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2203.07830
Shashikiran Venkatesha
Shashikiran Venkatesha and Ranjani Parthasarathi
A Survey of fault models and fault tolerance methods for 2D bus-based multi-core systems and TSV based 3D NOC many-core systems
An Elaborate survey on fault models and fault tolerant designs for multi-core and many-core systems
null
null
null
cs.AR
http://creativecommons.org/licenses/by/4.0/
Reliability has taken centre stage in the development of high-performance computing processors. A Surge of interest is noticeable in recent times in formulating fault and failure models, understanding failure mechanism and strategizing fault mitigation methods for improving the reliability of the system. The article ...
[ { "created": "Tue, 15 Mar 2022 12:36:14 GMT", "version": "v1" } ]
2022-03-16
[ [ "Venkatesha", "Shashikiran", "" ], [ "Parthasarathi", "Ranjani", "" ] ]
Reliability has taken centre stage in the development of high-performance computing processors. A Surge of interest is noticeable in recent times in formulating fault and failure models, understanding failure mechanism and strategizing fault mitigation methods for improving the reliability of the system. The article pr...
2305.07100
Floor Eijkelboom
Floor Eijkelboom, Rob Hesselink, Erik Bekkers
E(n) Equivariant Message Passing Simplicial Networks
null
Proceedings of the 40th International Conference on Machine Learning, PMLR 202:9071-9081, 2023
null
null
cs.LG cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper presents $\mathrm{E}(n)$ Equivariant Message Passing Simplicial Networks (EMPSNs), a novel approach to learning on geometric graphs and point clouds that is equivariant to rotations, translations, and reflections. EMPSNs can learn high-dimensional simplex features in graphs (e.g. triangles), and use the in...
[ { "created": "Thu, 11 May 2023 19:10:26 GMT", "version": "v1" }, { "created": "Sun, 22 Oct 2023 16:36:55 GMT", "version": "v2" } ]
2023-10-24
[ [ "Eijkelboom", "Floor", "" ], [ "Hesselink", "Rob", "" ], [ "Bekkers", "Erik", "" ] ]
This paper presents $\mathrm{E}(n)$ Equivariant Message Passing Simplicial Networks (EMPSNs), a novel approach to learning on geometric graphs and point clouds that is equivariant to rotations, translations, and reflections. EMPSNs can learn high-dimensional simplex features in graphs (e.g. triangles), and use the incr...
1810.02670
Kanstantsin Pashkovich
Kanstantsin Pashkovich
Computing the Nucleolus of Weighted Voting Games in Pseudo-polynomial Time
null
null
null
null
cs.GT math.OC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We provide an algorithm for computing the nucleolus for an instance of a weighted voting game in pseudo-polynomial time. This resolves an open question posed by Elkind. et.al. 2007.
[ { "created": "Wed, 3 Oct 2018 23:53:38 GMT", "version": "v1" } ]
2018-10-08
[ [ "Pashkovich", "Kanstantsin", "" ] ]
We provide an algorithm for computing the nucleolus for an instance of a weighted voting game in pseudo-polynomial time. This resolves an open question posed by Elkind. et.al. 2007.
1306.3914
Thomas Zemen
Laura Bernad\'o and Thomas Zemen and Fredrik Tufvesson and Andreas F. Molisch and Christoph F. Mecklenbr\"auker
Time- and Frequency-Varying $K$-Factor of Non-Stationary Vehicular Channels for Safety Relevant Scenarios
26 pages, 12 figures, submitted to IEEE Transactions on Intelligent Transportation Systems for possible publication
IEEE Transactions on Intelligent Transportation Systems, vol. 16, no. 2, April 2015
10.1109/TITS.2014.2349364
null
cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Vehicular communication channels are characterized by a non-stationary time- and frequency-selective fading process due to fast changes in the environment. We characterize the distribution of the envelope of the first delay bin in vehicle-to-vehicle channels by means of its Rician $K$-factor. We analyze the time-freq...
[ { "created": "Mon, 17 Jun 2013 16:12:50 GMT", "version": "v1" }, { "created": "Fri, 17 Jan 2014 19:57:20 GMT", "version": "v2" }, { "created": "Fri, 25 Apr 2014 17:44:25 GMT", "version": "v3" } ]
2015-04-06
[ [ "Bernadó", "Laura", "" ], [ "Zemen", "Thomas", "" ], [ "Tufvesson", "Fredrik", "" ], [ "Molisch", "Andreas F.", "" ], [ "Mecklenbräuker", "Christoph F.", "" ] ]
Vehicular communication channels are characterized by a non-stationary time- and frequency-selective fading process due to fast changes in the environment. We characterize the distribution of the envelope of the first delay bin in vehicle-to-vehicle channels by means of its Rician $K$-factor. We analyze the time-freque...
2305.06901
Marcell Szak\'aly
Marcell Szak\'aly, Sebastian K\"ohler, Martin Strohmeier, Ivan Martinovic
Assault and Battery: Evaluating the Security of Power Conversion Systems Against Electromagnetic Injection Attacks
null
null
null
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Many modern devices, including critical infrastructures, depend on the reliable operation of electrical power conversion systems. The small size and versatility of switched-mode power converters has resulted in their widespread adoption. Whereas transformer-based systems passively convert voltage, switched-mode conve...
[ { "created": "Thu, 11 May 2023 15:42:30 GMT", "version": "v1" } ]
2023-05-12
[ [ "Szakály", "Marcell", "" ], [ "Köhler", "Sebastian", "" ], [ "Strohmeier", "Martin", "" ], [ "Martinovic", "Ivan", "" ] ]
Many modern devices, including critical infrastructures, depend on the reliable operation of electrical power conversion systems. The small size and versatility of switched-mode power converters has resulted in their widespread adoption. Whereas transformer-based systems passively convert voltage, switched-mode convert...
2006.02047
Haoyang Cao
Haoyang Cao and Xin Guo
SDE approximations of GANs training and its long-run behavior
null
null
null
null
cs.LG math.PR stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper analyzes the training process of GANs via stochastic differential equations (SDEs). It first establishes SDE approximations for the training of GANs under stochastic gradient algorithms, with precise error bound analysis. It then describes the long-run behavior of GANs training via the invariant measures o...
[ { "created": "Wed, 3 Jun 2020 05:08:21 GMT", "version": "v1" }, { "created": "Mon, 15 Jun 2020 05:14:19 GMT", "version": "v2" }, { "created": "Thu, 13 Aug 2020 02:39:57 GMT", "version": "v3" }, { "created": "Thu, 19 Nov 2020 16:10:47 GMT", "version": "v4" }, { "cr...
2022-02-15
[ [ "Cao", "Haoyang", "" ], [ "Guo", "Xin", "" ] ]
This paper analyzes the training process of GANs via stochastic differential equations (SDEs). It first establishes SDE approximations for the training of GANs under stochastic gradient algorithms, with precise error bound analysis. It then describes the long-run behavior of GANs training via the invariant measures of ...
2301.08956
Odemir Bruno PhD
Joao V. Merenda, Odemir M. Bruno
Using deterministic tourist walk as a small-world metric on Watts-Strogatz networks
9 pages, 4 figures
null
10.1016/j.physa.2023.128713
null
cs.SI physics.data-an
http://creativecommons.org/licenses/by-nc-nd/4.0/
The Watts-Strogatz model (WS) has been demonstrated to effectively describe real-world networks due to its ability to reproduce the small-world properties commonly observed in a variety of systems, including social networks, computer networks, biochemical reactions, and neural networks. As the presence of small-world...
[ { "created": "Sat, 21 Jan 2023 14:26:55 GMT", "version": "v1" } ]
2023-05-24
[ [ "Merenda", "Joao V.", "" ], [ "Bruno", "Odemir M.", "" ] ]
The Watts-Strogatz model (WS) has been demonstrated to effectively describe real-world networks due to its ability to reproduce the small-world properties commonly observed in a variety of systems, including social networks, computer networks, biochemical reactions, and neural networks. As the presence of small-world p...
