "" ] ]
Software Vulnerability (SV) severity assessment is a vital task for informing SV remediation and triage. Ranking of SV severity scores is often used to advise prioritization of patching efforts. However, severity assessment is a difficult and subjective manual task that relies on expertise, knowledge, and standardized ...
2009.05983
Mengdi Xu
Wentai Lei, Mengdi Xu, Feifei Hou, Wensi Jiang
Calibration Venus: An Interactive Camera Calibration Method Based on Search Algorithm and Pose Decomposition
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In many scenarios where cameras are applied, such as robot positioning and unmanned driving, camera calibration is one of the most important pre-work. The interactive calibration method based on the plane board is becoming popular in camera calibration field due to its repeatability and operation advantages. However,...
[ { "created": "Sun, 13 Sep 2020 12:12:10 GMT", "version": "v1" } ]
2020-10-14
[ [ "Lei", "Wentai", "" ], [ "Xu", "Mengdi", "" ], [ "Hou", "Feifei", "" ], [ "Jiang", "Wensi", "" ] ]
In many scenarios where cameras are applied, such as robot positioning and unmanned driving, camera calibration is one of the most important pre-work. The interactive calibration method based on the plane board is becoming popular in camera calibration field due to its repeatability and operation advantages. However, t...
2006.11645
Tsung-Yen Yang
Tsung-Yen Yang and Justinian Rosca and Karthik Narasimhan and Peter J. Ramadge
Accelerating Safe Reinforcement Learning with Constraint-mismatched Policies
International Conference on Machine Learning (ICML) 2021
null
null
null
cs.LG cs.AI cs.RO stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We consider the problem of reinforcement learning when provided with (1) a baseline control policy and (2) a set of constraints that the learner must satisfy. The baseline policy can arise from demonstration data or a teacher agent and may provide useful cues for learning, but it might also be sub-optimal for the tas...
[ { "created": "Sat, 20 Jun 2020 20:20:47 GMT", "version": "v1" }, { "created": "Wed, 7 Oct 2020 05:08:21 GMT", "version": "v2" }, { "created": "Sat, 10 Jul 2021 02:55:37 GMT", "version": "v3" } ]
2021-07-13
[ [ "Yang", "Tsung-Yen", "" ], [ "Rosca", "Justinian", "" ], [ "Narasimhan", "Karthik", "" ], [ "Ramadge", "Peter J.", "" ] ]
We consider the problem of reinforcement learning when provided with (1) a baseline control policy and (2) a set of constraints that the learner must satisfy. The baseline policy can arise from demonstration data or a teacher agent and may provide useful cues for learning, but it might also be sub-optimal for the task ...
2401.10487
Peiwen Yuan
Peiwen Yuan, Xinglin Wang, Shaoxiong Feng, Boyuan Pan, Yiwei Li, Heda Wang, Xupeng Miao, Kan Li
Generative Dense Retrieval: Memory Can Be a Burden
EACL 2024 main
EACL 2024 main
null
null
cs.IR cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Generative Retrieval (GR), autoregressively decoding relevant document identifiers given a query, has been shown to perform well under the setting of small-scale corpora. By memorizing the document corpus with model parameters, GR implicitly achieves deep interaction between query and document. However, such a memori...
[ { "created": "Fri, 19 Jan 2024 04:24:07 GMT", "version": "v1" } ]
2024-01-22
[ [ "Yuan", "Peiwen", "" ], [ "Wang", "Xinglin", "" ], [ "Feng", "Shaoxiong", "" ], [ "Pan", "Boyuan", "" ], [ "Li", "Yiwei", "" ], [ "Wang", "Heda", "" ], [ "Miao", "Xupeng", "" ], [ "Li", "Kan", ...
Generative Retrieval (GR), autoregressively decoding relevant document identifiers given a query, has been shown to perform well under the setting of small-scale corpora. By memorizing the document corpus with model parameters, GR implicitly achieves deep interaction between query and document. However, such a memorizi...
1910.04162
Yizhen Chen
Yizhen Chen
Mobile Sensor Networks: Bounds on Capacity and Complexity of Realizability
24 pages, 14 figures
null
null
null
cs.DM cs.CC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We develop the mathematical theory of a model, constructed by C. Gu, I. Downes, O. Gnawali, and L. Guibas, of networks that diffuse continuously acquired information from mobile sensor nodes. We prove new results on the maximum, minimum, and expected capacity of their model of combinatorial and geometric mobile senso...
[ { "created": "Wed, 9 Oct 2019 14:48:31 GMT", "version": "v1" }, { "created": "Tue, 21 Jan 2020 23:20:58 GMT", "version": "v2" }, { "created": "Tue, 2 Feb 2021 00:04:54 GMT", "version": "v3" } ]
2021-02-03
[ [ "Chen", "Yizhen", "" ] ]
We develop the mathematical theory of a model, constructed by C. Gu, I. Downes, O. Gnawali, and L. Guibas, of networks that diffuse continuously acquired information from mobile sensor nodes. We prove new results on the maximum, minimum, and expected capacity of their model of combinatorial and geometric mobile sensor ...
1805.02020
Wu Yantong
YanTong Wu, Yang Liu
Position Estimation of Camera Based on Unsupervised Learning
6 pages,5 figures,1 table
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
It is an exciting task to recover the scene's 3d-structure and camera pose from the video sequence. Most of the current solutions divide it into two parts, monocular depth recovery and camera pose estimation. The monocular depth recovery is often studied as an independent part, and a better depth estimation is used t...
[ { "created": "Sat, 5 May 2018 08:35:23 GMT", "version": "v1" } ]
2018-05-24
[ [ "Wu", "YanTong", "" ], [ "Liu", "Yang", "" ] ]
It is an exciting task to recover the scene's 3d-structure and camera pose from the video sequence. Most of the current solutions divide it into two parts, monocular depth recovery and camera pose estimation. The monocular depth recovery is often studied as an independent part, and a better depth estimation is used to ...
1804.03079
Jinseok Choi
Jinseok Choi, Gilwon Lee, and Brian L. Evans
User Scheduling for Millimeter Wave Hybrid Beamforming Systems with Low-Resolution ADCs
Submitted to Transactions on Wireless Communications
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We investigate uplink user scheduling for millimeter wave (mmWave) hybrid analog/digital beamforming systems with low-resolution analog-to-digital converters (ADCs). Deriving new scheduling criteria for the mmWave systems, we show that the channel structure in the beamspace, in addition to the channel magnitude and o...
[ { "created": "Mon, 9 Apr 2018 16:11:17 GMT", "version": "v1" }, { "created": "Fri, 24 Aug 2018 04:47:01 GMT", "version": "v2" }, { "created": "Fri, 15 Feb 2019 04:10:22 GMT", "version": "v3" } ]
2019-02-18
[ [ "Choi", "Jinseok", "" ], [ "Lee", "Gilwon", "" ], [ "Evans", "Brian L.", "" ] ]
We investigate uplink user scheduling for millimeter wave (mmWave) hybrid analog/digital beamforming systems with low-resolution analog-to-digital converters (ADCs). Deriving new scheduling criteria for the mmWave systems, we show that the channel structure in the beamspace, in addition to the channel magnitude and ort...
2305.01140
Minkai Xu
Minkai Xu, Alexander Powers, Ron Dror, Stefano Ermon, Jure Leskovec
Geometric Latent Diffusion Models for 3D Molecule Generation
Published at ICML 2023
null
null
null
cs.LG q-bio.QM
http://creativecommons.org/licenses/by/4.0/
Generative models, especially diffusion models (DMs), have achieved promising results for generating feature-rich geometries and advancing foundational science problems such as molecule design. Inspired by the recent huge success of Stable (latent) Diffusion models, we propose a novel and principled method for 3D mol...
[ { "created": "Tue, 2 May 2023 01:07:22 GMT", "version": "v1" } ]
2023-05-03
[ [ "Xu", "Minkai", "" ], [ "Powers", "Alexander", "" ], [ "Dror", "Ron", "" ], [ "Ermon", "Stefano", "" ], [ "Leskovec", "Jure", "" ] ]
Generative models, especially diffusion models (DMs), have achieved promising results for generating feature-rich geometries and advancing foundational science problems such as molecule design. Inspired by the recent huge success of Stable (latent) Diffusion models, we propose a novel and principled method for 3D molec...
1607.04320
Roman Golubovski
Vanco Cabukovski, Roman Golubovski, Riste Temjanovski
Learning Repository Adaptibility in an Agent-Based University Environment
14 pages 4 figures
null
null
null
cs.CY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Automated e-Learning Systems (AeLS) are fundamental to contemporary educational concepts worldwide. It has become a standard not only in support to the formal curriculum, but containing social platform capabilities, gamification elements and functionalities fostering communities of experts, also for faster knowledge ...
[ { "created": "Wed, 13 Jul 2016 08:45:15 GMT", "version": "v1" } ]
2016-07-18
[ [ "Cabukovski", "Vanco", "" ], [ "Golubovski", "Roman", "" ], [ "Temjanovski", "Riste", "" ] ]
Automated e-Learning Systems (AeLS) are fundamental to contemporary educational concepts worldwide. It has become a standard not only in support to the formal curriculum, but containing social platform capabilities, gamification elements and functionalities fostering communities of experts, also for faster knowledge di...
2401.00434
Cheng Deng
Zhouhan Lin, Cheng Deng, Le Zhou, Tianhang Zhang, Yi Xu, Yutong Xu, Zhongmou He, Yuanyuan Shi, Beiya Dai, Yunchong Song, Boyi Zeng, Qiyuan Chen, Yuxun Miao, Bo Xue, Shu Wang, Luoyi Fu, Weinan Zhang, Junxian He, Yunqiang Zhu, Xinbing Wang, Chenghu Zhou
GeoGalactica: A Scientific Large Language Model in Geoscience
null
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Large language models (LLMs) have achieved huge success for their general knowledge and ability to solve a wide spectrum of tasks in natural language processing (NLP). Due to their impressive abilities, LLMs have shed light on potential inter-discipline applications to foster scientific discoveries of a specific doma...
[ { "created": "Sun, 31 Dec 2023 09:22:54 GMT", "version": "v1" }, { "created": "Sat, 13 Apr 2024 17:05:03 GMT", "version": "v2" } ]
2024-04-16
[ [ "Lin", "Zhouhan", "" ], [ "Deng", "Cheng", "" ], [ "Zhou", "Le", "" ], [ "Zhang", "Tianhang", "" ], [ "Xu", "Yi", "" ], [ "Xu", "Yutong", "" ], [ "He", "Zhongmou", "" ], [ "Shi", "Yuanyuan", ...
Large language models (LLMs) have achieved huge success for their general knowledge and ability to solve a wide spectrum of tasks in natural language processing (NLP). Due to their impressive abilities, LLMs have shed light on potential inter-discipline applications to foster scientific discoveries of a specific domain...
2204.11526
Su Lu
Su Lu, Han-Jia Ye, De-Chuan Zhan
Selective Cross-Task Distillation
null
null
null
null
cs.LG cs.CV
http://creativecommons.org/licenses/by-nc-sa/4.0/
The outpouring of various pre-trained models empowers knowledge distillation by providing abundant teacher resources, but there lacks a developed mechanism to utilize these teachers adequately. With a massive model repository composed of teachers pre-trained on diverse tasks, we must surmount two obstacles when using...
[ { "created": "Mon, 25 Apr 2022 09:34:37 GMT", "version": "v1" }, { "created": "Thu, 16 Jun 2022 05:57:58 GMT", "version": "v2" }, { "created": "Wed, 28 Sep 2022 01:43:56 GMT", "version": "v3" } ]
2022-09-29
[ [ "Lu", "Su", "" ], [ "Ye", "Han-Jia", "" ], [ "Zhan", "De-Chuan", "" ] ]
The outpouring of various pre-trained models empowers knowledge distillation by providing abundant teacher resources, but there lacks a developed mechanism to utilize these teachers adequately. With a massive model repository composed of teachers pre-trained on diverse tasks, we must surmount two obstacles when using k...
2007.02484
Florian Richter
Florian Richter
Logic, Language, and Calculus
null
null
null
null
cs.LO cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The difference between object-language and metalanguage is crucial for logical analysis, but has yet not been examined for the field of computer science. In this paper the difference is examined with regard to inferential relations. It is argued that inferential relations in a metalanguage (like a calculus for propos...
[ { "created": "Mon, 6 Jul 2020 00:52:54 GMT", "version": "v1" } ]
2020-07-07
[ [ "Richter", "Florian", "" ] ]
The difference between object-language and metalanguage is crucial for logical analysis, but has yet not been examined for the field of computer science. In this paper the difference is examined with regard to inferential relations. It is argued that inferential relations in a metalanguage (like a calculus for proposit...
2111.09815
Dingwen Tao
Sian Jin, Sheng Di, Jiannan Tian, Suren Byna, Dingwen Tao, Franck Cappello
Improving Prediction-Based Lossy Compression Dramatically via Ratio-Quality Modeling
14 pages, 14 figures, published by IEEE ICDE 2022
null
null
null
cs.DB cs.DC
http://creativecommons.org/licenses/by/4.0/
Error-bounded lossy compression is one of the most effective techniques for scientific data reduction. However, the traditional trial-and-error approach used to configure lossy compressors for finding the optimal trade-off between reconstructed data quality and compression ratio is prohibitively expensive. To resolve...
[ { "created": "Thu, 18 Nov 2021 17:29:42 GMT", "version": "v1" }, { "created": "Sun, 28 Nov 2021 11:43:56 GMT", "version": "v2" }, { "created": "Thu, 10 Mar 2022 01:11:10 GMT", "version": "v3" }, { "created": "Wed, 23 Mar 2022 23:02:43 GMT", "version": "v4" }, { "c...
2022-05-09
[ [ "Jin", "Sian", "" ], [ "Di", "Sheng", "" ], [ "Tian", "Jiannan", "" ], [ "Byna", "Suren", "" ], [ "Tao", "Dingwen", "" ], [ "Cappello", "Franck", "" ] ]
Error-bounded lossy compression is one of the most effective techniques for scientific data reduction. However, the traditional trial-and-error approach used to configure lossy compressors for finding the optimal trade-off between reconstructed data quality and compression ratio is prohibitively expensive. To resolve t...
2301.08564
Spyridon Mastorakis
Sifat Ut Taki and Spyridon Mastorakis
An NDN-Enabled Fog Radio Access Network Architecture With Distributed In-Network Caching
Accepted for publication by IEEE ICC 2023
null
null
null
cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
To meet the increasing demands of next-generation cellular networks (e.g., 6G), advanced networking technologies must be incorporated. On one hand, the Fog Radio Access Network (F-RAN), has been proposed as an enhancement to the Cloud Radio Access Network (C-RAN). On the other hand, efficient network architectures, s...
[ { "created": "Wed, 18 Jan 2023 22:41:01 GMT", "version": "v1" } ]
2023-01-23
[ [ "Taki", "Sifat Ut", "" ], [ "Mastorakis", "Spyridon", "" ] ]
To meet the increasing demands of next-generation cellular networks (e.g., 6G), advanced networking technologies must be incorporated. On one hand, the Fog Radio Access Network (F-RAN), has been proposed as an enhancement to the Cloud Radio Access Network (C-RAN). On the other hand, efficient network architectures, suc...
1602.08680
Shangwen Li
Shangwen Li, Sanjay Purushotham, Chen Chen, Yuzhuo Ren, and C.-C. Jay Kuo
Measuring and Predicting Tag Importance for Image Retrieval
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Textual data such as tags, sentence descriptions are combined with visual cues to reduce the semantic gap for image retrieval applications in today's Multimodal Image Retrieval (MIR) systems. However, all tags are treated as equally important in these systems, which may result in misalignment between visual and textu...
[ { "created": "Sun, 28 Feb 2016 07:38:25 GMT", "version": "v1" }, { "created": "Thu, 14 Apr 2016 18:13:21 GMT", "version": "v2" }, { "created": "Mon, 9 Jan 2017 22:32:36 GMT", "version": "v3" } ]
2017-01-11
[ [ "Li", "Shangwen", "" ], [ "Purushotham", "Sanjay", "" ], [ "Chen", "Chen", "" ], [ "Ren", "Yuzhuo", "" ], [ "Kuo", "C. -C. Jay", "" ] ]
Textual data such as tags, sentence descriptions are combined with visual cues to reduce the semantic gap for image retrieval applications in today's Multimodal Image Retrieval (MIR) systems. However, all tags are treated as equally important in these systems, which may result in misalignment between visual and textual...
1307.7429
Seyyed Reza Khaze
Amin Babazadeh Sangar, Seyyed Reza Khaze, Laya Ebrahimi
Participation anticipating in elections using data mining methods
null
International Journal on Cybernetics & Informatics ( IJCI) Vol.2, No.2, April2013
null
null
cs.CY cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Anticipating the political behavior of people will be considerable help for election candidates to assess the possibility of their success and to be acknowledged about the public motivations to select them. In this paper, we provide a general schematic of the architecture of participation anticipating system in presi...
[ { "created": "Mon, 29 Jul 2013 01:15:25 GMT", "version": "v1" } ]
2013-07-31
[ [ "Sangar", "Amin Babazadeh", "" ], [ "Khaze", "Seyyed Reza", "" ], [ "Ebrahimi", "Laya", "" ] ]
Anticipating the political behavior of people will be considerable help for election candidates to assess the possibility of their success and to be acknowledged about the public motivations to select them. In this paper, we provide a general schematic of the architecture of participation anticipating system in preside...
1011.2656
Carsten Schneider
Johannes Bluemlein and Sebastian Klein and Carsten Schneider and Flavia Stan
A Symbolic Summation Approach to Feynman Integral Calculus
null
J. Symbolic Comput. 47, pp. 1267-1289. 2012
10.1016/j.jsc.2011.12.044
DESY 10-185, TTK-10-49, SFB-CPP/10-107
cs.SC hep-ph hep-th math-ph math.MP
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Given a Feynman parameter integral, depending on a single discrete variable $N$ and a real parameter $\epsilon$, we discuss a new algorithmic framework to compute the first coefficients of its Laurent series expansion in $\epsilon$. In a first step, the integrals are expressed by hypergeometric multi-sums by means of...
[ { "created": "Thu, 11 Nov 2010 13:49:35 GMT", "version": "v1" }, { "created": "Wed, 30 May 2012 09:27:18 GMT", "version": "v2" } ]
2012-05-31
[ [ "Bluemlein", "Johannes", "" ], [ "Klein", "Sebastian", "" ], [ "Schneider", "Carsten", "" ], [ "Stan", "Flavia", "" ] ]
Given a Feynman parameter integral, depending on a single discrete variable $N$ and a real parameter $\epsilon$, we discuss a new algorithmic framework to compute the first coefficients of its Laurent series expansion in $\epsilon$. In a first step, the integrals are expressed by hypergeometric multi-sums by means of s...
2207.01229
Susmit Agrawal
K. Ram Prabhakar, Susmit Agrawal, R. Venkatesh Babu
Segmentation Guided Deep HDR Deghosting
null
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
We present a motion segmentation guided convolutional neural network (CNN) approach for high dynamic range (HDR) image deghosting. First, we segment the moving regions in the input sequence using a CNN. Then, we merge static and moving regions separately with different fusion networks and combine fused features to ge...
[ { "created": "Mon, 4 Jul 2022 06:49:27 GMT", "version": "v1" } ]
2022-07-05
[ [ "Prabhakar", "K. Ram", "" ], [ "Agrawal", "Susmit", "" ], [ "Babu", "R. Venkatesh", "" ] ]
We present a motion segmentation guided convolutional neural network (CNN) approach for high dynamic range (HDR) image deghosting. First, we segment the moving regions in the input sequence using a CNN. Then, we merge static and moving regions separately with different fusion networks and combine fused features to gene...
1906.00482
Fabian Kuhn
Mohsen Ghaffari and Fabian Kuhn
On the Use of Randomness in Local Distributed Graph Algorithms
21 pages, conference version in ACM Symp. on Principles of Distributed Computing (PODC) 2019
null
null
null
cs.DS cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We attempt to better understand randomization in local distributed graph algorithms by exploring how randomness is used and what we can gain from it: - We first ask the question of how much randomness is needed to obtain efficient randomized algorithms. We show that for all locally checkable problems for which polylo...
[ { "created": "Sun, 2 Jun 2019 20:51:15 GMT", "version": "v1" } ]
2019-06-04
[ [ "Ghaffari", "Mohsen", "" ], [ "Kuhn", "Fabian", "" ] ]
We attempt to better understand randomization in local distributed graph algorithms by exploring how randomness is used and what we can gain from it: - We first ask the question of how much randomness is needed to obtain efficient randomized algorithms. We show that for all locally checkable problems for which polylog ...
2309.03023
Heiko Paulheim
Patryk Preisner, Heiko Paulheim
Universal Preprocessing Operators for Embedding Knowledge Graphs with Literals
Accepted for DL4KG Workshop at ISWC 2023
null
null
null
cs.AI cs.LG
http://creativecommons.org/licenses/by/4.0/
Knowledge graph embeddings are dense numerical representations of entities in a knowledge graph (KG). While the majority of approaches concentrate only on relational information, i.e., relations between entities, fewer approaches exist which also take information about literal values (e.g., textual descriptions or nu...
[ { "created": "Wed, 6 Sep 2023 14:08:46 GMT", "version": "v1" } ]
2023-09-07
[ [ "Preisner", "Patryk", "" ], [ "Paulheim", "Heiko", "" ] ]
Knowledge graph embeddings are dense numerical representations of entities in a knowledge graph (KG). While the majority of approaches concentrate only on relational information, i.e., relations between entities, fewer approaches exist which also take information about literal values (e.g., textual descriptions or nume...
cs/0604038
Evgueni Petrov
E. Petrov, Yu. Kostov, E. Botoeva
UniCalc.LIN: a linear constraint solver for the UniCalc system
rejected by the programm committee of the conforence on Perspective of System Informatics held in Novosibirsk, Russian Federation July 2006
null
null
null
cs.MS cs.AI
null
In this short paper we present a linear constraint solver for the UniCalc system, an environment for reliable solution of mathematical modeling problems.
[ { "created": "Mon, 10 Apr 2006 06:30:02 GMT", "version": "v1" } ]
2007-05-23
[ [ "Petrov", "E.", "" ], [ "Kostov", "Yu.", "" ], [ "Botoeva", "E.", "" ] ]
In this short paper we present a linear constraint solver for the UniCalc system, an environment for reliable solution of mathematical modeling problems.
2204.03873
Cun Zhang
Cun Zhang, Xing-Peng Chen, Guo-Qiang Han, Xiang-Jie Liu
Spatial Transformer Network on Skeleton-based Gait Recognition
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Skeleton-based gait recognition models usually suffer from the robustness problem, as the Rank-1 accuracy varies from 90\% in normal walking cases to 70\% in walking with coats cases. In this work, we propose a state-of-the-art robust skeleton-based gait recognition model called Gait-TR, which is based on the combina...
[ { "created": "Fri, 8 Apr 2022 06:53:23 GMT", "version": "v1" } ]
2022-04-11
[ [ "Zhang", "Cun", "" ], [ "Chen", "Xing-Peng", "" ], [ "Han", "Guo-Qiang", "" ], [ "Liu", "Xiang-Jie", "" ] ]
Skeleton-based gait recognition models usually suffer from the robustness problem, as the Rank-1 accuracy varies from 90\% in normal walking cases to 70\% in walking with coats cases. In this work, we propose a state-of-the-art robust skeleton-based gait recognition model called Gait-TR, which is based on the combinati...
1902.02292
Praveen Venkatesh
Praveen Venkatesh, Sanghamitra Dutta, Pulkit Grover
Information Flow in Computational Systems
Significantly revised version which was accepted for publication at the IEEE Transactions on Information Theory
IEEE Transactions on Information Theory, September 2020
10.1109/TIT.2020.2987806
Volume: 66, Issue: 9, pages 5456 - 5491
cs.IT math.IT q-bio.NC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We develop a theoretical framework for defining and identifying flows of information in computational systems. Here, a computational system is assumed to be a directed graph, with "clocked" nodes that send transmissions to each other along the edges of the graph at discrete points in time. We are interested in a defi...
[ { "created": "Wed, 6 Feb 2019 17:38:54 GMT", "version": "v1" }, { "created": "Thu, 7 Feb 2019 21:13:46 GMT", "version": "v2" }, { "created": "Mon, 2 Mar 2020 07:36:56 GMT", "version": "v3" } ]
2023-07-21
[ [ "Venkatesh", "Praveen", "" ], [ "Dutta", "Sanghamitra", "" ], [ "Grover", "Pulkit", "" ] ]
We develop a theoretical framework for defining and identifying flows of information in computational systems. Here, a computational system is assumed to be a directed graph, with "clocked" nodes that send transmissions to each other along the edges of the graph at discrete points in time. We are interested in a defini...
2308.03741
Muhammad Bilal Shaikh
Muhammad Bilal Shaikh, Douglas Chai, Syed Mohammed Shamsul Islam and Naveed Akhtar
MAiVAR-T: Multimodal Audio-image and Video Action Recognizer using Transformers
6 pages, 7 figures, 4 tables, Peer reviewed, Accepted @ The 11th European Workshop on Visual Information Processing (EUVIP) will be held on 11th-14th September 2023, in Gj{\o}vik, Norway. arXiv admin note: text overlap with arXiv:2103.15691 by other authors
null
null
null
cs.CV cs.AI cs.LG cs.MM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In line with the human capacity to perceive the world by simultaneously processing and integrating high-dimensional inputs from multiple modalities like vision and audio, we propose a novel model, MAiVAR-T (Multimodal Audio-Image to Video Action Recognition Transformer). This model employs an intuitive approach for t...
[ { "created": "Tue, 1 Aug 2023 11:00:25 GMT", "version": "v1" } ]
2023-08-08
[ [ "Shaikh", "Muhammad Bilal", "" ], [ "Chai", "Douglas", "" ], [ "Islam", "Syed Mohammed Shamsul", "" ], [ "Akhtar", "Naveed", "" ] ]
In line with the human capacity to perceive the world by simultaneously processing and integrating high-dimensional inputs from multiple modalities like vision and audio, we propose a novel model, MAiVAR-T (Multimodal Audio-Image to Video Action Recognition Transformer). This model employs an intuitive approach for the...
0710.4649
EDA Publishing Association
Praveen Ghanta, Sarma Vrudhula, Rajendran Panda, Janet Wang
Stochastic Power Grid Analysis Considering Process Variations
Submitted on behalf of EDAA (http://www.edaa.com/)
Dans Design, Automation and Test in Europe - DATE'05, Munich : Allemagne (2005)
null
null
cs.AR
null
In this paper, we investigate the impact of interconnect and device process variations on voltage fluctuations in power grids. We consider random variations in the power grid's electrical parameters as spatial stochastic processes and propose a new and efficient method to compute the stochastic voltage response of th...
[ { "created": "Thu, 25 Oct 2007 08:24:02 GMT", "version": "v1" } ]
2011-11-09
[ [ "Ghanta", "Praveen", "" ], [ "Vrudhula", "Sarma", "" ], [ "Panda", "Rajendran", "" ], [ "Wang", "Janet", "" ] ]
In this paper, we investigate the impact of interconnect and device process variations on voltage fluctuations in power grids. We consider random variations in the power grid's electrical parameters as spatial stochastic processes and propose a new and efficient method to compute the stochastic voltage response of the ...
1805.06213
Makoto Naruse
Hayato Saigo, Makoto Naruse, Kazuya Okamura, Hirokazu Hori, Izumi Ojima
Category theory as a foundation for soft robotics
null
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Soft robotics is an emerging field of research where the robot body is composed of compliant and soft materials. It allows the body to bend, twist, and deform to move or to adapt its shape to the environment for grasping, all of which are difficult for traditional hard robots with rigid bodies. However, the theoretic...
[ { "created": "Wed, 16 May 2018 09:54:02 GMT", "version": "v1" }, { "created": "Tue, 25 Sep 2018 13:26:41 GMT", "version": "v2" } ]
2018-09-26
[ [ "Saigo", "Hayato", "" ], [ "Naruse", "Makoto", "" ], [ "Okamura", "Kazuya", "" ], [ "Hori", "Hirokazu", "" ], [ "Ojima", "Izumi", "" ] ]
Soft robotics is an emerging field of research where the robot body is composed of compliant and soft materials. It allows the body to bend, twist, and deform to move or to adapt its shape to the environment for grasping, all of which are difficult for traditional hard robots with rigid bodies. However, the theoretical...