1901.05906
Xinyu Hu
Xinyu Hu, Paul Szerlip, Theofanis Karaletsos, Rohit Singh
Applying SVGD to Bayesian Neural Networks for Cyclical Time-Series Prediction and Inference
Third workshop on Bayesian Deep Learning (NeurIPS 2018)
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A regression-based BNN model is proposed to predict spatiotemporal quantities like hourly rider demand with calibrated uncertainties. The main contributions of this paper are (i) A feed-forward deterministic neural network (DetNN) architecture that predicts cyclical time series data with sensitivity to anomalous fore...
[ { "created": "Thu, 17 Jan 2019 17:08:59 GMT", "version": "v1" } ]
2019-01-18
[ [ "Hu", "Xinyu", "" ], [ "Szerlip", "Paul", "" ], [ "Karaletsos", "Theofanis", "" ], [ "Singh", "Rohit", "" ] ]
A regression-based BNN model is proposed to predict spatiotemporal quantities like hourly rider demand with calibrated uncertainties. The main contributions of this paper are (i) A feed-forward deterministic neural network (DetNN) architecture that predicts cyclical time series data with sensitivity to anomalous foreca...
2107.01544
EPTCS
Chantal Keller (JKU Linz), Mathias Fleury (LRI, Universit\'e Paris Saclay, and CNRS)
Proceedings Seventh Workshop on Proof eXchange for Theorem Proving
null
EPTCS 336, 2021
10.4204/EPTCS.336
null
cs.LO
http://creativecommons.org/licenses/by/4.0/
This volume of EPTCS contains the proceedings of the Seventh Workshop on Proof Exchange for Theorem Proving (PxTP 2021), held on 11 July 2021 as part of the CADE-28 online conference in Pittsburgh, USA. The PxTP workshop series brings together researchers working on various aspects of communication, integration, and ...
[ { "created": "Sun, 4 Jul 2021 05:29:34 GMT", "version": "v1" } ]
2021-07-06
[ [ "Keller", "Chantal", "", "JKU Linz" ], [ "Fleury", "Mathias", "", "LRI, Université Paris\n Saclay, and CNRS" ] ]
This volume of EPTCS contains the proceedings of the Seventh Workshop on Proof Exchange for Theorem Proving (PxTP 2021), held on 11 July 2021 as part of the CADE-28 online conference in Pittsburgh, USA. The PxTP workshop series brings together researchers working on various aspects of communication, integration, and co...
1003.4836
Carmelo Malta
Carmelo Malta, Jos\'e Martinez (LINA)
Automating Fine Concurrency Control in Object-Oriented Databases
null
IEEE 9th International Conference on Data Engineering (ICDE'93), Vienn : Austria (1993)
10.1109/ICDE.1993.344057
null
cs.DB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Several propositions were done to provide adapted concurrency control to object-oriented databases. However, most of these proposals miss the fact that considering solely read and write access modes on instances may lead to less parallelism than in relational databases! This paper cope with that issue, and advantages...
[ { "created": "Thu, 25 Mar 2010 09:55:48 GMT", "version": "v1" } ]
2010-03-26
[ [ "Malta", "Carmelo", "", "LINA" ], [ "Martinez", "José", "", "LINA" ] ]
Several propositions were done to provide adapted concurrency control to object-oriented databases. However, most of these proposals miss the fact that considering solely read and write access modes on instances may lead to less parallelism than in relational databases! This paper cope with that issue, and advantages a...
1906.08385
Dominik St\"oger
Felix Krahmer, Dominik St\"oger
Complex phase retrieval from subgaussian measurements
25 pages
null
null
null
cs.IT math.IT math.ST stat.TH
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Phase retrieval refers to the problem of reconstructing an unknown vector $x_0 \in \mathbb{C}^n$ or $x_0 \in \mathbb{R}^n $ from $m$ measurements of the form $y_i = \big\vert \langle \xi^{\left(i\right)}, x_0 \rangle \big\vert^2 $, where $ \left\{ \xi^{\left(i\right)} \right\}^m_{i=1} \subset \mathbb{C}^m $ are known...
[ { "created": "Wed, 19 Jun 2019 22:36:45 GMT", "version": "v1" }, { "created": "Fri, 17 Jul 2020 18:50:15 GMT", "version": "v2" } ]
2020-07-21
[ [ "Krahmer", "Felix", "" ], [ "Stöger", "Dominik", "" ] ]
Phase retrieval refers to the problem of reconstructing an unknown vector $x_0 \in \mathbb{C}^n$ or $x_0 \in \mathbb{R}^n $ from $m$ measurements of the form $y_i = \big\vert \langle \xi^{\left(i\right)}, x_0 \rangle \big\vert^2 $, where $ \left\{ \xi^{\left(i\right)} \right\}^m_{i=1} \subset \mathbb{C}^m $ are known m...
1211.4258
Matthew Andrews
Matthew Andrews and Lisa Zhang
Utility Optimization in Heterogeneous Networks via CSMA-Based Algorithms
null
null
null
null
cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We study algorithms for carrier and rate allocation in cellular systems with distributed components such as a heterogeneous LTE system with macrocells and femtocells. Existing work on LTE systems often involves centralized techniques or requires significant signaling, and is therefore not always applicable in the pre...
[ { "created": "Sun, 18 Nov 2012 21:15:13 GMT", "version": "v1" }, { "created": "Tue, 20 Nov 2012 14:07:54 GMT", "version": "v2" }, { "created": "Thu, 3 Jan 2013 15:27:20 GMT", "version": "v3" } ]
2013-01-04
[ [ "Andrews", "Matthew", "" ], [ "Zhang", "Lisa", "" ] ]
We study algorithms for carrier and rate allocation in cellular systems with distributed components such as a heterogeneous LTE system with macrocells and femtocells. Existing work on LTE systems often involves centralized techniques or requires significant signaling, and is therefore not always applicable in the prese...
2003.09266
Aruni Choudhary
Man-Kwun Chiu and Aruni Choudhary and Wolfgang Mulzer
Computational Complexity of the $\alpha$-Ham-Sandwich Problem
null
null
null
null
cs.CG cs.CC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The classic Ham-Sandwich theorem states that for any $d$ measurable sets in $\mathbb{R}^d$, there is a hyperplane that bisects them simultaneously. An extension by B\'ar\'any, Hubard, and Jer\'onimo [DCG 2008] states that if the sets are convex and \emph{well-separated}, then for any given $\alpha_1, \dots, \alpha_d ...
[ { "created": "Fri, 20 Mar 2020 13:29:28 GMT", "version": "v1" } ]
2020-03-23
[ [ "Chiu", "Man-Kwun", "" ], [ "Choudhary", "Aruni", "" ], [ "Mulzer", "Wolfgang", "" ] ]
The classic Ham-Sandwich theorem states that for any $d$ measurable sets in $\mathbb{R}^d$, there is a hyperplane that bisects them simultaneously. An extension by B\'ar\'any, Hubard, and Jer\'onimo [DCG 2008] states that if the sets are convex and \emph{well-separated}, then for any given $\alpha_1, \dots, \alpha_d \i...
2112.08991
Yixuan Weng
Yixuan Weng, Fei Xia, Bin Li, Xiusheng Huang, Shizhu He
ADBCMM : Acronym Disambiguation by Building Counterfactuals and Multilingual Mixing
SDU@AAAI-2022
null
null
null
cs.CL cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Scientific documents often contain a large number of acronyms. Disambiguation of these acronyms will help researchers better understand the meaning of vocabulary in the documents. In the past, thanks to large amounts of data from English literature, acronym task was mainly applied in English literature. However, for ...
[ { "created": "Wed, 8 Dec 2021 15:08:27 GMT", "version": "v1" }, { "created": "Sat, 5 Feb 2022 15:53:37 GMT", "version": "v2" } ]
2022-02-08
[ [ "Weng", "Yixuan", "" ], [ "Xia", "Fei", "" ], [ "Li", "Bin", "" ], [ "Huang", "Xiusheng", "" ], [ "He", "Shizhu", "" ] ]
Scientific documents often contain a large number of acronyms. Disambiguation of these acronyms will help researchers better understand the meaning of vocabulary in the documents. In the past, thanks to large amounts of data from English literature, acronym task was mainly applied in English literature. However, for ot...
2110.12033
Kossar Pourahmadi-Meibodi
Kossar Pourahmadi, Parsa Nooralinejad, Hamed Pirsiavash
A Simple Baseline for Low-Budget Active Learning
20 pages, 16 tables; additional experiments
null
null
null
cs.CV cs.LG
http://creativecommons.org/licenses/by/4.0/
Active learning focuses on choosing a subset of unlabeled data to be labeled. However, most such methods assume that a large subset of the data can be annotated. We are interested in low-budget active learning where only a small subset (e.g., 0.2% of ImageNet) can be annotated. Instead of proposing a new query strate...
[ { "created": "Fri, 22 Oct 2021 19:36:56 GMT", "version": "v1" }, { "created": "Fri, 1 Apr 2022 17:57:19 GMT", "version": "v2" } ]
2022-04-04
[ [ "Pourahmadi", "Kossar", "" ], [ "Nooralinejad", "Parsa", "" ], [ "Pirsiavash", "Hamed", "" ] ]
Active learning focuses on choosing a subset of unlabeled data to be labeled. However, most such methods assume that a large subset of the data can be annotated. We are interested in low-budget active learning where only a small subset (e.g., 0.2% of ImageNet) can be annotated. Instead of proposing a new query strategy...
0806.1543
Andreas U. Schmidt
Andreas U. Schmidt
On the Superdistribution of Digital Goods
Invited paper at the Wokshop 2008 International Workshop on Multimedia Security in Communication (MUSIC'08) To appear in: Proceedings of 2008 Third International Conference on Communications and Networking in China (CHINACOM'08), August 25-27, 2008, Hangzhou, China
null
null
null
cs.MM cs.CR cs.CY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Business models involving buyers of digital goods in the distribution process are called superdistribution schemes. We review the state-of-the art of research and application of superdistribution and propose systematic approach to market mechanisms using super-distribution and technical system architectures supportin...
[ { "created": "Mon, 9 Jun 2008 22:03:40 GMT", "version": "v1" } ]
2008-06-11
[ [ "Schmidt", "Andreas U.", "" ] ]
Business models involving buyers of digital goods in the distribution process are called superdistribution schemes. We review the state-of-the art of research and application of superdistribution and propose systematic approach to market mechanisms using super-distribution and technical system architectures supporting ...
2009.09048
Richard Savery
Richard Savery, Lisa Zahray, Gil Weinberg
Emotional Musical Prosody for the Enhancement of Trust in Robotic Arm Communication
SCRITA 2020 Trust, Acceptance and Social Cues in Human-Robot Interaction
null
null
null
cs.RO cs.HC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
As robotic arms become prevalent in industry it is crucial to improve levels of trust from human collaborators. Low levels of trust in human-robot interaction can reduce overall performance and prevent full robot utilization. We investigated the potential benefits of using emotional musical prosody to allow the robot...
[ { "created": "Fri, 18 Sep 2020 20:05:13 GMT", "version": "v1" } ]
2020-09-22
[ [ "Savery", "Richard", "" ], [ "Zahray", "Lisa", "" ], [ "Weinberg", "Gil", "" ] ]
As robotic arms become prevalent in industry it is crucial to improve levels of trust from human collaborators. Low levels of trust in human-robot interaction can reduce overall performance and prevent full robot utilization. We investigated the potential benefits of using emotional musical prosody to allow the robot t...
2203.05067
Moise Blanchard
Mo\"ise Blanchard, Patrick Jaillet
Universal Regression with Adversarial Responses
null
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We provide algorithms for regression with adversarial responses under large classes of non-i.i.d. instance sequences, on general separable metric spaces, with provably minimal assumptions. We also give characterizations of learnability in this regression context. We consider universal consistency which asks for stron...
[ { "created": "Wed, 9 Mar 2022 22:10:30 GMT", "version": "v1" }, { "created": "Mon, 14 Mar 2022 14:30:08 GMT", "version": "v2" }, { "created": "Sat, 10 Jun 2023 01:22:34 GMT", "version": "v3" } ]
2023-06-13
[ [ "Blanchard", "Moïse", "" ], [ "Jaillet", "Patrick", "" ] ]
We provide algorithms for regression with adversarial responses under large classes of non-i.i.d. instance sequences, on general separable metric spaces, with provably minimal assumptions. We also give characterizations of learnability in this regression context. We consider universal consistency which asks for strong ...
1707.08147
Amir Masoud Ghalamzan Esfahani
Amir M. Ghalamzan Esfahani, Firas Abi-Farraj, Paolo Robuffo Giordano, and Rustam Stolkin
Human-in-the-loop optimisation: mixed initiative grasping for optimally facilitating post-grasp manipulative actions
To be appeared in IEEE/RAS IROS 2017
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper addresses the problem of mixed initiative, shared control for master-slave grasping and manipulation. We propose a novel system, in which an autonomous agent assists a human in teleoperating a remote slave arm/gripper, using a haptic master device. Our system is designed to exploit the human operator's exp...
[ { "created": "Tue, 25 Jul 2017 18:34:51 GMT", "version": "v1" } ]
2017-07-27
[ [ "Esfahani", "Amir M. Ghalamzan", "" ], [ "Abi-Farraj", "Firas", "" ], [ "Giordano", "Paolo Robuffo", "" ], [ "Stolkin", "Rustam", "" ] ]
This paper addresses the problem of mixed initiative, shared control for master-slave grasping and manipulation. We propose a novel system, in which an autonomous agent assists a human in teleoperating a remote slave arm/gripper, using a haptic master device. Our system is designed to exploit the human operator's exper...
2009.14115
Adam Kortylewski
Yutong Bai, Angtian Wang, Adam Kortylewski, Alan Yuille
CoKe: Localized Contrastive Learning for Robust Keypoint Detection
Accepted to WACV 2023
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we introduce a contrastive learning framework for keypoint detection (CoKe). Keypoint detection differs from other visual tasks where contrastive learning has been applied because the input is a set of images in which multiple keypoints are annotated. This requires the contrastive learning to be extend...
[ { "created": "Tue, 29 Sep 2020 16:00:43 GMT", "version": "v1" }, { "created": "Wed, 30 Sep 2020 01:32:46 GMT", "version": "v2" }, { "created": "Mon, 23 Nov 2020 16:22:35 GMT", "version": "v3" }, { "created": "Mon, 5 Dec 2022 08:56:16 GMT", "version": "v4" } ]
2022-12-06
[ [ "Bai", "Yutong", "" ], [ "Wang", "Angtian", "" ], [ "Kortylewski", "Adam", "" ], [ "Yuille", "Alan", "" ] ]
In this paper, we introduce a contrastive learning framework for keypoint detection (CoKe). Keypoint detection differs from other visual tasks where contrastive learning has been applied because the input is a set of images in which multiple keypoints are annotated. This requires the contrastive learning to be extended...
1709.04857
Kun Xing
Kun Xing
A New Semantic Theory of Natural Language
null
null
null
null
cs.CL cs.LO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Formal Semantics and Distributional Semantics are two important semantic frameworks in Natural Language Processing (NLP). Cognitive Semantics belongs to the movement of Cognitive Linguistics, which is based on contemporary cognitive science. Each framework could deal with some meaning phenomena, but none of them fulf...