1912.10606
L\^e Th\`anh D\~ung (Tito) Nguy\^en
L\^e Th\`anh D\~ung Nguy\^en
Complexity of correctness for pomset logic proof nets
Fully subsumed by arXiv:2209.07825 (which contains a lot more material and has an additional coauthor)
null
null
null
cs.LO
http://creativecommons.org/licenses/by/4.0/
We show that it is coNP-complete to decide whether a given proof structure of pomset logic is a correct proof net, using the graph-theoretic used in a previous paper of ours (arXiv:1901.10247).
[ { "created": "Mon, 23 Dec 2019 03:41:32 GMT", "version": "v1" }, { "created": "Mon, 6 Jan 2020 17:58:41 GMT", "version": "v2" }, { "created": "Wed, 22 Jan 2020 16:48:35 GMT", "version": "v3" }, { "created": "Mon, 23 Jan 2023 00:13:20 GMT", "version": "v4" } ]
2023-01-24
[ [ "Nguyên", "Lê Thành Dũng", "" ] ]
We show that it is coNP-complete to decide whether a given proof structure of pomset logic is a correct proof net, using the graph-theoretic used in a previous paper of ours (arXiv:1901.10247).
2005.07727
David Bau iii
David Bau, Hendrik Strobelt, William Peebles, Jonas Wulff, Bolei Zhou, Jun-Yan Zhu, Antonio Torralba
Semantic Photo Manipulation with a Generative Image Prior
SIGGRAPH 2019
ACM Transactions on Graphics (TOG) 38.4 (2019)
10.1145/3306346.3323023
null
cs.CV cs.GR cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Despite the recent success of GANs in synthesizing images conditioned on inputs such as a user sketch, text, or semantic labels, manipulating the high-level attributes of an existing natural photograph with GANs is challenging for two reasons. First, it is hard for GANs to precisely reproduce an input image. Second, ...
[ { "created": "Fri, 15 May 2020 18:22:05 GMT", "version": "v1" }, { "created": "Sat, 12 Sep 2020 19:53:55 GMT", "version": "v2" } ]
2020-09-15
[ [ "Bau", "David", "" ], [ "Strobelt", "Hendrik", "" ], [ "Peebles", "William", "" ], [ "Wulff", "Jonas", "" ], [ "Zhou", "Bolei", "" ], [ "Zhu", "Jun-Yan", "" ], [ "Torralba", "Antonio", "" ] ]
Despite the recent success of GANs in synthesizing images conditioned on inputs such as a user sketch, text, or semantic labels, manipulating the high-level attributes of an existing natural photograph with GANs is challenging for two reasons. First, it is hard for GANs to precisely reproduce an input image. Second, af...
2404.17036
Yoonha Cha
Yoonha Cha, Victoria Jackson, Isabela Figueira, Stacy M. Branham, Andr\'e van der Hoek
Understanding the Career Mobility of Blind and Low Vision Software Professionals
12 pages, 1 table, conference paper, 2024 ACM / IEEE 17th International Conference on Cooperative and Human Aspects of Software Engineering
null
10.1145/3641822.3641872
null
cs.SE cs.HC
http://creativecommons.org/licenses/by/4.0/
Context: Scholars in the software engineering (SE) research community have investigated career advancement in the software industry. Research topics have included how individual and external factors can impact career mobility of software professionals, and how gender affects career advancement. However, the community...
[ { "created": "Thu, 25 Apr 2024 20:51:56 GMT", "version": "v1" } ]
2024-04-29
[ [ "Cha", "Yoonha", "" ], [ "Jackson", "Victoria", "" ], [ "Figueira", "Isabela", "" ], [ "Branham", "Stacy M.", "" ], [ "van der Hoek", "André", "" ] ]
Context: Scholars in the software engineering (SE) research community have investigated career advancement in the software industry. Research topics have included how individual and external factors can impact career mobility of software professionals, and how gender affects career advancement. However, the community h...
2005.14347
Pieter van Goor
Pieter van Goor, Robert Mahony, Tarek Hamel, Jochen Trumpf
An Observer Design for Visual Simultaneous Localisation and Mapping with Output Equivariance
11 pages, 3 figures, to be published as {van Goor, P., Mahony, R., Hamel, T., Trumpf, J. (2020). An Observer Design for Visual Simultaneous Localisation and Mapping with Output Equivariance. In Proceedings of 21st IFAC World Congress 2020.}
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Visual Simultaneous Localisation and Mapping (VSLAM) is a key enabling technology for small embedded robotic systems such as aerial vehicles. Recent advances in equivariant filter and observer design offer the potential of a new generation of highly robust algorithms with low memory and computation requirements for e...
[ { "created": "Fri, 29 May 2020 00:14:08 GMT", "version": "v1" } ]
2020-06-01
[ [ "van Goor", "Pieter", "" ], [ "Mahony", "Robert", "" ], [ "Hamel", "Tarek", "" ], [ "Trumpf", "Jochen", "" ] ]
Visual Simultaneous Localisation and Mapping (VSLAM) is a key enabling technology for small embedded robotic systems such as aerial vehicles. Recent advances in equivariant filter and observer design offer the potential of a new generation of highly robust algorithms with low memory and computation requirements for emb...
2406.13173
Hejie Cui
Hejie Cui, Lingjun Mao, Xin Liang, Jieyu Zhang, Hui Ren, Quanzheng Li, Xiang Li, Carl Yang
Biomedical Visual Instruction Tuning with Clinician Preference Alignment
null
null
null
null
cs.CV cs.AI cs.CL cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recent advancements in multimodal foundation models have showcased impressive capabilities in understanding and reasoning with visual and textual information. Adapting these foundation models trained for general usage to specialized domains like biomedicine requires large-scale domain-specific instruction datasets. W...
[ { "created": "Wed, 19 Jun 2024 03:07:33 GMT", "version": "v1" }, { "created": "Sun, 30 Jun 2024 01:22:09 GMT", "version": "v2" }, { "created": "Tue, 16 Jul 2024 05:56:05 GMT", "version": "v3" } ]
2024-07-17
[ [ "Cui", "Hejie", "" ], [ "Mao", "Lingjun", "" ], [ "Liang", "Xin", "" ], [ "Zhang", "Jieyu", "" ], [ "Ren", "Hui", "" ], [ "Li", "Quanzheng", "" ], [ "Li", "Xiang", "" ], [ "Yang", "Carl", ""...
Recent advancements in multimodal foundation models have showcased impressive capabilities in understanding and reasoning with visual and textual information. Adapting these foundation models trained for general usage to specialized domains like biomedicine requires large-scale domain-specific instruction datasets. Whi...
2212.09988
Ke Zhao
Ke Zhao, Haining Tan, Tsz Fung Yau
Multi-Reference Image Super-Resolution: A Posterior Fusion Approach
null
null
null
null
cs.CV eess.IV
http://creativecommons.org/licenses/by-nc-sa/4.0/
Reference-based Super-resolution (RefSR) approaches have recently been proposed to overcome the ill-posed problem of image super-resolution by providing additional information from a high-resolution image. Multi-reference super-resolution extends this approach by allowing more information to be incorporated. This pap...
[ { "created": "Tue, 20 Dec 2022 04:15:03 GMT", "version": "v1" } ]
2022-12-21
[ [ "Zhao", "Ke", "" ], [ "Tan", "Haining", "" ], [ "Yau", "Tsz Fung", "" ] ]
Reference-based Super-resolution (RefSR) approaches have recently been proposed to overcome the ill-posed problem of image super-resolution by providing additional information from a high-resolution image. Multi-reference super-resolution extends this approach by allowing more information to be incorporated. This paper...
2305.05317
Xia Wu
X. Wu, W. Lu, X. P. Qin, X. W. Cao
Minimal Linear Codes Constructed from hierarchical posets with two levels
arXiv admin note: text overlap with arXiv:1911.11632, arXiv:1911.07648
null
null
null
cs.IT math.IT
http://creativecommons.org/licenses/by/4.0/
J. Y. Hyun, et al. (Des. Codes Cryptogr., vol. 88, pp. 2475-2492, 2020) constructed some optimal and minimal binary linear codes generated by one or two order ideals in hierarchical posets of two levels. At the end of their paper, they left an open problem: it also should be interesting to investigate the cases of mo...
[ { "created": "Tue, 9 May 2023 10:12:17 GMT", "version": "v1" } ]
2023-05-10
[ [ "Wu", "X.", "" ], [ "Lu", "W.", "" ], [ "Qin", "X. P.", "" ], [ "Cao", "X. W.", "" ] ]
J. Y. Hyun, et al. (Des. Codes Cryptogr., vol. 88, pp. 2475-2492, 2020) constructed some optimal and minimal binary linear codes generated by one or two order ideals in hierarchical posets of two levels. At the end of their paper, they left an open problem: it also should be interesting to investigate the cases of more...
2207.04806
Melanie F. Pradier
Ryutaro Tanno, Melanie F. Pradier, Aditya Nori, Yingzhen Li
Repairing Neural Networks by Leaving the Right Past Behind
24 pages, 12 figures
null
null
null
cs.LG
http://creativecommons.org/licenses/by/4.0/
Prediction failures of machine learning models often arise from deficiencies in training data, such as incorrect labels, outliers, and selection biases. However, such data points that are responsible for a given failure mode are generally not known a priori, let alone a mechanism for repairing the failure. This work ...
[ { "created": "Mon, 11 Jul 2022 12:07:39 GMT", "version": "v1" }, { "created": "Wed, 9 Nov 2022 21:04:59 GMT", "version": "v2" } ]
2022-11-11
[ [ "Tanno", "Ryutaro", "" ], [ "Pradier", "Melanie F.", "" ], [ "Nori", "Aditya", "" ], [ "Li", "Yingzhen", "" ] ]
Prediction failures of machine learning models often arise from deficiencies in training data, such as incorrect labels, outliers, and selection biases. However, such data points that are responsible for a given failure mode are generally not known a priori, let alone a mechanism for repairing the failure. This work dr...
2310.08221
Minseok Choi
Minseok Choi, Chaeheon Gwak, Seho Kim, Si Hyeong Kim, Jaegul Choo
SimCKP: Simple Contrastive Learning of Keyphrase Representations
Accepted to Findings of EMNLP 2023
null
null
null
cs.CL cs.AI cs.LG
http://creativecommons.org/licenses/by/4.0/
Keyphrase generation (KG) aims to generate a set of summarizing words or phrases given a source document, while keyphrase extraction (KE) aims to identify them from the text. Because the search space is much smaller in KE, it is often combined with KG to predict keyphrases that may or may not exist in the correspondi...
[ { "created": "Thu, 12 Oct 2023 11:11:54 GMT", "version": "v1" } ]
2023-10-13
[ [ "Choi", "Minseok", "" ], [ "Gwak", "Chaeheon", "" ], [ "Kim", "Seho", "" ], [ "Kim", "Si Hyeong", "" ], [ "Choo", "Jaegul", "" ] ]
Keyphrase generation (KG) aims to generate a set of summarizing words or phrases given a source document, while keyphrase extraction (KE) aims to identify them from the text. Because the search space is much smaller in KE, it is often combined with KG to predict keyphrases that may or may not exist in the corresponding...
2108.13051
Edoardo Ramalli
Edoardo Ramalli, Alberto Parravicini, Guido Walter Di Donato, Mirko Salaris, C\'eline Hudelot, Marco Domenico Santambrogio
Demystifying Drug Repurposing Domain Comprehension with Knowledge Graph Embedding
5 pages, IEEE BioCAS 2021
null
null
null
cs.LG cs.AI
http://creativecommons.org/licenses/by-nc-sa/4.0/
Drug repurposing is more relevant than ever due to drug development's rising costs and the need to respond to emerging diseases quickly. Knowledge graph embedding enables drug repurposing using heterogeneous data sources combined with state-of-the-art machine learning models to predict new drug-disease links in the k...
[ { "created": "Mon, 30 Aug 2021 08:16:02 GMT", "version": "v1" } ]
2021-08-31
[ [ "Ramalli", "Edoardo", "" ], [ "Parravicini", "Alberto", "" ], [ "Di Donato", "Guido Walter", "" ], [ "Salaris", "Mirko", "" ], [ "Hudelot", "Céline", "" ], [ "Santambrogio", "Marco Domenico", "" ] ]
Drug repurposing is more relevant than ever due to drug development's rising costs and the need to respond to emerging diseases quickly. Knowledge graph embedding enables drug repurposing using heterogeneous data sources combined with state-of-the-art machine learning models to predict new drug-disease links in the kno...
2303.00289
Xiameng Qin
Yuechen Yu, Yulin Li, Chengquan Zhang, Xiaoqiang Zhang, Zengyuan Guo, Xiameng Qin, Kun Yao, Junyu Han, Errui Ding, Jingdong Wang
StrucTexTv2: Masked Visual-Textual Prediction for Document Image Pre-training
ICLR 2023
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we present StrucTexTv2, an effective document image pre-training framework, by performing masked visual-textual prediction. It consists of two self-supervised pre-training tasks: masked image modeling and masked language modeling, based on text region-level image masking. The proposed method randomly m...
[ { "created": "Wed, 1 Mar 2023 07:32:51 GMT", "version": "v1" } ]
2023-03-02
[ [ "Yu", "Yuechen", "" ], [ "Li", "Yulin", "" ], [ "Zhang", "Chengquan", "" ], [ "Zhang", "Xiaoqiang", "" ], [ "Guo", "Zengyuan", "" ], [ "Qin", "Xiameng", "" ], [ "Yao", "Kun", "" ], [ "Han", "Jun...
In this paper, we present StrucTexTv2, an effective document image pre-training framework, by performing masked visual-textual prediction. It consists of two self-supervised pre-training tasks: masked image modeling and masked language modeling, based on text region-level image masking. The proposed method randomly mas...
2006.05082
Xinshi Chen
Xinshi Chen, Hanjun Dai, Yu Li, Xin Gao, Le Song
Learning to Stop While Learning to Predict
Proceedings of the 37th International Conference on Machine Learning
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
There is a recent surge of interest in designing deep architectures based on the update steps in traditional algorithms, or learning neural networks to improve and replace traditional algorithms. While traditional algorithms have certain stopping criteria for outputting results at different iterations, many algorithm...