[ { "created": "Sun, 10 Sep 2017 13:18:58 GMT", "version": "v1" } ]
2017-09-26
[ [ "Xing", "Kun", "" ] ]
Formal Semantics and Distributional Semantics are two important semantic frameworks in Natural Language Processing (NLP). Cognitive Semantics belongs to the movement of Cognitive Linguistics, which is based on contemporary cognitive science. Each framework could deal with some meaning phenomena, but none of them fulfil...
2303.02758
Manan Suri
Manan Suri, Aaryak Garg, Divya Chaudhary, Ian Gorton, Bijendra Kumar
WADER at SemEval-2023 Task 9: A Weak-labelling framework for Data augmentation in tExt Regression Tasks
null
null
null
null
cs.CL cs.LG
http://creativecommons.org/licenses/by/4.0/
Intimacy is an essential element of human relationships and language is a crucial means of conveying it. Textual intimacy analysis can reveal social norms in different contexts and serve as a benchmark for testing computational models' ability to understand social information. In this paper, we propose a novel weak-l...
[ { "created": "Sun, 5 Mar 2023 19:45:42 GMT", "version": "v1" } ]
2023-03-07
[ [ "Suri", "Manan", "" ], [ "Garg", "Aaryak", "" ], [ "Chaudhary", "Divya", "" ], [ "Gorton", "Ian", "" ], [ "Kumar", "Bijendra", "" ] ]
Intimacy is an essential element of human relationships and language is a crucial means of conveying it. Textual intimacy analysis can reveal social norms in different contexts and serve as a benchmark for testing computational models' ability to understand social information. In this paper, we propose a novel weak-lab...
2308.05737
Alaa Maalouf
Alaa Maalouf and Ninad Jadhav and Krishna Murthy Jatavallabhula and Makram Chahine and Daniel M.Vogt and Robert J. Wood and Antonio Torralba and Daniela Rus
Follow Anything: Open-set detection, tracking, and following in real-time
Project webpage: https://github.com/alaamaalouf/FollowAnything Explainer video: https://www.youtube.com/watch?v=6Mgt3EPytrw
null
null
null
cs.RO cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Tracking and following objects of interest is critical to several robotics use cases, ranging from industrial automation to logistics and warehousing, to healthcare and security. In this paper, we present a robotic system to detect, track, and follow any object in real-time. Our approach, dubbed ``follow anything'' (...
[ { "created": "Thu, 10 Aug 2023 17:57:06 GMT", "version": "v1" }, { "created": "Sat, 10 Feb 2024 03:53:18 GMT", "version": "v2" } ]
2024-02-13
[ [ "Maalouf", "Alaa", "" ], [ "Jadhav", "Ninad", "" ], [ "Jatavallabhula", "Krishna Murthy", "" ], [ "Chahine", "Makram", "" ], [ "Vogt", "Daniel M.", "" ], [ "Wood", "Robert J.", "" ], [ "Torralba", "Antonio", ...
Tracking and following objects of interest is critical to several robotics use cases, ranging from industrial automation to logistics and warehousing, to healthcare and security. In this paper, we present a robotic system to detect, track, and follow any object in real-time. Our approach, dubbed ``follow anything'' (FA...
2404.04557
Zhiyuan Yu
Zhiyuan Yu and Zheng Qin and Lintao Zheng and Kai Xu
Learning Instance-Aware Correspondences for Robust Multi-Instance Point Cloud Registration in Cluttered Scenes
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Multi-instance point cloud registration estimates the poses of multiple instances of a model point cloud in a scene point cloud. Extracting accurate point correspondence is to the center of the problem. Existing approaches usually treat the scene point cloud as a whole, overlooking the separation of instances. Theref...
[ { "created": "Sat, 6 Apr 2024 08:51:07 GMT", "version": "v1" } ]
2024-04-09
[ [ "Yu", "Zhiyuan", "" ], [ "Qin", "Zheng", "" ], [ "Zheng", "Lintao", "" ], [ "Xu", "Kai", "" ] ]
Multi-instance point cloud registration estimates the poses of multiple instances of a model point cloud in a scene point cloud. Extracting accurate point correspondence is to the center of the problem. Existing approaches usually treat the scene point cloud as a whole, overlooking the separation of instances. Therefor...
2106.01288
Charlotte Frenkel
Charlotte Frenkel, David Bol, Giacomo Indiveri
Bottom-up and top-down approaches for the design of neuromorphic processing systems: Tradeoffs and synergies between natural and artificial intelligence
Accepted for publication in Proceedings of the IEEE
null
10.1109/JPROC.2023.3273520
null
cs.NE cs.AI cs.ET
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
While Moore's law has driven exponential computing power expectations, its nearing end calls for new avenues for improving the overall system performance. One of these avenues is the exploration of alternative brain-inspired computing architectures that aim at achieving the flexibility and computational efficiency of...
[ { "created": "Wed, 2 Jun 2021 16:51:45 GMT", "version": "v1" }, { "created": "Fri, 12 May 2023 22:20:46 GMT", "version": "v2" } ]
2023-05-16
[ [ "Frenkel", "Charlotte", "" ], [ "Bol", "David", "" ], [ "Indiveri", "Giacomo", "" ] ]
While Moore's law has driven exponential computing power expectations, its nearing end calls for new avenues for improving the overall system performance. One of these avenues is the exploration of alternative brain-inspired computing architectures that aim at achieving the flexibility and computational efficiency of b...
2403.06354
Michael Andersland
Michael Andersland
Amharic LLaMA and LLaVA: Multimodal LLMs for Low Resource Languages
null
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
Large Language Models (LLMs) like GPT-4 and LLaMA have shown incredible proficiency at natural language processing tasks and have even begun to excel at tasks across other modalities such as vision and audio. Despite their success, LLMs often struggle to perform well on low-resource languages because there is so litt...
[ { "created": "Mon, 11 Mar 2024 01:04:36 GMT", "version": "v1" } ]
2024-03-12
[ [ "Andersland", "Michael", "" ] ]
Large Language Models (LLMs) like GPT-4 and LLaMA have shown incredible proficiency at natural language processing tasks and have even begun to excel at tasks across other modalities such as vision and audio. Despite their success, LLMs often struggle to perform well on low-resource languages because there is so little...
1710.11253
Pavel Kolev
Karl Bringmann, Pavel Kolev, David P. Woodruff
Approximation Algorithms for $\ell_0$-Low Rank Approximation
null
null
null
null
cs.DS cs.DM cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We study the $\ell_0$-Low Rank Approximation Problem, where the goal is, given an $m \times n$ matrix $A$, to output a rank-$k$ matrix $A'$ for which $\|A'-A\|_0$ is minimized. Here, for a matrix $B$, $\|B\|_0$ denotes the number of its non-zero entries. This NP-hard variant of low rank approximation is natural for p...
[ { "created": "Mon, 30 Oct 2017 21:49:48 GMT", "version": "v1" }, { "created": "Mon, 1 Oct 2018 15:06:01 GMT", "version": "v2" } ]
2018-10-02
[ [ "Bringmann", "Karl", "" ], [ "Kolev", "Pavel", "" ], [ "Woodruff", "David P.", "" ] ]
We study the $\ell_0$-Low Rank Approximation Problem, where the goal is, given an $m \times n$ matrix $A$, to output a rank-$k$ matrix $A'$ for which $\|A'-A\|_0$ is minimized. Here, for a matrix $B$, $\|B\|_0$ denotes the number of its non-zero entries. This NP-hard variant of low rank approximation is natural for pro...
2208.11582
Haiyue Yuan
Haiyue Yuan, Enes Altuncu, Shujun Li, Can Baskent
Graphical Models of False Information and Fact Checking Ecosystems
null
null
null
null
cs.SI cs.AI cs.CR
http://creativecommons.org/licenses/by/4.0/
The wide spread of false information online including misinformation and disinformation has become a major problem for our highly digitised and globalised society. A lot of research has been done to better understand different aspects of false information online such as behaviours of different actors and patterns of ...