[ { "created": "Tue, 9 Jun 2020 07:22:01 GMT", "version": "v1" } ]
2020-06-11
[ [ "Chen", "Xinshi", "" ], [ "Dai", "Hanjun", "" ], [ "Li", "Yu", "" ], [ "Gao", "Xin", "" ], [ "Song", "Le", "" ] ]
There is a recent surge of interest in designing deep architectures based on the update steps in traditional algorithms, or learning neural networks to improve and replace traditional algorithms. While traditional algorithms have certain stopping criteria for outputting results at different iterations, many algorithm-i...
2003.01593
Benjamin Finley
Abhishek Kumar, Benjamin Finley, Tristan Braud, Sasu Tarkoma, Pan Hui
Marketplace for AI Models
null
null
null
null
cs.CY cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Artificial intelligence shows promise for solving many practical societal problems in areas such as healthcare and transportation. However, the current mechanisms for AI model diffusion such as Github code repositories, academic project webpages, and commercial AI marketplaces have some limitations; for example, a la...
[ { "created": "Tue, 3 Mar 2020 15:27:30 GMT", "version": "v1" } ]
2020-03-04
[ [ "Kumar", "Abhishek", "" ], [ "Finley", "Benjamin", "" ], [ "Braud", "Tristan", "" ], [ "Tarkoma", "Sasu", "" ], [ "Hui", "Pan", "" ] ]
Artificial intelligence shows promise for solving many practical societal problems in areas such as healthcare and transportation. However, the current mechanisms for AI model diffusion such as Github code repositories, academic project webpages, and commercial AI marketplaces have some limitations; for example, a lack...
2010.12268
Jianan Wang
Jianan Wang, Eren Sezener, David Budden, Marcus Hutter, Joel Veness
A Combinatorial Perspective on Transfer Learning
null
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Human intelligence is characterized not only by the capacity to learn complex skills, but the ability to rapidly adapt and acquire new skills within an ever-changing environment. In this work we study how the learning of modular solutions can allow for effective generalization to both unseen and potentially different...
[ { "created": "Fri, 23 Oct 2020 09:53:31 GMT", "version": "v1" } ]
2020-10-26
[ [ "Wang", "Jianan", "" ], [ "Sezener", "Eren", "" ], [ "Budden", "David", "" ], [ "Hutter", "Marcus", "" ], [ "Veness", "Joel", "" ] ]
Human intelligence is characterized not only by the capacity to learn complex skills, but the ability to rapidly adapt and acquire new skills within an ever-changing environment. In this work we study how the learning of modular solutions can allow for effective generalization to both unseen and potentially differently...
2311.17030
Aleksandar Makelov
Aleksandar Makelov, Georg Lange, Neel Nanda
Is This the Subspace You Are Looking for? An Interpretability Illusion for Subspace Activation Patching
NeurIPS 2023 Workshop on Attributing Model Behavior at Scale
null
null
null
cs.LG cs.AI cs.CL
http://creativecommons.org/licenses/by/4.0/
Mechanistic interpretability aims to understand model behaviors in terms of specific, interpretable features, often hypothesized to manifest as low-dimensional subspaces of activations. Specifically, recent studies have explored subspace interventions (such as activation patching) as a way to simultaneously manipulat...
[ { "created": "Tue, 28 Nov 2023 18:32:19 GMT", "version": "v1" }, { "created": "Wed, 6 Dec 2023 14:28:46 GMT", "version": "v2" } ]
2023-12-07
[ [ "Makelov", "Aleksandar", "" ], [ "Lange", "Georg", "" ], [ "Nanda", "Neel", "" ] ]
Mechanistic interpretability aims to understand model behaviors in terms of specific, interpretable features, often hypothesized to manifest as low-dimensional subspaces of activations. Specifically, recent studies have explored subspace interventions (such as activation patching) as a way to simultaneously manipulate ...
1712.07474
Johann Makowsky
J.A. Makowsky
Can one design a geometry engine? On the (un)decidability of affine Euclidean geometries
28 pages, revised version, May 25, 2018
null
null
null
cs.SC
http://creativecommons.org/publicdomain/zero/1.0/
We survey the status of decidabilty of the consequence relation in various axiomatizations of Euclidean geometry. We draw attention to a widely overlooked result by Martin Ziegler from 1980, which proves Tarski's conjecture on the undecidability of finitely axiomatizable theories of fields. We elaborate on how to use...
[ { "created": "Wed, 20 Dec 2017 13:29:12 GMT", "version": "v1" }, { "created": "Wed, 23 May 2018 10:51:54 GMT", "version": "v2" }, { "created": "Fri, 1 Jun 2018 07:57:08 GMT", "version": "v3" } ]
2018-06-04
[ [ "Makowsky", "J. A.", "" ] ]
We survey the status of decidabilty of the consequence relation in various axiomatizations of Euclidean geometry. We draw attention to a widely overlooked result by Martin Ziegler from 1980, which proves Tarski's conjecture on the undecidability of finitely axiomatizable theories of fields. We elaborate on how to use Z...
2006.07159
Lucas Beyer
Lucas Beyer and Olivier J. H\'enaff and Alexander Kolesnikov and Xiaohua Zhai and A\"aron van den Oord
Are we done with ImageNet?
All five authors contributed equally. New labels at https://github.com/google-research/reassessed-imagenet
null
null
null
cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Yes, and no. We ask whether recent progress on the ImageNet classification benchmark continues to represent meaningful generalization, or whether the community has started to overfit to the idiosyncrasies of its labeling procedure. We therefore develop a significantly more robust procedure for collecting human annota...
[ { "created": "Fri, 12 Jun 2020 13:17:25 GMT", "version": "v1" } ]
2020-06-15
[ [ "Beyer", "Lucas", "" ], [ "Hénaff", "Olivier J.", "" ], [ "Kolesnikov", "Alexander", "" ], [ "Zhai", "Xiaohua", "" ], [ "Oord", "Aäron van den", "" ] ]
Yes, and no. We ask whether recent progress on the ImageNet classification benchmark continues to represent meaningful generalization, or whether the community has started to overfit to the idiosyncrasies of its labeling procedure. We therefore develop a significantly more robust procedure for collecting human annotati...
2306.09805
Joao A. Candido Ramos
Jo\~ao A. C\^andido Ramos, Lionel Blond\'e, Naoya Takeishi and Alexandros Kalousis
Mimicking Better by Matching the Approximate Action Distribution
null
null
null
null
cs.LG
http://creativecommons.org/licenses/by/4.0/
In this paper, we introduce MAAD, a novel, sample-efficient on-policy algorithm for Imitation Learning from Observations. MAAD utilizes a surrogate reward signal, which can be derived from various sources such as adversarial games, trajectory matching objectives, or optimal transport criteria. To compensate for the n...
[ { "created": "Fri, 16 Jun 2023 12:43:47 GMT", "version": "v1" }, { "created": "Fri, 9 Feb 2024 16:04:42 GMT", "version": "v2" } ]
2024-02-12
[ [ "Ramos", "João A. Cândido", "" ], [ "Blondé", "Lionel", "" ], [ "Takeishi", "Naoya", "" ], [ "Kalousis", "Alexandros", "" ] ]
In this paper, we introduce MAAD, a novel, sample-efficient on-policy algorithm for Imitation Learning from Observations. MAAD utilizes a surrogate reward signal, which can be derived from various sources such as adversarial games, trajectory matching objectives, or optimal transport criteria. To compensate for the non...
2012.00135
Yingtai Xiao
Yingtai Xiao, Zeyu Ding, Yuxin Wang, Danfeng Zhang, Daniel Kifer
Optimizing Fitness-For-Use of Differentially Private Linear Queries
null
null
null
null
cs.DB
http://creativecommons.org/licenses/by/4.0/
In practice, differentially private data releases are designed to support a variety of applications. A data release is fit for use if it meets target accuracy requirements for each application. In this paper, we consider the problem of answering linear queries under differential privacy subject to per-query accuracy ...
[ { "created": "Mon, 30 Nov 2020 22:10:21 GMT", "version": "v1" }, { "created": "Wed, 2 Dec 2020 01:14:08 GMT", "version": "v2" }, { "created": "Mon, 28 Dec 2020 16:22:22 GMT", "version": "v3" }, { "created": "Fri, 19 Mar 2021 02:26:31 GMT", "version": "v4" }, { "cr...
2021-06-15
[ [ "Xiao", "Yingtai", "" ], [ "Ding", "Zeyu", "" ], [ "Wang", "Yuxin", "" ], [ "Zhang", "Danfeng", "" ], [ "Kifer", "Daniel", "" ] ]
In practice, differentially private data releases are designed to support a variety of applications. A data release is fit for use if it meets target accuracy requirements for each application. In this paper, we consider the problem of answering linear queries under differential privacy subject to per-query accuracy co...
2112.06223
Holy Lovenia
Holy Lovenia, Samuel Cahyawijaya, Genta Indra Winata, Peng Xu, Xu Yan, Zihan Liu, Rita Frieske, Tiezheng Yu, Wenliang Dai, Elham J. Barezi, Qifeng Chen, Xiaojuan Ma, Bertram E. Shi, Pascale Fung
ASCEND: A Spontaneous Chinese-English Dataset for Code-switching in Multi-turn Conversation
null
Proceedings of the 13th Conference on Language Resources and Evaluation (LREC 2022)
null
null
cs.CL
http://creativecommons.org/licenses/by-sa/4.0/
Code-switching is a speech phenomenon occurring when a speaker switches language during a conversation. Despite the spontaneous nature of code-switching in conversational spoken language, most existing works collect code-switching data from read speech instead of spontaneous speech. ASCEND (A Spontaneous Chinese-Engl...
[ { "created": "Sun, 12 Dec 2021 12:59:20 GMT", "version": "v1" }, { "created": "Fri, 17 Dec 2021 17:11:30 GMT", "version": "v2" }, { "created": "Fri, 7 Jan 2022 14:46:18 GMT", "version": "v3" }, { "created": "Sun, 16 Jan 2022 08:27:45 GMT", "version": "v4" }, { "cr...
2022-09-07
[ [ "Lovenia", "Holy", "" ], [ "Cahyawijaya", "Samuel", "" ], [ "Winata", "Genta Indra", "" ], [ "Xu", "Peng", "" ], [ "Yan", "Xu", "" ], [ "Liu", "Zihan", "" ], [ "Frieske", "Rita", "" ], [ "Yu", "...
Code-switching is a speech phenomenon occurring when a speaker switches language during a conversation. Despite the spontaneous nature of code-switching in conversational spoken language, most existing works collect code-switching data from read speech instead of spontaneous speech. ASCEND (A Spontaneous Chinese-Englis...
2105.04181
Mengqi Xue
Mengqi Xue, Jie Song, Xinchao Wang, Ying Chen, Xingen Wang, Mingli Song
KDExplainer: A Task-oriented Attention Model for Explaining Knowledge Distillation
7 pages, 4 figures, accepted to IJCAI 2021
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Knowledge distillation (KD) has recently emerged as an efficacious scheme for learning compact deep neural networks (DNNs). Despite the promising results achieved, the rationale that interprets the behavior of KD has yet remained largely understudied. In this paper, we introduce a novel task-oriented attention model,...
[ { "created": "Mon, 10 May 2021 08:15:26 GMT", "version": "v1" }, { "created": "Wed, 12 May 2021 11:54:17 GMT", "version": "v2" } ]
2021-05-13
[ [ "Xue", "Mengqi", "" ], [ "Song", "Jie", "" ], [ "Wang", "Xinchao", "" ], [ "Chen", "Ying", "" ], [ "Wang", "Xingen", "" ], [ "Song", "Mingli", "" ] ]
Knowledge distillation (KD) has recently emerged as an efficacious scheme for learning compact deep neural networks (DNNs). Despite the promising results achieved, the rationale that interprets the behavior of KD has yet remained largely understudied. In this paper, we introduce a novel task-oriented attention model, t...
2306.05123
Fouad Oubari
Fouad Oubari, Raphael Meunier, Rodrigue D\'ecatoire, Mathilde Mougeot
A Meta-Generation framework for Industrial System Generation
null
null
null
null
cs.LG
http://creativecommons.org/licenses/by-nc-nd/4.0/
Generative design is an increasingly important tool in the industrial world. It allows the designers and engineers to easily explore vast ranges of design options, providing a cheaper and faster alternative to the trial and failure approaches. Thanks to the flexibility they offer, Deep Generative Models are gaining p...
[ { "created": "Thu, 8 Jun 2023 11:47:02 GMT", "version": "v1" } ]
2023-06-09
[ [ "Oubari", "Fouad", "" ], [ "Meunier", "Raphael", "" ], [ "Décatoire", "Rodrigue", "" ], [ "Mougeot", "Mathilde", "" ] ]
Generative design is an increasingly important tool in the industrial world. It allows the designers and engineers to easily explore vast ranges of design options, providing a cheaper and faster alternative to the trial and failure approaches. Thanks to the flexibility they offer, Deep Generative Models are gaining pop...
0908.2256
Viswanath Nagarajan
Nikhil Bansal, Nitish Korula, Viswanath Nagarajan and Aravind Srinivasan
On k-Column Sparse Packing Programs
19 pages, v3: additional details
null
10.1007/978-3-642-13036-6_28
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We consider the class of packing integer programs (PIPs) that are column sparse, i.e. there is a specified upper bound k on the number of constraints that each variable appears in. We give an (ek+o(k))-approximation algorithm for k-column sparse PIPs, improving on recent results of $k^2\cdot 2^k$ and $O(k^2)$. We als...
[ { "created": "Sun, 16 Aug 2009 17:55:03 GMT", "version": "v1" }, { "created": "Wed, 30 Sep 2009 02:27:09 GMT", "version": "v2" }, { "created": "Sun, 14 Mar 2010 15:29:51 GMT", "version": "v3" } ]
2015-05-13
[ [ "Bansal", "Nikhil", "" ], [ "Korula", "Nitish", "" ], [ "Nagarajan", "Viswanath", "" ], [ "Srinivasan", "Aravind", "" ] ]
We consider the class of packing integer programs (PIPs) that are column sparse, i.e. there is a specified upper bound k on the number of constraints that each variable appears in. We give an (ek+o(k))-approximation algorithm for k-column sparse PIPs, improving on recent results of $k^2\cdot 2^k$ and $O(k^2)$. We also ...
2307.00856
Xinhang Li
Xinhang Li, Xiangyu Zhao, Yejing Wang, Yu Liu, Yong Li, Cheng Long, Yong Zhang, Chunxiao Xing
OpenSiteRec: An Open Dataset for Site Recommendation
null
null
null
null
cs.IR cs.AI
http://creativecommons.org/licenses/by/4.0/
As a representative information retrieval task, site recommendation, which aims at predicting the optimal sites for a brand or an institution to open new branches in an automatic data-driven way, is beneficial and crucial for brand development in modern business. However, there is no publicly available dataset so far...
[ { "created": "Mon, 3 Jul 2023 08:54:32 GMT", "version": "v1" } ]
2023-07-04
[ [ "Li", "Xinhang", "" ], [ "Zhao", "Xiangyu", "" ], [ "Wang", "Yejing", "" ], [ "Liu", "Yu", "" ], [ "Li", "Yong", "" ], [ "Long", "Cheng", "" ], [ "Zhang", "Yong", "" ], [ "Xing", "Chunxiao", ...
As a representative information retrieval task, site recommendation, which aims at predicting the optimal sites for a brand or an institution to open new branches in an automatic data-driven way, is beneficial and crucial for brand development in modern business. However, there is no publicly available dataset so far a...
2310.01235
Patrick Pfreundschuh
Patrick Pfreundschuh, Helen Oleynikova, Cesar Cadena, Roland Siegwart, Olov Andersson
COIN-LIO: Complementary Intensity-Augmented LiDAR Inertial Odometry
null
null
null
null
cs.RO
http://creativecommons.org/licenses/by/4.0/
We present COIN-LIO, a LiDAR Inertial Odometry pipeline that tightly couples information from LiDAR intensity with geometry-based point cloud registration. The focus of our work is to improve the robustness of LiDAR-inertial odometry in geometrically degenerate scenarios, like tunnels or flat fields. We project LiDAR...
[ { "created": "Mon, 2 Oct 2023 14:24:38 GMT", "version": "v1" }, { "created": "Wed, 8 Nov 2023 10:15:53 GMT", "version": "v2" }, { "created": "Thu, 25 Apr 2024 13:46:52 GMT", "version": "v3" }, { "created": "Thu, 30 May 2024 16:50:54 GMT", "version": "v4" } ]
2024-05-31
[ [ "Pfreundschuh", "Patrick", "" ], [ "Oleynikova", "Helen", "" ], [ "Cadena", "Cesar", "" ], [ "Siegwart", "Roland", "" ], [ "Andersson", "Olov", "" ] ]
We present COIN-LIO, a LiDAR Inertial Odometry pipeline that tightly couples information from LiDAR intensity with geometry-based point cloud registration. The focus of our work is to improve the robustness of LiDAR-inertial odometry in geometrically degenerate scenarios, like tunnels or flat fields. We project LiDAR i...
2006.12708
Mingyuan Mao
Mingyuan Mao, Yuxin Tian, Baochang Zhang, Qixiang Ye, Wanquan Liu, Guodong Guo, David Doermann
iffDetector: Inference-aware Feature Filtering for Object Detection
14 pages, 6 figures
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Modern CNN-based object detectors focus on feature configuration during training but often ignore feature optimization during inference. In this paper, we propose a new feature optimization approach to enhance features and suppress background noise in both the training and inference stages. We introduce a generic Inf...
[ { "created": "Tue, 23 Jun 2020 02:57:29 GMT", "version": "v1" } ]
2020-06-24
[ [ "Mao", "Mingyuan", "" ], [ "Tian", "Yuxin", "" ], [ "Zhang", "Baochang", "" ], [ "Ye", "Qixiang", "" ], [ "Liu", "Wanquan", "" ], [ "Guo", "Guodong", "" ], [ "Doermann", "David", "" ] ]
Modern CNN-based object detectors focus on feature configuration during training but often ignore feature optimization during inference. In this paper, we propose a new feature optimization approach to enhance features and suppress background noise in both the training and inference stages. We introduce a generic Infer...
2203.04050
Erkang Cheng
Lang Peng, Zhirong Chen, Zhangjie Fu, Pengpeng Liang, Erkang Cheng
BEVSegFormer: Bird's Eye View Semantic Segmentation From Arbitrary Camera Rigs
Accepted at the IEEE Winter Conference on Applications of Computer Vision, WACV 2023
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Semantic segmentation in bird's eye view (BEV) is an important task for autonomous driving. Though this task has attracted a large amount of research efforts, it is still challenging to flexibly cope with arbitrary (single or multiple) camera sensors equipped on the autonomous vehicle. In this paper, we present BEVSe...
[ { "created": "Tue, 8 Mar 2022 12:39:51 GMT", "version": "v1" }, { "created": "Sun, 13 Mar 2022 04:29:34 GMT", "version": "v2" }, { "created": "Wed, 17 Aug 2022 03:28:41 GMT", "version": "v3" } ]
2022-08-19
[ [ "Peng", "Lang", "" ], [ "Chen", "Zhirong", "" ], [ "Fu", "Zhangjie", "" ], [ "Liang", "Pengpeng", "" ], [ "Cheng", "Erkang", "" ] ]
Semantic segmentation in bird's eye view (BEV) is an important task for autonomous driving. Though this task has attracted a large amount of research efforts, it is still challenging to flexibly cope with arbitrary (single or multiple) camera sensors equipped on the autonomous vehicle. In this paper, we present BEVSegF...
1811.06042
Christian Samuel Perone
Christian S. Perone, Pedro Ballester, Rodrigo C. Barros, Julien Cohen-Adad
Unsupervised domain adaptation for medical imaging segmentation with self-ensembling
15 pages, 9 figures
null
null
null
cs.CV
http://creativecommons.org/licenses/by-nc-sa/4.0/
Recent advances in deep learning methods have come to define the state-of-the-art for many medical imaging applications, surpassing even human judgment in several tasks. Those models, however, when trained to reduce the empirical risk on a single domain, fail to generalize when applied to other domains, a very common...
[ { "created": "Wed, 14 Nov 2018 20:18:13 GMT", "version": "v1" }, { "created": "Thu, 10 Jan 2019 22:38:53 GMT", "version": "v2" } ]
2019-01-14
[ [ "Perone", "Christian S.", "" ], [ "Ballester", "Pedro", "" ], [ "Barros", "Rodrigo C.", "" ], [ "Cohen-Adad", "Julien", "" ] ]
Recent advances in deep learning methods have come to define the state-of-the-art for many medical imaging applications, surpassing even human judgment in several tasks. Those models, however, when trained to reduce the empirical risk on a single domain, fail to generalize when applied to other domains, a very common s...
1811.10493
Bingzhang Hu
BingZhang Hu, Yu Guan, Yan Gao, Yang Long, Nicholas Lane and Thomas Ploetz
Robust Cross-View Gait Recognition with Evidence: A Discriminant Gait GAN (DiGGAN) Approach
Submitted to ACM Transactions on Intelligent Systems and Technology
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Gait as a biometric trait has attracted much attention in many security and privacy applications such as identity recognition and authentication, during the last few decades. Because of its nature as a long-distance biometric trait, gait can be easily collected and used to identify individuals non-intrusively through...
[ { "created": "Mon, 26 Nov 2018 16:37:29 GMT", "version": "v1" }, { "created": "Wed, 16 Sep 2020 16:10:26 GMT", "version": "v2" }, { "created": "Thu, 17 Sep 2020 10:17:12 GMT", "version": "v3" } ]
2020-09-18
[ [ "Hu", "BingZhang", "" ], [ "Guan", "Yu", "" ], [ "Gao", "Yan", "" ], [ "Long", "Yang", "" ], [ "Lane", "Nicholas", "" ], [ "Ploetz", "Thomas", "" ] ]
Gait as a biometric trait has attracted much attention in many security and privacy applications such as identity recognition and authentication, during the last few decades. Because of its nature as a long-distance biometric trait, gait can be easily collected and used to identify individuals non-intrusively through C...
1311.3387
Chen He Mr.
Chen He, Xun Chen and Z. Jane Wang
Performance of General STCs over Spatially Correlated MIMO Single-keyhole Channels
null
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
For MIMO Rayleigh channels, it has been shown that transmitter correlations always degrade the performance of general space-time codes (STCs) in high SNR regimes. In this correspondence, however, we show that when MIMO channels experience single-keyhole conditions, the effect of spatial correlations between transmiss...
[ { "created": "Thu, 14 Nov 2013 05:39:37 GMT", "version": "v1" }, { "created": "Sat, 23 Nov 2013 03:37:49 GMT", "version": "v2" }, { "created": "Mon, 13 Jan 2014 19:09:29 GMT", "version": "v3" } ]
2014-01-14
[ [ "He", "Chen", "" ], [ "Chen", "Xun", "" ], [ "Wang", "Z. Jane", "" ] ]
For MIMO Rayleigh channels, it has been shown that transmitter correlations always degrade the performance of general space-time codes (STCs) in high SNR regimes. In this correspondence, however, we show that when MIMO channels experience single-keyhole conditions, the effect of spatial correlations between transmissio...
2401.11929
Jinliang Deng
Jinliang Deng, Feiyang Ye, Du Yin, Xuan Song, Ivor W. Tsang, Hui Xiong
Parsimony or Capability? Decomposition Delivers Both in Long-term Time Series Forecasting
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Long-term time series forecasting (LTSF) represents a critical frontier in time series analysis, characterized by extensive input sequences, as opposed to the shorter spans typical of traditional approaches. While longer sequences inherently offer richer information for enhanced predictive precision, prevailing studi...
[ { "created": "Mon, 22 Jan 2024 13:15:40 GMT", "version": "v1" }, { "created": "Sat, 3 Feb 2024 02:24:06 GMT", "version": "v2" }, { "created": "Fri, 24 May 2024 01:17:03 GMT", "version": "v3" } ]
2024-05-27
[ [ "Deng", "Jinliang", "" ], [ "Ye", "Feiyang", "" ], [ "Yin", "Du", "" ], [ "Song", "Xuan", "" ], [ "Tsang", "Ivor W.", "" ], [ "Xiong", "Hui", "" ] ]
Long-term time series forecasting (LTSF) represents a critical frontier in time series analysis, characterized by extensive input sequences, as opposed to the shorter spans typical of traditional approaches. While longer sequences inherently offer richer information for enhanced predictive precision, prevailing studies...
2303.04912
Tom Silver
Amber Li, Tom Silver
Embodied Active Learning of Relational State Abstractions for Bilevel Planning
Conference on Lifelong Learning Agents (CoLLAs) 2023
null
null
null
cs.RO cs.AI cs.LG
http://creativecommons.org/licenses/by/4.0/
State abstraction is an effective technique for planning in robotics environments with continuous states and actions, long task horizons, and sparse feedback. In object-oriented environments, predicates are a particularly useful form of state abstraction because of their compatibility with symbolic planners and their...
[ { "created": "Wed, 8 Mar 2023 22:04:31 GMT", "version": "v1" }, { "created": "Mon, 19 Jun 2023 14:50:16 GMT", "version": "v2" } ]
2023-06-21
[ [ "Li", "Amber", "" ], [ "Silver", "Tom", "" ] ]
State abstraction is an effective technique for planning in robotics environments with continuous states and actions, long task horizons, and sparse feedback. In object-oriented environments, predicates are a particularly useful form of state abstraction because of their compatibility with symbolic planners and their c...
2005.13457
Sergio Miguel Martin
Sergio M. Martin, Daniel W\"alchli, Georgios Arampatzis, Athena E. Economides, Petr Karnakov, Petros Koumoutsakos
Korali: Efficient and Scalable Software Framework for Bayesian Uncertainty Quantification and Stochastic Optimization
12 pages, 12 figures
null
10.1016/j.cma.2021.114264
null
cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present Korali, an open-source framework for large-scale Bayesian uncertainty quantification and stochastic optimization. The framework relies on non-intrusive sampling of complex multiphysics models and enables their exploitation for optimization and decision-making. In addition, its distributed sampling engine m...
[ { "created": "Wed, 27 May 2020 16:14:49 GMT", "version": "v1" }, { "created": "Thu, 11 Mar 2021 12:58:16 GMT", "version": "v2" } ]
2022-01-26
[ [ "Martin", "Sergio M.", "" ], [ "Wälchli", "Daniel", "" ], [ "Arampatzis", "Georgios", "" ], [ "Economides", "Athena E.", "" ], [ "Karnakov", "Petr", "" ], [ "Koumoutsakos", "Petros", "" ] ]
We present Korali, an open-source framework for large-scale Bayesian uncertainty quantification and stochastic optimization. The framework relies on non-intrusive sampling of complex multiphysics models and enables their exploitation for optimization and decision-making. In addition, its distributed sampling engine mak...
2211.03183
Nawid Keshtmand
Nawid Keshtmand, Raul Santos-Rodriguez, Jonathan Lawry
Understanding the properties and limitations of contrastive learning for Out-of-Distribution detection
null
null
null
null
cs.LG cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A recent popular approach to out-of-distribution (OOD) detection is based on a self-supervised learning technique referred to as contrastive learning. There are two main variants of contrastive learning, namely instance and class discrimination, targeting features that can discriminate between different instances for...
[ { "created": "Sun, 6 Nov 2022 17:33:29 GMT", "version": "v1" } ]
2022-11-08
[ [ "Keshtmand", "Nawid", "" ], [ "Santos-Rodriguez", "Raul", "" ], [ "Lawry", "Jonathan", "" ] ]
A recent popular approach to out-of-distribution (OOD) detection is based on a self-supervised learning technique referred to as contrastive learning. There are two main variants of contrastive learning, namely instance and class discrimination, targeting features that can discriminate between different instances for t...
2405.18523
Jiaze Wang
Jiaze Wang, Yi Wang, Ziyu Guo, Renrui Zhang, Donghao Zhou, Guangyong Chen, Anfeng Liu, Pheng-Ann Heng
TripletMix: Triplet Data Augmentation for 3D Understanding
null
null
null
null
cs.CV cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Data augmentation has proven to be a vital tool for enhancing the generalization capabilities of deep learning models, especially in the context of 3D vision where traditional datasets are often limited. Despite previous advancements, existing methods primarily cater to unimodal data scenarios, leaving a gap in the a...
[ { "created": "Tue, 28 May 2024 18:44:15 GMT", "version": "v1" } ]
2024-05-30
[ [ "Wang", "Jiaze", "" ], [ "Wang", "Yi", "" ], [ "Guo", "Ziyu", "" ], [ "Zhang", "Renrui", "" ], [ "Zhou", "Donghao", "" ], [ "Chen", "Guangyong", "" ], [ "Liu", "Anfeng", "" ], [ "Heng", "Pheng-A...