[ { "created": "Wed, 24 Aug 2022 14:37:41 GMT", "version": "v1" } ]
2022-08-25
[ [ "Yuan", "Haiyue", "" ], [ "Altuncu", "Enes", "" ], [ "Li", "Shujun", "" ], [ "Baskent", "Can", "" ] ]
The wide spread of false information online including misinformation and disinformation has become a major problem for our highly digitised and globalised society. A lot of research has been done to better understand different aspects of false information online such as behaviours of different actors and patterns of sp...
2210.16470
Rehana Mahfuz
Rehana Mahfuz, Yinyi Guo, Erik Visser
Improving Audio Captioning Using Semantic Similarity Metrics
Accepted at ICASSP 2023
null
null
null
cs.MM
http://creativecommons.org/licenses/by/4.0/
Audio captioning quality metrics which are typically borrowed from the machine translation and image captioning areas measure the degree of overlap between predicted tokens and gold reference tokens. In this work, we consider a metric measuring semantic similarities between predicted and reference captions instead of...
[ { "created": "Sat, 29 Oct 2022 02:53:10 GMT", "version": "v1" }, { "created": "Fri, 3 Mar 2023 18:15:34 GMT", "version": "v2" } ]
2023-03-06
[ [ "Mahfuz", "Rehana", "" ], [ "Guo", "Yinyi", "" ], [ "Visser", "Erik", "" ] ]
Audio captioning quality metrics which are typically borrowed from the machine translation and image captioning areas measure the degree of overlap between predicted tokens and gold reference tokens. In this work, we consider a metric measuring semantic similarities between predicted and reference captions instead of m...
2003.09736
Jeremy Wong
Jeremy N. Wong, David J. Yoon, Angela P. Schoellig, Timothy D. Barfoot
Variational Inference with Parameter Learning Applied to Vehicle Trajectory Estimation
IEEE Robotics and Automation Letters (RA-L). 8 pages, 4 figures
null
10.1109/LRA.2020.3007381
null
cs.RO stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present parameter learning in a Gaussian variational inference setting using only noisy measurements (i.e., no groundtruth). This is demonstrated in the context of vehicle trajectory estimation, although the method we propose is general. The paper extends the Exactly Sparse Gaussian Variational Inference (ESGVI) f...
[ { "created": "Sat, 21 Mar 2020 19:48:07 GMT", "version": "v1" }, { "created": "Fri, 10 Jul 2020 01:54:45 GMT", "version": "v2" } ]
2020-07-13
[ [ "Wong", "Jeremy N.", "" ], [ "Yoon", "David J.", "" ], [ "Schoellig", "Angela P.", "" ], [ "Barfoot", "Timothy D.", "" ] ]
We present parameter learning in a Gaussian variational inference setting using only noisy measurements (i.e., no groundtruth). This is demonstrated in the context of vehicle trajectory estimation, although the method we propose is general. The paper extends the Exactly Sparse Gaussian Variational Inference (ESGVI) fra...
1808.01842
Ashkan Norouzi-Fard
Ashkan Norouzi-Fard, Jakub Tarnawski, Slobodan Mitrovi\'c, Amir Zandieh, Aida Mousavifar, and Ola Svensson
Beyond $1/2$-Approximation for Submodular Maximization on Massive Data Streams
null
Proc. of 35th International Conference on Machine Learning (ICML), 2018, pages 3829-3838
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Many tasks in machine learning and data mining, such as data diversification, non-parametric learning, kernel machines, clustering etc., require extracting a small but representative summary from a massive dataset. Often, such problems can be posed as maximizing a submodular set function subject to a cardinality cons...
[ { "created": "Mon, 6 Aug 2018 12:23:42 GMT", "version": "v1" } ]
2018-09-17
[ [ "Norouzi-Fard", "Ashkan", "" ], [ "Tarnawski", "Jakub", "" ], [ "Mitrović", "Slobodan", "" ], [ "Zandieh", "Amir", "" ], [ "Mousavifar", "Aida", "" ], [ "Svensson", "Ola", "" ] ]
Many tasks in machine learning and data mining, such as data diversification, non-parametric learning, kernel machines, clustering etc., require extracting a small but representative summary from a massive dataset. Often, such problems can be posed as maximizing a submodular set function subject to a cardinality constr...
1511.06931
Jason Weston
Jesse Dodge, Andreea Gane, Xiang Zhang, Antoine Bordes, Sumit Chopra, Alexander Miller, Arthur Szlam, Jason Weston
Evaluating Prerequisite Qualities for Learning End-to-End Dialog Systems
null
null
null
null
cs.CL cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A long-term goal of machine learning is to build intelligent conversational agents. One recent popular approach is to train end-to-end models on a large amount of real dialog transcripts between humans (Sordoni et al., 2015; Vinyals & Le, 2015; Shang et al., 2015). However, this approach leaves many questions unanswe...
[ { "created": "Sat, 21 Nov 2015 22:26:49 GMT", "version": "v1" }, { "created": "Tue, 15 Dec 2015 09:31:59 GMT", "version": "v2" }, { "created": "Wed, 6 Jan 2016 04:51:54 GMT", "version": "v3" }, { "created": "Fri, 1 Apr 2016 06:22:44 GMT", "version": "v4" }, { "cre...
2016-04-20
[ [ "Dodge", "Jesse", "" ], [ "Gane", "Andreea", "" ], [ "Zhang", "Xiang", "" ], [ "Bordes", "Antoine", "" ], [ "Chopra", "Sumit", "" ], [ "Miller", "Alexander", "" ], [ "Szlam", "Arthur", "" ], [ "West...
A long-term goal of machine learning is to build intelligent conversational agents. One recent popular approach is to train end-to-end models on a large amount of real dialog transcripts between humans (Sordoni et al., 2015; Vinyals & Le, 2015; Shang et al., 2015). However, this approach leaves many questions unanswere...
1403.6046
Changhong Zhao
Changhong Zhao and Steven Low
Decentralized Primary Frequency Control in Power Networks
7 pages, 2 figures. Submitted to CDC 2014
null
null
null
cs.SY math.OC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We augment existing generator-side primary frequency control with load-side control that are local, ubiquitous, and continuous. The mechanisms on both the generator and the load sides are decentralized in that their control decisions are functions of locally measurable frequency deviations. These local algorithms int...
[ { "created": "Mon, 24 Mar 2014 17:23:08 GMT", "version": "v1" } ]
2014-03-25
[ [ "Zhao", "Changhong", "" ], [ "Low", "Steven", "" ] ]
We augment existing generator-side primary frequency control with load-side control that are local, ubiquitous, and continuous. The mechanisms on both the generator and the load sides are decentralized in that their control decisions are functions of locally measurable frequency deviations. These local algorithms inter...
2005.11724
Yonghui Yang
Le Wu, Yonghui Yang, Lei Chen, Defu Lian, Richang Hong and Meng Wang
Learning to Transfer Graph Embeddings for Inductive Graph based Recommendation
Accepted by SIGIR2020
null
null
null
cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
With the increasing availability of videos, how to edit them and present the most interesting parts to users, i.e., video highlight, has become an urgent need with many broad applications. As users'visual preferences are subjective and vary from person to person, previous generalized video highlight extraction models...
[ { "created": "Sun, 24 May 2020 11:37:48 GMT", "version": "v1" } ]
2020-05-26
[ [ "Wu", "Le", "" ], [ "Yang", "Yonghui", "" ], [ "Chen", "Lei", "" ], [ "Lian", "Defu", "" ], [ "Hong", "Richang", "" ], [ "Wang", "Meng", "" ] ]
With the increasing availability of videos, how to edit them and present the most interesting parts to users, i.e., video highlight, has become an urgent need with many broad applications. As users'visual preferences are subjective and vary from person to person, previous generalized video highlight extraction models f...