Data augmentation has proven to be a vital tool for enhancing the generalization capabilities of deep learning models, especially in the context of 3D vision where traditional datasets are often limited. Despite previous advancements, existing methods primarily cater to unimodal data scenarios, leaving a gap in the aug...
2109.05413
Yudong Luo
Ziyuan Ma, Yudong Luo, Jia Pan
Learning Selective Communication for Multi-Agent Path Finding
IEEE Robotics and Automation Letters (RA-L)
null
null
null
cs.RO cs.AI cs.MA
http://creativecommons.org/licenses/by/4.0/
Learning communication via deep reinforcement learning (RL) or imitation learning (IL) has recently been shown to be an effective way to solve Multi-Agent Path Finding (MAPF). However, existing communication based MAPF solvers focus on broadcast communication, where an agent broadcasts its message to all other or pre...
[ { "created": "Sun, 12 Sep 2021 03:07:20 GMT", "version": "v1" }, { "created": "Thu, 23 Dec 2021 18:50:22 GMT", "version": "v2" } ]
2021-12-24
[ [ "Ma", "Ziyuan", "" ], [ "Luo", "Yudong", "" ], [ "Pan", "Jia", "" ] ]
Learning communication via deep reinforcement learning (RL) or imitation learning (IL) has recently been shown to be an effective way to solve Multi-Agent Path Finding (MAPF). However, existing communication based MAPF solvers focus on broadcast communication, where an agent broadcasts its message to all other or prede...
2107.12342
Nandan Kumar Jha
Karthik Garimella, Nandan Kumar Jha and Brandon Reagen
Sisyphus: A Cautionary Tale of Using Low-Degree Polynomial Activations in Privacy-Preserving Deep Learning
Accepted to PPML (ACM CCS) 2021
null
null
null
cs.LG cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Privacy concerns in client-server machine learning have given rise to private inference (PI), where neural inference occurs directly on encrypted inputs. PI protects clients' personal data and the server's intellectual property. A common practice in PI is to use garbled circuits to compute nonlinear functions private...
[ { "created": "Mon, 26 Jul 2021 17:33:56 GMT", "version": "v1" }, { "created": "Tue, 2 Nov 2021 22:22:42 GMT", "version": "v2" } ]
2021-11-04
[ [ "Garimella", "Karthik", "" ], [ "Jha", "Nandan Kumar", "" ], [ "Reagen", "Brandon", "" ] ]
Privacy concerns in client-server machine learning have given rise to private inference (PI), where neural inference occurs directly on encrypted inputs. PI protects clients' personal data and the server's intellectual property. A common practice in PI is to use garbled circuits to compute nonlinear functions privately...
2407.07672
Zhaohui Liang
Zhaohui Liang, Xiaoyu Zhang, Kevin Ma, Zhao Liu, Xipei Ren, Kosa Goucher-Lambert, Can Liu
StoryDiffusion: How to Support UX Storyboarding With Generative-AI
null
null
null
null
cs.HC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Storyboarding is an established method for designing user experiences. Generative AI can support this process by helping designers quickly create visual narratives. However, existing tools only focus on accurate text-to-image generation. Currently, it is not clear how to effectively support the entire creative proces...
[ { "created": "Wed, 10 Jul 2024 13:59:37 GMT", "version": "v1" } ]
2024-07-11
[ [ "Liang", "Zhaohui", "" ], [ "Zhang", "Xiaoyu", "" ], [ "Ma", "Kevin", "" ], [ "Liu", "Zhao", "" ], [ "Ren", "Xipei", "" ], [ "Goucher-Lambert", "Kosa", "" ], [ "Liu", "Can", "" ] ]
Storyboarding is an established method for designing user experiences. Generative AI can support this process by helping designers quickly create visual narratives. However, existing tools only focus on accurate text-to-image generation. Currently, it is not clear how to effectively support the entire creative process ...
1808.01080
Anisse Ismaili
Anisse Ismaili
The Complexity of Sequential Routing Games
Submitted to WINE2018 on July 28th, 2018. Rejected (reviews included here). No major flaws are known. Additional (positive) results would be welcome
null
null
null
cs.GT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We study routing games where every agent sequentially decides her next edge when she obtains the green light at each vertex. Because every edge only has capacity to let out one agent per round, an edge acts as a FIFO waiting queue that causes congestion on agents who enter. Given $n$ agents over $|V|$ vertices, we sh...
[ { "created": "Fri, 3 Aug 2018 03:52:42 GMT", "version": "v1" }, { "created": "Fri, 26 Oct 2018 05:30:59 GMT", "version": "v2" } ]
2018-10-29
[ [ "Ismaili", "Anisse", "" ] ]
We study routing games where every agent sequentially decides her next edge when she obtains the green light at each vertex. Because every edge only has capacity to let out one agent per round, an edge acts as a FIFO waiting queue that causes congestion on agents who enter. Given $n$ agents over $|V|$ vertices, we show...
1410.4977
Amit Sheth
Pratikkumar Desai, Amit Sheth and Pramod Anantharam
Semantic Gateway as a Service architecture for IoT Interoperability
16 pages
null
null
null
cs.NI cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The Internet of Things (IoT) is set to occupy a substantial component of future Internet. The IoT connects sensors and devices that record physical observations to applications and services of the Internet. As a successor to technologies such as RFID and Wireless Sensor Networks (WSN), the IoT has stumbled into verti...
[ { "created": "Sat, 18 Oct 2014 16:23:51 GMT", "version": "v1" } ]
2014-10-21
[ [ "Desai", "Pratikkumar", "" ], [ "Sheth", "Amit", "" ], [ "Anantharam", "Pramod", "" ] ]
The Internet of Things (IoT) is set to occupy a substantial component of future Internet. The IoT connects sensors and devices that record physical observations to applications and services of the Internet. As a successor to technologies such as RFID and Wireless Sensor Networks (WSN), the IoT has stumbled into vertica...
2102.05334
Yael Mathov
Yael Mathov, Lior Rokach, Yuval Elovici
Enhancing Real-World Adversarial Patches through 3D Modeling of Complex Target Scenes
null
null
null
null
cs.CV cs.AI cs.CR cs.LG
http://creativecommons.org/licenses/by-nc-sa/4.0/
Adversarial examples have proven to be a concerning threat to deep learning models, particularly in the image domain. However, while many studies have examined adversarial examples in the real world, most of them relied on 2D photos of the attack scene. As a result, the attacks proposed may have limited effectiveness...
[ { "created": "Wed, 10 Feb 2021 09:16:09 GMT", "version": "v1" }, { "created": "Thu, 2 Sep 2021 07:50:28 GMT", "version": "v2" } ]
2021-09-03
[ [ "Mathov", "Yael", "" ], [ "Rokach", "Lior", "" ], [ "Elovici", "Yuval", "" ] ]
Adversarial examples have proven to be a concerning threat to deep learning models, particularly in the image domain. However, while many studies have examined adversarial examples in the real world, most of them relied on 2D photos of the attack scene. As a result, the attacks proposed may have limited effectiveness w...
1703.07655
Priyadarshini Panda
Priyadarshini Panda, Jason M. Allred, Shriram Ramanathan and Kaushik Roy
ASP: Learning to Forget with Adaptive Synaptic Plasticity in Spiking Neural Networks
14 pages, 14 figures
IEEE Journal on Emerging and Selected Topics in Circuits and Systems (Volume: 8, Issue: 1, March 2018)
10.1109/JETCAS.2017.2769684
null
cs.NE cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A fundamental feature of learning in animals is the "ability to forget" that allows an organism to perceive, model and make decisions from disparate streams of information and adapt to changing environments. Against this backdrop, we present a novel unsupervised learning mechanism ASP (Adaptive Synaptic Plasticity) f...
[ { "created": "Wed, 22 Mar 2017 13:48:47 GMT", "version": "v1" }, { "created": "Fri, 8 Jun 2018 20:17:33 GMT", "version": "v2" } ]
2018-06-12
[ [ "Panda", "Priyadarshini", "" ], [ "Allred", "Jason M.", "" ], [ "Ramanathan", "Shriram", "" ], [ "Roy", "Kaushik", "" ] ]
A fundamental feature of learning in animals is the "ability to forget" that allows an organism to perceive, model and make decisions from disparate streams of information and adapt to changing environments. Against this backdrop, we present a novel unsupervised learning mechanism ASP (Adaptive Synaptic Plasticity) for...
1310.5656
Dimiter Skordev
Dimiter Skordev (Sofia University, Faculty of Mathematics and Informatics, Sofia, Bulgaria)
Approximation systems for functions in topological and in metric spaces
21 pages, published in Logical Methods in Computer Science
Logical Methods in Computer Science, Volume 9, Issue 4 (November 20, 2013) lmcs:890
10.2168/LMCS-9(4:15)2013
null
cs.LO math.LO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A notable feature of the TTE approach to computability is the representation of the argument values and the corresponding function values by means of infinitistic names. Two ways to eliminate the using of such names in certain cases are indicated in the paper. The first one is intended for the case of topological spa...
[ { "created": "Mon, 21 Oct 2013 17:42:33 GMT", "version": "v1" }, { "created": "Tue, 19 Nov 2013 09:20:16 GMT", "version": "v2" }, { "created": "Thu, 21 Nov 2013 09:24:54 GMT", "version": "v3" } ]
2015-07-01
[ [ "Skordev", "Dimiter", "", "Sofia University, Faculty of Mathematics and\n Informatics, Sofia, Bulgaria" ] ]
A notable feature of the TTE approach to computability is the representation of the argument values and the corresponding function values by means of infinitistic names. Two ways to eliminate the using of such names in certain cases are indicated in the paper. The first one is intended for the case of topological space...
2405.01054
Andriy Sarabakha
Zhongzheng Qiao, Xuan Huy Pham, Savitha Ramasamy, Xudong Jiang, Erdal Kayacan, Andriy Sarabakha
Continual Learning for Robust Gate Detection under Dynamic Lighting in Autonomous Drone Racing
8 pages, 6 figures, in 2024 International Joint Conference on Neural Networks (IJCNN)
null
null
null
cs.RO cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In autonomous and mobile robotics, a principal challenge is resilient real-time environmental perception, particularly in situations characterized by unknown and dynamic elements, as exemplified in the context of autonomous drone racing. This study introduces a perception technique for detecting drone racing gates un...
[ { "created": "Thu, 2 May 2024 07:21:12 GMT", "version": "v1" } ]
2024-05-03
[ [ "Qiao", "Zhongzheng", "" ], [ "Pham", "Xuan Huy", "" ], [ "Ramasamy", "Savitha", "" ], [ "Jiang", "Xudong", "" ], [ "Kayacan", "Erdal", "" ], [ "Sarabakha", "Andriy", "" ] ]
In autonomous and mobile robotics, a principal challenge is resilient real-time environmental perception, particularly in situations characterized by unknown and dynamic elements, as exemplified in the context of autonomous drone racing. This study introduces a perception technique for detecting drone racing gates unde...
1512.06009
Reuben Farrugia
Reuben Farrugia, Christine Guillemot
Face Hallucination using Linear Models of Coupled Sparse Support
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Most face super-resolution methods assume that low-resolution and high-resolution manifolds have similar local geometrical structure, hence learn local models on the lowresolution manifolds (e.g. sparse or locally linear embedding models), which are then applied on the high-resolution manifold. However, the low-resol...
[ { "created": "Fri, 18 Dec 2015 16:01:55 GMT", "version": "v1" } ]
2015-12-21
[ [ "Farrugia", "Reuben", "" ], [ "Guillemot", "Christine", "" ] ]
Most face super-resolution methods assume that low-resolution and high-resolution manifolds have similar local geometrical structure, hence learn local models on the lowresolution manifolds (e.g. sparse or locally linear embedding models), which are then applied on the high-resolution manifold. However, the low-resolut...
2403.16030
Dongqi Fu
Dongqi Fu, Zhigang Hua, Yan Xie, Jin Fang, Si Zhang, Kaan Sancak, Hao Wu, Andrey Malevich, Jingrui He, Bo Long
VCR-Graphormer: A Mini-batch Graph Transformer via Virtual Connections
null
null
null
null
cs.LG
http://creativecommons.org/licenses/by-nc-nd/4.0/
Graph transformer has been proven as an effective graph learning method for its adoption of attention mechanism that is capable of capturing expressive representations from complex topological and feature information of graphs. Graph transformer conventionally performs dense attention (or global attention) for every ...
[ { "created": "Sun, 24 Mar 2024 06:10:56 GMT", "version": "v1" } ]
2024-03-26
[ [ "Fu", "Dongqi", "" ], [ "Hua", "Zhigang", "" ], [ "Xie", "Yan", "" ], [ "Fang", "Jin", "" ], [ "Zhang", "Si", "" ], [ "Sancak", "Kaan", "" ], [ "Wu", "Hao", "" ], [ "Malevich", "Andrey", "" ...
Graph transformer has been proven as an effective graph learning method for its adoption of attention mechanism that is capable of capturing expressive representations from complex topological and feature information of graphs. Graph transformer conventionally performs dense attention (or global attention) for every pa...
2404.19141
Tonglong Wei
Tonglong Wei, Youfang Lin, Yan Lin, Shengnan Guo, Lan Zhang, Huaiyu Wan
Micro-Macro Spatial-Temporal Graph-based Encoder-Decoder for Map-Constrained Trajectory Recovery
This paper has been accepted as a regular paper at IEEE TKDE
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recovering intermediate missing GPS points in a sparse trajectory, while adhering to the constraints of the road network, could offer deep insights into users' moving behaviors in intelligent transportation systems. Although recent studies have demonstrated the advantages of achieving map-constrained trajectory recov...
[ { "created": "Mon, 29 Apr 2024 22:54:35 GMT", "version": "v1" } ]
2024-05-01
[ [ "Wei", "Tonglong", "" ], [ "Lin", "Youfang", "" ], [ "Lin", "Yan", "" ], [ "Guo", "Shengnan", "" ], [ "Zhang", "Lan", "" ], [ "Wan", "Huaiyu", "" ] ]
Recovering intermediate missing GPS points in a sparse trajectory, while adhering to the constraints of the road network, could offer deep insights into users' moving behaviors in intelligent transportation systems. Although recent studies have demonstrated the advantages of achieving map-constrained trajectory recover...
2004.06081
Aboul Ella Hassanien Abo
Mohamed Torky and Aboul Ella Hassanien (Scientific Research Group in Egypt)
COVID-19 Blockchain Framework: Innovative Approach
22 pages, 11 Figures
null
null
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The world is currently witnessing dangerous shifts in the epidemic of emerging SARS-CoV-2, the causative agent of (COVID-19) coronavirus. The infection, and death numbers reported by World Health Organization (WHO) about this epidemic forecasts an increasing threats to the lives of people and the economics of countri...
[ { "created": "Sun, 5 Apr 2020 11:25:45 GMT", "version": "v1" } ]
2020-04-14
[ [ "Torky", "Mohamed", "", "Scientific Research Group in\n Egypt" ], [ "Hassanien", "Aboul Ella", "", "Scientific Research Group in\n Egypt" ] ]
The world is currently witnessing dangerous shifts in the epidemic of emerging SARS-CoV-2, the causative agent of (COVID-19) coronavirus. The infection, and death numbers reported by World Health Organization (WHO) about this epidemic forecasts an increasing threats to the lives of people and the economics of countries...
1705.07904
Chris Donahue
Chris Donahue, Zachary C. Lipton, Akshay Balsubramani, Julian McAuley
Semantically Decomposing the Latent Spaces of Generative Adversarial Networks
Published as a conference paper at ICLR 2018
null
null
null
cs.LG cs.AI cs.CV cs.NE stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We propose a new algorithm for training generative adversarial networks that jointly learns latent codes for both identities (e.g. individual humans) and observations (e.g. specific photographs). By fixing the identity portion of the latent codes, we can generate diverse images of the same subject, and by fixing the ...
[ { "created": "Mon, 22 May 2017 18:00:02 GMT", "version": "v1" }, { "created": "Tue, 31 Oct 2017 18:00:05 GMT", "version": "v2" }, { "created": "Thu, 22 Feb 2018 19:36:33 GMT", "version": "v3" } ]
2018-02-26
[ [ "Donahue", "Chris", "" ], [ "Lipton", "Zachary C.", "" ], [ "Balsubramani", "Akshay", "" ], [ "McAuley", "Julian", "" ] ]
We propose a new algorithm for training generative adversarial networks that jointly learns latent codes for both identities (e.g. individual humans) and observations (e.g. specific photographs). By fixing the identity portion of the latent codes, we can generate diverse images of the same subject, and by fixing the ob...
2212.11922
Evin P{\i}nar \"Ornek
Evin P{\i}nar \"Ornek, Aravindhan K Krishnan, Shreekant Gayaka, Cheng-Hao Kuo, Arnie Sen, Nassir Navab, Federico Tombari
SupeRGB-D: Zero-shot Instance Segmentation in Cluttered Indoor Environments
Accepted in Robotics and Automation Letters April 2023
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Object instance segmentation is a key challenge for indoor robots navigating cluttered environments with many small objects. Limitations in 3D sensing capabilities often make it difficult to detect every possible object. While deep learning approaches may be effective for this problem, manually annotating 3D data for...
[ { "created": "Thu, 22 Dec 2022 17:59:48 GMT", "version": "v1" }, { "created": "Thu, 25 May 2023 12:25:24 GMT", "version": "v2" } ]
2023-05-26
[ [ "Örnek", "Evin Pınar", "" ], [ "Krishnan", "Aravindhan K", "" ], [ "Gayaka", "Shreekant", "" ], [ "Kuo", "Cheng-Hao", "" ], [ "Sen", "Arnie", "" ], [ "Navab", "Nassir", "" ], [ "Tombari", "Federico", "" ]...
Object instance segmentation is a key challenge for indoor robots navigating cluttered environments with many small objects. Limitations in 3D sensing capabilities often make it difficult to detect every possible object. While deep learning approaches may be effective for this problem, manually annotating 3D data for s...
1505.07396
Marko Horvat
Marko Horvat, Davor Kukolja, Dragutin Ivanec
Retrieval of multimedia stimuli with semantic and emotional cues: Suggestions from a controlled study
4 pages, 3 figures, 1 table. In the Proceedings of 38th International Convention on Information and Communication Technology, Electronics and Microelectronics MIPRO 2015 (pp. 1399-1402)
null
null
null
cs.HC cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The ability to efficiently search pictures with annotated semantics and emotion is an important problem for Human-Computer Interaction with considerable interdisciplinary significance. Accuracy and speed of the multimedia retrieval process depends on the chosen metadata annotation model. The quality of such multiface...
[ { "created": "Wed, 27 May 2015 16:34:55 GMT", "version": "v1" }, { "created": "Fri, 30 Jun 2017 14:09:38 GMT", "version": "v2" } ]
2017-07-03
[ [ "Horvat", "Marko", "" ], [ "Kukolja", "Davor", "" ], [ "Ivanec", "Dragutin", "" ] ]
The ability to efficiently search pictures with annotated semantics and emotion is an important problem for Human-Computer Interaction with considerable interdisciplinary significance. Accuracy and speed of the multimedia retrieval process depends on the chosen metadata annotation model. The quality of such multifacete...
1908.02134
Hiroshi Kuwajima
Hiroshi Kuwajima and Fuyuki Ishikawa
Adapting SQuaRE for Quality Assessment of Artificial Intelligence Systems
null
null
null
null
cs.CY cs.LG cs.SE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
More and more software practitioners are tackling towards industrial applications of artificial intelligence (AI) systems, especially those based on machine learning (ML). However, many of existing principles and approaches to traditional systems do not work effectively for the system behavior obtained by training no...
[ { "created": "Wed, 31 Jul 2019 18:31:06 GMT", "version": "v1" } ]
2019-08-07
[ [ "Kuwajima", "Hiroshi", "" ], [ "Ishikawa", "Fuyuki", "" ] ]
More and more software practitioners are tackling towards industrial applications of artificial intelligence (AI) systems, especially those based on machine learning (ML). However, many of existing principles and approaches to traditional systems do not work effectively for the system behavior obtained by training not ...
2012.03709
Yilin Zhao
Yilin Zhao, Zhuosheng Zhang, Hai Zhao
Reference Knowledgeable Network for Machine Reading Comprehension
Accepted by TASLP 2022
null
null
null
cs.CL cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Multi-choice Machine Reading Comprehension (MRC) as a challenge requires models to select the most appropriate answer from a set of candidates with a given passage and question. Most of the existing researches focus on the modeling of specific tasks or complex networks, without explicitly referring to relevant and cr...
[ { "created": "Mon, 7 Dec 2020 14:11:33 GMT", "version": "v1" }, { "created": "Wed, 14 Jul 2021 12:49:41 GMT", "version": "v2" }, { "created": "Sat, 26 Mar 2022 15:27:28 GMT", "version": "v3" } ]
2022-03-29
[ [ "Zhao", "Yilin", "" ], [ "Zhang", "Zhuosheng", "" ], [ "Zhao", "Hai", "" ] ]
Multi-choice Machine Reading Comprehension (MRC) as a challenge requires models to select the most appropriate answer from a set of candidates with a given passage and question. Most of the existing researches focus on the modeling of specific tasks or complex networks, without explicitly referring to relevant and cred...
2012.08129
Yi-Hsin Chen
Cheng-Hsun Lei, Yi-Hsin Chen, Wen-Hsiao Peng, Wei-Chen Chiu
Class-incremental Learning with Rectified Feature-Graph Preservation
Accepted by ACCV 2020 (oral)
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
In this paper, we address the problem of distillation-based class-incremental learning with a single head. A central theme of this task is to learn new classes that arrive in sequential phases over time while keeping the model's capability of recognizing seen classes with only limited memory for preserving seen data ...
[ { "created": "Tue, 15 Dec 2020 07:26:04 GMT", "version": "v1" }, { "created": "Fri, 22 Jan 2021 09:06:04 GMT", "version": "v2" } ]
2021-01-25
[ [ "Lei", "Cheng-Hsun", "" ], [ "Chen", "Yi-Hsin", "" ], [ "Peng", "Wen-Hsiao", "" ], [ "Chiu", "Wei-Chen", "" ] ]
In this paper, we address the problem of distillation-based class-incremental learning with a single head. A central theme of this task is to learn new classes that arrive in sequential phases over time while keeping the model's capability of recognizing seen classes with only limited memory for preserving seen data sa...
1406.3269
Krzysztof Geras
Krzysztof J. Geras and Charles Sutton
Scheduled denoising autoencoders
Published as a conference paper at ICLR 2015
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present a representation learning method that learns features at multiple different levels of scale. Working within the unsupervised framework of denoising autoencoders, we observe that when the input is heavily corrupted during training, the network tends to learn coarse-grained features, whereas when the input i...
[ { "created": "Thu, 12 Jun 2014 15:40:18 GMT", "version": "v1" }, { "created": "Fri, 19 Dec 2014 20:42:11 GMT", "version": "v2" }, { "created": "Fri, 10 Apr 2015 21:05:32 GMT", "version": "v3" } ]
2015-04-14
[ [ "Geras", "Krzysztof J.", "" ], [ "Sutton", "Charles", "" ] ]
We present a representation learning method that learns features at multiple different levels of scale. Working within the unsupervised framework of denoising autoencoders, we observe that when the input is heavily corrupted during training, the network tends to learn coarse-grained features, whereas when the input is ...
2010.16340
Yuval Moskovitch
Yuval Moskovitch and H. V. Jagadish
Patterns Count-Based Labels for Datasets
ICDE2021
null
null
null
cs.DB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Counts of attribute-value combinations are central to the profiling of a dataset, particularly in determining fitness for use and in eliminating bias and unfairness. While counts of individual attribute values may be stored in some dataset profiles, there are too many combinations of attributes for it to be practical...
[ { "created": "Fri, 30 Oct 2020 16:00:34 GMT", "version": "v1" }, { "created": "Sat, 7 Nov 2020 15:10:11 GMT", "version": "v2" } ]
2020-11-10
[ [ "Moskovitch", "Yuval", "" ], [ "Jagadish", "H. V.", "" ] ]
Counts of attribute-value combinations are central to the profiling of a dataset, particularly in determining fitness for use and in eliminating bias and unfairness. While counts of individual attribute values may be stored in some dataset profiles, there are too many combinations of attributes for it to be practical t...
2403.05351
Hassan Keshvarikhojasteh
H. Keshvarikhojasteh, J.P.W. Pluim, M. Veta
Multiple Instance Learning with random sampling for Whole Slide Image Classification
SPIE Medical Imaging 2024
null
null
null
cs.CV
http://creativecommons.org/licenses/by-nc-nd/4.0/
In computational pathology, random sampling of patches during training of Multiple Instance Learning (MIL) methods is computationally efficient and serves as a regularization strategy. Despite its promising benefits, questions concerning performance trends for varying sample sizes and its influence on model interpret...
[ { "created": "Fri, 8 Mar 2024 14:31:40 GMT", "version": "v1" } ]
2024-03-11
[ [ "Keshvarikhojasteh", "H.", "" ], [ "Pluim", "J. P. W.", "" ], [ "Veta", "M.", "" ] ]
In computational pathology, random sampling of patches during training of Multiple Instance Learning (MIL) methods is computationally efficient and serves as a regularization strategy. Despite its promising benefits, questions concerning performance trends for varying sample sizes and its influence on model interpretab...
2207.05855
Ka Ho Brian Chor
Ka Ho Brian Chor, Kit T. Rodolfa, Rayid Ghani
A Conceptual Framework for Using Machine Learning to Support Child Welfare Decisions
69 pages, 1 table, 5 figures, 1 appendix
null
null
null
cs.CY cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Human services systems make key decisions that impact individuals in the society. The U.S. child welfare system makes such decisions, from screening-in hotline reports of suspected abuse or neglect for child protective investigations, placing children in foster care, to returning children to permanent home settings. ...
[ { "created": "Tue, 12 Jul 2022 21:42:22 GMT", "version": "v1" } ]
2022-07-14
[ [ "Chor", "Ka Ho Brian", "" ], [ "Rodolfa", "Kit T.", "" ], [ "Ghani", "Rayid", "" ] ]
Human services systems make key decisions that impact individuals in the society. The U.S. child welfare system makes such decisions, from screening-in hotline reports of suspected abuse or neglect for child protective investigations, placing children in foster care, to returning children to permanent home settings. Th...
1309.5507
Irfan Uddin
Irfan Uddin
Microgrid - The microthreaded many-core architecture
30 pages, 16 figures
null
null
null
cs.AR
http://creativecommons.org/licenses/by/3.0/
Traditional processors use the von Neumann execution model, some other processors in the past have used the dataflow execution model. A combination of von Neuman model and dataflow model is also tried in the past and the resultant model is referred as hybrid dataflow execution model. We describe a hybrid dataflow mod...
[ { "created": "Sat, 21 Sep 2013 17:50:09 GMT", "version": "v1" } ]
2013-09-24
[ [ "Uddin", "Irfan", "" ] ]
Traditional processors use the von Neumann execution model, some other processors in the past have used the dataflow execution model. A combination of von Neuman model and dataflow model is also tried in the past and the resultant model is referred as hybrid dataflow execution model. We describe a hybrid dataflow model...
2108.03122
Vishrant Tripathi
Vishrant Tripathi, Luca Ballotta, Luca Carlone, and Eytan Modiano
Computation and Communication Co-Design for Real-Time Monitoring and Control in Multi-Agent Systems
accepted at WiOpt 2021
null
10.23919/WiOpt52861.2021.9589966
null
cs.NI cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We investigate the problem of co-designing computation and communication in a multi-agent system (e.g. a sensor network or a multi-robot team). We consider the realistic setting where each agent acquires sensor data and is capable of local processing before sending updates to a base station, which is in charge of mak...
[ { "created": "Fri, 6 Aug 2021 13:45:30 GMT", "version": "v1" }, { "created": "Mon, 9 Aug 2021 02:11:37 GMT", "version": "v2" } ]
2022-04-08
[ [ "Tripathi", "Vishrant", "" ], [ "Ballotta", "Luca", "" ], [ "Carlone", "Luca", "" ], [ "Modiano", "Eytan", "" ] ]
We investigate the problem of co-designing computation and communication in a multi-agent system (e.g. a sensor network or a multi-robot team). We consider the realistic setting where each agent acquires sensor data and is capable of local processing before sending updates to a base station, which is in charge of makin...