2401.14014
Daiki Morinaga
Daiki Morinaga, Youhei Akimoto
Theoretical Analysis of Explicit Averaging and Novel Sign Averaging in Comparison-Based Search
13 pages, 1 figures
null
null
null
cs.NE
http://creativecommons.org/licenses/by/4.0/
In black-box optimization, noise in the objective function is inevitable. Noise disrupts the ranking of candidate solutions in comparison-based optimization, possibly deteriorating the search performance compared with a noiseless scenario. Explicit averaging takes the sample average of noisy objective function values...
[ { "created": "Thu, 25 Jan 2024 08:35:50 GMT", "version": "v1" } ]
2024-01-26
[ [ "Morinaga", "Daiki", "" ], [ "Akimoto", "Youhei", "" ] ]
In black-box optimization, noise in the objective function is inevitable. Noise disrupts the ranking of candidate solutions in comparison-based optimization, possibly deteriorating the search performance compared with a noiseless scenario. Explicit averaging takes the sample average of noisy objective function values a...
2408.04195
Daniel Vargas
Daniel Vargas, Ethan Haque, Matthew Carroll, Daniel Perez, Tyler Roman, Phong Nguyen, Golnaz Habibi
Design and Implementation of Smart Infrastructures and Connected Vehicles in A Mini-city Platform
8 pages, 9 figures, Presented at 2024 IEEE ITSC Conference, 23 Citations
null
null
null
cs.RO
http://creativecommons.org/licenses/by/4.0/
This paper presents a 1/10th scale mini-city platform used as a testing bed for evaluating autonomous and connected vehicles. Using the mini-city platform, we can evaluate different driving scenarios including human-driven and autonomous driving. We provide a unique, visual feature-rich environment for evaluating com...
[ { "created": "Thu, 8 Aug 2024 03:31:04 GMT", "version": "v1" } ]
2024-08-09
[ [ "Vargas", "Daniel", "" ], [ "Haque", "Ethan", "" ], [ "Carroll", "Matthew", "" ], [ "Perez", "Daniel", "" ], [ "Roman", "Tyler", "" ], [ "Nguyen", "Phong", "" ], [ "Habibi", "Golnaz", "" ] ]
This paper presents a 1/10th scale mini-city platform used as a testing bed for evaluating autonomous and connected vehicles. Using the mini-city platform, we can evaluate different driving scenarios including human-driven and autonomous driving. We provide a unique, visual feature-rich environment for evaluating compu...
1902.09958
Sebastian Brandt
Sebastian Brandt
An Automatic Speedup Theorem for Distributed Problems
null
null
null
null
cs.DC cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recently, Brandt et al. [STOC'16] proved a lower bound for the distributed Lov\'asz Local Lemma, which has been conjectured to be tight for sufficiently relaxed LLL criteria by Chang and Pettie [FOCS'17]. At the heart of their result lies a speedup technique that, for graphs of girth at least $2t+2$, transforms any $...
[ { "created": "Tue, 26 Feb 2019 14:27:52 GMT", "version": "v1" } ]
2019-02-27
[ [ "Brandt", "Sebastian", "" ] ]
Recently, Brandt et al. [STOC'16] proved a lower bound for the distributed Lov\'asz Local Lemma, which has been conjectured to be tight for sufficiently relaxed LLL criteria by Chang and Pettie [FOCS'17]. At the heart of their result lies a speedup technique that, for graphs of girth at least $2t+2$, transforms any $t$...
2010.10051
Jieqi Shi
Jieqi Shi, Peiliang Li, Shaojie Shen
Tracking from Patterns: Learning Corresponding Patterns in Point Clouds for 3D Object Tracking
4 pages, ECCV2020 Workshop on Perception for Autonomous Driving(PAD2020)
ECCV2020 Workshop on Perception for Autonomous Driving(PAD2020)
null
null
cs.CV cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A robust 3D object tracker which continuously tracks surrounding objects and estimates their trajectories is key for self-driving vehicles. Most existing tracking methods employ a tracking-by-detection strategy, which usually requires complex pair-wise similarity computation and neglects the nature of continuous obje...
[ { "created": "Tue, 20 Oct 2020 06:07:20 GMT", "version": "v1" } ]
2020-10-21
[ [ "Shi", "Jieqi", "" ], [ "Li", "Peiliang", "" ], [ "Shen", "Shaojie", "" ] ]
A robust 3D object tracker which continuously tracks surrounding objects and estimates their trajectories is key for self-driving vehicles. Most existing tracking methods employ a tracking-by-detection strategy, which usually requires complex pair-wise similarity computation and neglects the nature of continuous object...
2311.10585
Steven Ge
Steven Ge, Toshiya Itoh
Popularity on the 3D-Euclidean Stable Roommates
27 pages, 23 figures
null
null
null
cs.CC
http://creativecommons.org/licenses/by/4.0/
We study the 3D-Euclidean Multidimensional Stable Roommates problem, which asks whether a given set $V$ of $s\cdot n$ agents with a location in 3-dimensional Euclidean space can be partitioned into $n$ disjoint subsets $\pi = \{R_1 ,\dots , R_n\}$ with $|R_i| = s$ for each $R_i \in \pi$ such that $\pi$ is (strictly) ...
[ { "created": "Fri, 17 Nov 2023 15:35:57 GMT", "version": "v1" } ]
2023-11-20
[ [ "Ge", "Steven", "" ], [ "Itoh", "Toshiya", "" ] ]
We study the 3D-Euclidean Multidimensional Stable Roommates problem, which asks whether a given set $V$ of $s\cdot n$ agents with a location in 3-dimensional Euclidean space can be partitioned into $n$ disjoint subsets $\pi = \{R_1 ,\dots , R_n\}$ with $|R_i| = s$ for each $R_i \in \pi$ such that $\pi$ is (strictly) po...
1811.00119
Su Wang
Su Wang, Rahul Gupta, Nancy Chang, Jason Baldridge
A task in a suit and a tie: paraphrase generation with semantic augmentation
null
Association for the Advancement of Artificial Intelligence (AAAI) 2019
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Paraphrasing is rooted in semantics. We show the effectiveness of transformers (Vaswani et al. 2017) for paraphrase generation and further improvements by incorporating PropBank labels via a multi-encoder. Evaluating on MSCOCO and WikiAnswers, we find that transformers are fast and effective, and that semantic augmen...
[ { "created": "Wed, 31 Oct 2018 21:04:04 GMT", "version": "v1" }, { "created": "Wed, 14 Nov 2018 15:24:51 GMT", "version": "v2" } ]
2018-11-15
[ [ "Wang", "Su", "" ], [ "Gupta", "Rahul", "" ], [ "Chang", "Nancy", "" ], [ "Baldridge", "Jason", "" ] ]
Paraphrasing is rooted in semantics. We show the effectiveness of transformers (Vaswani et al. 2017) for paraphrase generation and further improvements by incorporating PropBank labels via a multi-encoder. Evaluating on MSCOCO and WikiAnswers, we find that transformers are fast and effective, and that semantic augmenta...
2405.06242
Md Sadik Awal
Md Sadik Awal, Buddhipriya Gayanath, and Md Tauhidur Rahman
Impedance vs. Power Side-channel Vulnerabilities: A Comparative Study
null
null
null
null
cs.CR cs.IR
http://creativecommons.org/licenses/by/4.0/
In recent times, impedance side-channel analysis has emerged as a potent strategy for adversaries seeking to extract sensitive information from computing systems. It leverages variations in the intrinsic impedance of a chip's internal structure across different logic states. In this study, we conduct a comparative an...
[ { "created": "Fri, 10 May 2024 04:44:34 GMT", "version": "v1" } ]
2024-05-13
[ [ "Awal", "Md Sadik", "" ], [ "Gayanath", "Buddhipriya", "" ], [ "Rahman", "Md Tauhidur", "" ] ]
In recent times, impedance side-channel analysis has emerged as a potent strategy for adversaries seeking to extract sensitive information from computing systems. It leverages variations in the intrinsic impedance of a chip's internal structure across different logic states. In this study, we conduct a comparative anal...