1808.09463
Christina Niklaus
Matthias Cetto, Christina Niklaus, Andr\'e Freitas, Siegfried Handschuh
Graphene: A Context-Preserving Open Information Extraction System
27th International Conference on Computational Linguistics (COLING 2018)
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
We introduce Graphene, an Open IE system whose goal is to generate accurate, meaningful and complete propositions that may facilitate a variety of downstream semantic applications. For this purpose, we transform syntactically complex input sentences into clean, compact structures in the form of core facts and accompa...
[ { "created": "Tue, 28 Aug 2018 18:00:44 GMT", "version": "v1" } ]
2018-08-30
[ [ "Cetto", "Matthias", "" ], [ "Niklaus", "Christina", "" ], [ "Freitas", "André", "" ], [ "Handschuh", "Siegfried", "" ] ]
We introduce Graphene, an Open IE system whose goal is to generate accurate, meaningful and complete propositions that may facilitate a variety of downstream semantic applications. For this purpose, we transform syntactically complex input sentences into clean, compact structures in the form of core facts and accompany...
1909.08240
EPTCS
David Spies (University of Alberta), Jia-Huai You (University of Alberta), Ryan Hayward (University of Alberta)
Mutex Graphs and Multicliques: Reducing Grounding Size for Planning
In Proceedings ICLP 2019, arXiv:1909.07646
EPTCS 306, 2019, pp. 140-153
10.4204/EPTCS.306.20
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present an approach to representing large sets of mutual exclusions, also known as mutexes or mutex constraints. These are the types of constraints that specify the exclusion of some properties, events, processes, and so on. They are ubiquitous in many areas of applications. The size of these constraints for a giv...
[ { "created": "Wed, 18 Sep 2019 07:04:54 GMT", "version": "v1" } ]
2019-09-19
[ [ "Spies", "David", "", "University of Alberta" ], [ "You", "Jia-Huai", "", "University of\n Alberta" ], [ "Hayward", "Ryan", "", "University of Alberta" ] ]
We present an approach to representing large sets of mutual exclusions, also known as mutexes or mutex constraints. These are the types of constraints that specify the exclusion of some properties, events, processes, and so on. They are ubiquitous in many areas of applications. The size of these constraints for a given...
cs/0201023
Andree Blotz
Andree Blotz (1), Franz Huber (2), Heiko Loetzbeyer (3), Alexander Pretschner (3), Oscar Slotosch (2), Hans-Peter Zaengerl (2) ((1) EADS Deutschland GmbH, (2) Validas AG, (3) TU Munich)
Model-Based Software Engineering and Ada: Synergy for the Development of Safety-Critical Systems
16 pages, figures included, paper accepted for ADA Deutschland Tagung 2002, March 6-8, Jena, GERMANY
null
null
null
cs.SE
null
In this paper we outline a software development process for safety-critical systems that aims at combining some of the specific strengths of model-based development with those of programming language based development using safety-critical subsets of Ada. Model-based software development and model-based test case gen...
[ { "created": "Sat, 26 Jan 2002 11:32:31 GMT", "version": "v1" } ]
2007-05-23
[ [ "Blotz", "Andree", "" ], [ "Huber", "Franz", "" ], [ "Loetzbeyer", "Heiko", "" ], [ "Pretschner", "Alexander", "" ], [ "Slotosch", "Oscar", "" ], [ "Zaengerl", "Hans-Peter", "" ] ]
In this paper we outline a software development process for safety-critical systems that aims at combining some of the specific strengths of model-based development with those of programming language based development using safety-critical subsets of Ada. Model-based software development and model-based test case gener...
2203.01548
Ziyi Zhou
Ziyi Zhou, Bruce Wingo, Nathan Boyd, Seth Hutchinson, and Ye Zhao
Momentum-Aware Trajectory Optimization and Control for Agile Quadrupedal Locomotion
null
null
null
null
cs.RO
http://creativecommons.org/licenses/by-nc-sa/4.0/
In this letter, we present a versatile hierarchical offline planning algorithm, along with an online control pipeline for agile quadrupedal locomotion. Our offline planner alternates between optimizing centroidal dynamics for a reduced-order model and whole-body trajectory optimization, with the aim of achieving dyna...
[ { "created": "Thu, 3 Mar 2022 07:30:06 GMT", "version": "v1" }, { "created": "Sun, 19 Jun 2022 01:37:02 GMT", "version": "v2" } ]
2022-06-22
[ [ "Zhou", "Ziyi", "" ], [ "Wingo", "Bruce", "" ], [ "Boyd", "Nathan", "" ], [ "Hutchinson", "Seth", "" ], [ "Zhao", "Ye", "" ] ]
In this letter, we present a versatile hierarchical offline planning algorithm, along with an online control pipeline for agile quadrupedal locomotion. Our offline planner alternates between optimizing centroidal dynamics for a reduced-order model and whole-body trajectory optimization, with the aim of achieving dynami...
2406.18460
Ahmed Njifenjou
Ahmed Njifenjou, Virgile Sucal, Bassam Jabaian and Fabrice Lef\`evre
Role-Play Zero-Shot Prompting with Large Language Models for Open-Domain Human-Machine Conversation
Updated version of a paper originally submitted at SIGDIAL 2023
null
null
null
cs.CL cs.AI cs.HC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recently, various methods have been proposed to create open-domain conversational agents with Large Language Models (LLMs). These models are able to answer user queries, but in a one-way Q&A format rather than a true conversation. Fine-tuning on particular datasets is the usual way to modify their style to increase c...
[ { "created": "Wed, 26 Jun 2024 16:10:53 GMT", "version": "v1" } ]
2024-07-02
[ [ "Njifenjou", "Ahmed", "" ], [ "Sucal", "Virgile", "" ], [ "Jabaian", "Bassam", "" ], [ "Lefèvre", "Fabrice", "" ] ]
Recently, various methods have been proposed to create open-domain conversational agents with Large Language Models (LLMs). These models are able to answer user queries, but in a one-way Q&A format rather than a true conversation. Fine-tuning on particular datasets is the usual way to modify their style to increase con...
2104.05974
Mengmeng Yang
Mengmeng Yang, Ivan Tjuawinata, Kwok-Yan Lam, Tianqing Zhu, Jun Zhao
Fair and Differentially Private Distributed Frequency Estimation
null
null
null
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In order to remain competitive, Internet companies collect and analyse user data for the purpose of improving user experiences. Frequency estimation is a widely used statistical tool which could potentially conflict with the relevant privacy regulations. Privacy preserving analytic methods based on differential priva...
[ { "created": "Tue, 13 Apr 2021 07:02:16 GMT", "version": "v1" } ]
2021-04-14
[ [ "Yang", "Mengmeng", "" ], [ "Tjuawinata", "Ivan", "" ], [ "Lam", "Kwok-Yan", "" ], [ "Zhu", "Tianqing", "" ], [ "Zhao", "Jun", "" ] ]
In order to remain competitive, Internet companies collect and analyse user data for the purpose of improving user experiences. Frequency estimation is a widely used statistical tool which could potentially conflict with the relevant privacy regulations. Privacy preserving analytic methods based on differential privacy...
2203.13321
Yeshwanth Venkatesha
Yeshwanth Venkatesha, Youngeun Kim, Hyoungseob Park, Yuhang Li, Priyadarshini Panda
Addressing Client Drift in Federated Continual Learning with Adaptive Optimization
null
null
null
null
cs.LG cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Federated learning has been extensively studied and is the prevalent method for privacy-preserving distributed learning in edge devices. Correspondingly, continual learning is an emerging field targeted towards learning multiple tasks sequentially. However, there is little attention towards additional challenges emer...
[ { "created": "Thu, 24 Mar 2022 20:00:03 GMT", "version": "v1" } ]
2022-03-28
[ [ "Venkatesha", "Yeshwanth", "" ], [ "Kim", "Youngeun", "" ], [ "Park", "Hyoungseob", "" ], [ "Li", "Yuhang", "" ], [ "Panda", "Priyadarshini", "" ] ]
Federated learning has been extensively studied and is the prevalent method for privacy-preserving distributed learning in edge devices. Correspondingly, continual learning is an emerging field targeted towards learning multiple tasks sequentially. However, there is little attention towards additional challenges emergi...
1503.07795
Marina Sokolova
Naveen Kumar Parachur Cotha and Marina Sokolova
Multi-Labeled Classification of Demographic Attributes of Patients: a case study of diabetics patients
16 pages, 9 tables
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Automated learning of patients demographics can be seen as multi-label problem where a patient model is based on different race and gender groups. The resulting model can be further integrated into Privacy-Preserving Data Mining, where it can be used to assess risk of identification of different patient groups. Our p...
[ { "created": "Thu, 26 Mar 2015 17:22:26 GMT", "version": "v1" } ]
2015-03-27
[ [ "Cotha", "Naveen Kumar Parachur", "" ], [ "Sokolova", "Marina", "" ] ]
Automated learning of patients demographics can be seen as multi-label problem where a patient model is based on different race and gender groups. The resulting model can be further integrated into Privacy-Preserving Data Mining, where it can be used to assess risk of identification of different patient groups. Our pro...
2109.13126
Fidan Samet
Fidan Samet and Oguz Bakir
GANiry: Bald-to-Hairy Translation Using CycleGAN
null
null
null
null
cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This work presents our computer vision course project called bald men-to-hairy men translation using CycleGAN. On top of CycleGAN architecture, we utilize perceptual loss in order to achieve more realistic results. We also integrate conditional constrains to obtain different stylized and colored hairs on bald men. We...
[ { "created": "Mon, 27 Sep 2021 15:39:27 GMT", "version": "v1" } ]
2021-09-28
[ [ "Samet", "Fidan", "" ], [ "Bakir", "Oguz", "" ] ]
This work presents our computer vision course project called bald men-to-hairy men translation using CycleGAN. On top of CycleGAN architecture, we utilize perceptual loss in order to achieve more realistic results. We also integrate conditional constrains to obtain different stylized and colored hairs on bald men. We c...
1909.06045
Ajay Kumar
Ritesh Vyas and Ajay Kumar
A Collaborative Approach using Ridge-Valley Minutiae for More Accurate Contactless Fingerprint Identification
null
null
null
null
cs.CV eess.IV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Contactless fingerprint identification has emerged as an reliable and user friendly alternative for the personal identification in a range of e-business and law-enforcement applications. It is however quite known from the literature that the contactless fingerprint images deliver remarkably low matching accuracies as...
[ { "created": "Fri, 13 Sep 2019 05:56:52 GMT", "version": "v1" }, { "created": "Thu, 19 Sep 2019 07:40:23 GMT", "version": "v2" } ]
2019-09-20
[ [ "Vyas", "Ritesh", "" ], [ "Kumar", "Ajay", "" ] ]
Contactless fingerprint identification has emerged as an reliable and user friendly alternative for the personal identification in a range of e-business and law-enforcement applications. It is however quite known from the literature that the contactless fingerprint images deliver remarkably low matching accuracies as c...
1703.00941
Stefan Schneider
Marvin K\"unnemann, Ramamohan Paturi, Stefan Schneider
On the Fine-grained Complexity of One-Dimensional Dynamic Programming
null
null
null
null
cs.CC cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we investigate the complexity of one-dimensional dynamic programming, or more specifically, of the Least-Weight Subsequence (LWS) problem: Given a sequence of $n$ data items together with weights for every pair of the items, the task is to determine a subsequence $S$ minimizing the total weight of the ...
[ { "created": "Thu, 2 Mar 2017 20:25:04 GMT", "version": "v1" } ]
2017-03-06
[ [ "Künnemann", "Marvin", "" ], [ "Paturi", "Ramamohan", "" ], [ "Schneider", "Stefan", "" ] ]
In this paper, we investigate the complexity of one-dimensional dynamic programming, or more specifically, of the Least-Weight Subsequence (LWS) problem: Given a sequence of $n$ data items together with weights for every pair of the items, the task is to determine a subsequence $S$ minimizing the total weight of the pa...
2404.00506
Shaofei Shen
Shaofei Shen, Chenhao Zhang, Yawen Zhao, Alina Bialkowski, Weitong Tony Chen, Miao Xu
Label-Agnostic Forgetting: A Supervision-Free Unlearning in Deep Models
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Machine unlearning aims to remove information derived from forgotten data while preserving that of the remaining dataset in a well-trained model. With the increasing emphasis on data privacy, several approaches to machine unlearning have emerged. However, these methods typically rely on complete supervision throughou...
[ { "created": "Sun, 31 Mar 2024 00:29:00 GMT", "version": "v1" }, { "created": "Tue, 7 May 2024 16:06:50 GMT", "version": "v2" } ]
2024-05-08
[ [ "Shen", "Shaofei", "" ], [ "Zhang", "Chenhao", "" ], [ "Zhao", "Yawen", "" ], [ "Bialkowski", "Alina", "" ], [ "Chen", "Weitong Tony", "" ], [ "Xu", "Miao", "" ] ]
Machine unlearning aims to remove information derived from forgotten data while preserving that of the remaining dataset in a well-trained model. With the increasing emphasis on data privacy, several approaches to machine unlearning have emerged. However, these methods typically rely on complete supervision throughout ...
2402.14367
Tianyu Fu
Rex Ying, Tianyu Fu, Andrew Wang, Jiaxuan You, Yu Wang, Jure Leskovec
Representation Learning for Frequent Subgraph Mining
Oral Presentation in The Graph Representation Learning and Beyond (GRL+) Workshop from The 37th International Conference on Ma- chine Learning, 2020
null
null
null
cs.LG cs.SI
http://creativecommons.org/licenses/by/4.0/
Identifying frequent subgraphs, also called network motifs, is crucial in analyzing and predicting properties of real-world networks. However, finding large commonly-occurring motifs remains a challenging problem not only due to its NP-hard subroutine of subgraph counting, but also the exponential growth of the numbe...
[ { "created": "Thu, 22 Feb 2024 08:11:22 GMT", "version": "v1" } ]
2024-02-23
[ [ "Ying", "Rex", "" ], [ "Fu", "Tianyu", "" ], [ "Wang", "Andrew", "" ], [ "You", "Jiaxuan", "" ], [ "Wang", "Yu", "" ], [ "Leskovec", "Jure", "" ] ]
Identifying frequent subgraphs, also called network motifs, is crucial in analyzing and predicting properties of real-world networks. However, finding large commonly-occurring motifs remains a challenging problem not only due to its NP-hard subroutine of subgraph counting, but also the exponential growth of the number ...