2206.13968
Alexander Lobashev
Nikita Turko, Alexander Lobashev, Konstantin Ushakov, Maxim Kaurkin, Rashit Ibrayev
Information Entropy Initialized Concrete Autoencoder for Optimal Sensor Placement and Reconstruction of Geophysical Fields
18 pages, 6 figures
null
null
null
cs.LG cs.CV physics.ao-ph
http://creativecommons.org/licenses/by/4.0/
We propose a new approach to the optimal placement of sensors for the problem of reconstructing geophysical fields from sparse measurements. Our method consists of two stages. In the first stage, we estimate the variability of the physical field as a function of spatial coordinates by approximating its information en...
[ { "created": "Tue, 28 Jun 2022 12:43:38 GMT", "version": "v1" } ]
2022-06-29
[ [ "Turko", "Nikita", "" ], [ "Lobashev", "Alexander", "" ], [ "Ushakov", "Konstantin", "" ], [ "Kaurkin", "Maxim", "" ], [ "Ibrayev", "Rashit", "" ] ]
We propose a new approach to the optimal placement of sensors for the problem of reconstructing geophysical fields from sparse measurements. Our method consists of two stages. In the first stage, we estimate the variability of the physical field as a function of spatial coordinates by approximating its information entr...
1904.05615
Fabrice Guillemin
Fabrice Guillemin, Veronica Quintuna Rodriguez, Alain Simonian
A Processor-Sharing model for the Performance of Virtualized Network Functions
Submitted for publication
null
null
null
cs.PF
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The parallel execution of requests in a Cloud Computing platform, as for Virtualized Network Functions, is modeled by an $M^{[X]}/M/1$ Processor-Sharing (PS) system, where each request is seen as a batch of unit jobs. The performance of such paralleled system can then be measured by the quantiles of the batch sojourn...
[ { "created": "Thu, 11 Apr 2019 10:32:02 GMT", "version": "v1" } ]
2019-04-12
[ [ "Guillemin", "Fabrice", "" ], [ "Rodriguez", "Veronica Quintuna", "" ], [ "Simonian", "Alain", "" ] ]
The parallel execution of requests in a Cloud Computing platform, as for Virtualized Network Functions, is modeled by an $M^{[X]}/M/1$ Processor-Sharing (PS) system, where each request is seen as a batch of unit jobs. The performance of such paralleled system can then be measured by the quantiles of the batch sojourn t...
1912.08674
Tillmann Miltzow
Mikkel Abrahamsen and Tillmann Miltzow
Dynamic Toolbox for ETRINV
19 pages, 3 figures
null
null
null
cs.CC cs.CG cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recently, various natural algorithmic problems have been shown to be $\exists \mathbb{R}$-complete. The reduction relied in many cases on the $\exists \mathbb{R}$-completeness of the problem ETR-INV, which served as a useful intermediate problem. Often some strengthening and modification of ETR-INV was required. This...
[ { "created": "Wed, 18 Dec 2019 15:46:01 GMT", "version": "v1" } ]
2019-12-19
[ [ "Abrahamsen", "Mikkel", "" ], [ "Miltzow", "Tillmann", "" ] ]
Recently, various natural algorithmic problems have been shown to be $\exists \mathbb{R}$-complete. The reduction relied in many cases on the $\exists \mathbb{R}$-completeness of the problem ETR-INV, which served as a useful intermediate problem. Often some strengthening and modification of ETR-INV was required. This l...
1807.02235
Zirui Wang
Zirui Wang and Jaime Carbonell
Towards more Reliable Transfer Learning
ECML-PKDD 2018
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Multi-source transfer learning has been proven effective when within-target labeled data is scarce. Previous work focuses primarily on exploiting domain similarities and assumes that source domains are richly or at least comparably labeled. While this strong assumption is never true in practice, this paper relaxes it...
[ { "created": "Fri, 6 Jul 2018 03:22:29 GMT", "version": "v1" } ]
2018-07-09
[ [ "Wang", "Zirui", "" ], [ "Carbonell", "Jaime", "" ] ]
Multi-source transfer learning has been proven effective when within-target labeled data is scarce. Previous work focuses primarily on exploiting domain similarities and assumes that source domains are richly or at least comparably labeled. While this strong assumption is never true in practice, this paper relaxes it a...
1810.00329
Lu\'is Alexandre
Vasco Lopes and Lu\'is A. Alexandre
An Overview of Blockchain Integration with Robotics and Artificial Intelligence
null
null
null
null
cs.AI cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Blockchain technology is growing everyday at a fast-passed rhythm and it's possible to integrate it with many systems, namely Robotics with AI services. However, this is still a recent field and there isn't yet a clear understanding of what it could potentially become. In this paper, we conduct an overview of many di...
[ { "created": "Sun, 30 Sep 2018 07:34:20 GMT", "version": "v1" } ]
2018-10-02
[ [ "Lopes", "Vasco", "" ], [ "Alexandre", "Luís A.", "" ] ]
Blockchain technology is growing everyday at a fast-passed rhythm and it's possible to integrate it with many systems, namely Robotics with AI services. However, this is still a recent field and there isn't yet a clear understanding of what it could potentially become. In this paper, we conduct an overview of many diff...
2407.03842
Ye Huang
Linlong Fan, Ye Huang, Yanqi Ge, Wen Li, Lixin Duan
Beyond Viewpoint: Robust 3D Object Recognition under Arbitrary Views through Joint Multi-Part Representation
ECCV 2024 camera ready
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Existing view-based methods excel at recognizing 3D objects from predefined viewpoints, but their exploration of recognition under arbitrary views is limited. This is a challenging and realistic setting because each object has different viewpoint positions and quantities, and their poses are not aligned. However, mos...
[ { "created": "Thu, 4 Jul 2024 11:16:47 GMT", "version": "v1" }, { "created": "Wed, 17 Jul 2024 17:52:05 GMT", "version": "v2" } ]
2024-07-18
[ [ "Fan", "Linlong", "" ], [ "Huang", "Ye", "" ], [ "Ge", "Yanqi", "" ], [ "Li", "Wen", "" ], [ "Duan", "Lixin", "" ] ]
Existing view-based methods excel at recognizing 3D objects from predefined viewpoints, but their exploration of recognition under arbitrary views is limited. This is a challenging and realistic setting because each object has different viewpoint positions and quantities, and their poses are not aligned. However, most ...
2306.13843
Shangqing Tong
Shangqing Tong, Hengrong Lan, Liming Nie, Jianwen Luo and Fei Gao
Score-based Generative Models for Photoacoustic Image Reconstruction with Rotation Consistency Constraints
null
null
null
null
cs.CV eess.IV
http://creativecommons.org/licenses/by/4.0/
Photoacoustic tomography (PAT) is a newly emerged imaging modality which enables both high optical contrast and acoustic depth of penetration. Reconstructing images of photoacoustic tomography from limited amount of senser data is among one of the major challenges in photoacoustic imaging. Previous works based on dee...
[ { "created": "Sat, 24 Jun 2023 02:47:03 GMT", "version": "v1" } ]
2023-06-27
[ [ "Tong", "Shangqing", "" ], [ "Lan", "Hengrong", "" ], [ "Nie", "Liming", "" ], [ "Luo", "Jianwen", "" ], [ "Gao", "Fei", "" ] ]
Photoacoustic tomography (PAT) is a newly emerged imaging modality which enables both high optical contrast and acoustic depth of penetration. Reconstructing images of photoacoustic tomography from limited amount of senser data is among one of the major challenges in photoacoustic imaging. Previous works based on deep ...
2312.10076
Bhaskar Mitra
Anna Gausen and Bhaskar Mitra and Si\^an Lindley
A Framework for Exploring the Consequences of AI-Mediated Enterprise Knowledge Access and Identifying Risks to Workers
19 pages, 1 table
null
null
null
cs.CY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Organisations generate vast amounts of information, which has resulted in a long-term research effort into knowledge access systems for enterprise settings. Recent developments in artificial intelligence, in relation to large language models, are poised to have significant impact on knowledge access. This has the pot...
[ { "created": "Fri, 8 Dec 2023 17:05:40 GMT", "version": "v1" }, { "created": "Tue, 30 Apr 2024 12:25:46 GMT", "version": "v2" } ]
2024-05-01
[ [ "Gausen", "Anna", "" ], [ "Mitra", "Bhaskar", "" ], [ "Lindley", "Siân", "" ] ]
Organisations generate vast amounts of information, which has resulted in a long-term research effort into knowledge access systems for enterprise settings. Recent developments in artificial intelligence, in relation to large language models, are poised to have significant impact on knowledge access. This has the poten...
2211.12734
Michael Mislove
Z. Lyu, X. Xie and H. Kou
A note on the category of c-spaces
5 pages
Electronic Notes in Theoretical Informatics and Computer Science, Volume 2 - Proceedings of ISDT 9 (March 21, 2023) entics:10362
10.46298/entics.10362
null
cs.LO math.CT
http://creativecommons.org/licenses/by/4.0/
We prove that the category of c-spaces with continuous maps is not cartesian closed. As a corollary the category of locally finitary compact spaces with continuous maps is also not cartesian closed.
[ { "created": "Wed, 23 Nov 2022 06:55:11 GMT", "version": "v1" }, { "created": "Sat, 18 Mar 2023 15:58:48 GMT", "version": "v2" } ]
2023-06-22
[ [ "Lyu", "Z.", "" ], [ "Xie", "X.", "" ], [ "Kou", "H.", "" ] ]
We prove that the category of c-spaces with continuous maps is not cartesian closed. As a corollary the category of locally finitary compact spaces with continuous maps is also not cartesian closed.
2002.02949
Priyadarshini Panda
Timothy Foldy-Porto, Yeshwanth Venkatesha, and Priyadarshini Panda
Activation Density driven Energy-Efficient Pruning in Training
8 pages, 5 figures, 4 tables (Accepted in ICPR 2020)
null
null
null
cs.LG cs.CV cs.NE stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Neural network pruning with suitable retraining can yield networks with considerably fewer parameters than the original with comparable degrees of accuracy. Typical pruning methods require large, fully trained networks as a starting point from which they perform a time-intensive iterative pruning and retraining proce...
[ { "created": "Fri, 7 Feb 2020 18:34:31 GMT", "version": "v1" }, { "created": "Mon, 12 Oct 2020 12:16:25 GMT", "version": "v2" } ]
2020-10-13
[ [ "Foldy-Porto", "Timothy", "" ], [ "Venkatesha", "Yeshwanth", "" ], [ "Panda", "Priyadarshini", "" ] ]
Neural network pruning with suitable retraining can yield networks with considerably fewer parameters than the original with comparable degrees of accuracy. Typical pruning methods require large, fully trained networks as a starting point from which they perform a time-intensive iterative pruning and retraining procedu...
1810.06667
Yaser Keneshloo
Yaser Keneshloo, Naren Ramakrishnan, Chandan K. Reddy
Deep Transfer Reinforcement Learning for Text Summarization
null
null
null
null
cs.LG cs.CL stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Deep neural networks are data hungry models and thus face difficulties when attempting to train on small text datasets. Transfer learning is a potential solution but their effectiveness in the text domain is not as explored as in areas such as image analysis. In this paper, we study the problem of transfer learning f...
[ { "created": "Mon, 15 Oct 2018 20:26:44 GMT", "version": "v1" }, { "created": "Thu, 24 Jan 2019 20:14:33 GMT", "version": "v2" } ]
2019-01-28
[ [ "Keneshloo", "Yaser", "" ], [ "Ramakrishnan", "Naren", "" ], [ "Reddy", "Chandan K.", "" ] ]
Deep neural networks are data hungry models and thus face difficulties when attempting to train on small text datasets. Transfer learning is a potential solution but their effectiveness in the text domain is not as explored as in areas such as image analysis. In this paper, we study the problem of transfer learning for...
2203.11914
Jayasree Sengupta
Jayasree Sengupta and Sushmita Ruj and Sipra Das Bit
SPRITE: A Scalable Privacy-Preserving and Verifiable Collaborative Learning for Industrial IoT
Accepted for publication at The 22nd IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGrid 2022). 5 figures and 6 tables
null
null
null
cs.CR cs.DC cs.LG
http://creativecommons.org/licenses/by/4.0/
Recently collaborative learning is widely applied to model sensitive data generated in Industrial IoT (IIoT). It enables a large number of devices to collectively train a global model by collaborating with a server while keeping the datasets on their respective premises. However, existing approaches are limited by hi...
[ { "created": "Tue, 22 Mar 2022 17:34:27 GMT", "version": "v1" } ]
2022-03-23
[ [ "Sengupta", "Jayasree", "" ], [ "Ruj", "Sushmita", "" ], [ "Bit", "Sipra Das", "" ] ]
Recently collaborative learning is widely applied to model sensitive data generated in Industrial IoT (IIoT). It enables a large number of devices to collectively train a global model by collaborating with a server while keeping the datasets on their respective premises. However, existing approaches are limited by high...
1702.07501
Jhoirene Clemente
Erlo Robert F. Oquendo, Jhoirene B. Clemente, Jasmine A. Malinao, Henry N. Adorna
Characterizing Classes of Potential Outliers through Traffic Data Set Data Signature 2D nMDS Projection
null
null
null
null
cs.OH
http://creativecommons.org/licenses/by/4.0/
This paper presents a formal method for characterizing the potential outliers from the data signature projection of traffic data set using Non-Metric Multidimensional Scaling (nMDS) visualization. Previous work had only relied on visual inspection and the subjective nature of this technique may derive false and inval...
[ { "created": "Fri, 24 Feb 2017 09:03:00 GMT", "version": "v1" } ]
2017-02-27
[ [ "Oquendo", "Erlo Robert F.", "" ], [ "Clemente", "Jhoirene B.", "" ], [ "Malinao", "Jasmine A.", "" ], [ "Adorna", "Henry N.", "" ] ]
This paper presents a formal method for characterizing the potential outliers from the data signature projection of traffic data set using Non-Metric Multidimensional Scaling (nMDS) visualization. Previous work had only relied on visual inspection and the subjective nature of this technique may derive false and invalid...
1910.10502
Maaike De Boer
Hella Haanstra and Maaike H. T. de Boer
Opinion aspect extraction in Dutch childrens diary entries
null
null
null
null
cs.CL cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Aspect extraction can be used in dialogue systems to understand the topic of opinionated text. Expressing an empathetic reaction to an opinion can strengthen the bond between a human and, for example, a robot. The aim of this study is three-fold: 1. create a new annotated dataset for both aspect extraction and opinio...
[ { "created": "Mon, 21 Oct 2019 09:33:09 GMT", "version": "v1" } ]
2019-10-24
[ [ "Haanstra", "Hella", "" ], [ "de Boer", "Maaike H. T.", "" ] ]
Aspect extraction can be used in dialogue systems to understand the topic of opinionated text. Expressing an empathetic reaction to an opinion can strengthen the bond between a human and, for example, a robot. The aim of this study is three-fold: 1. create a new annotated dataset for both aspect extraction and opinion ...
2309.05090
Sudarshan Sreeram
Sudarshan Sreeram and Bernhard Kainz
Sculpting Efficiency: Pruning Medical Imaging Models for On-Device Inference
Accepted at MedNeurIPS 2023
null
null
null
cs.CV
http://creativecommons.org/licenses/by-sa/4.0/
Leveraging ML advancements to augment healthcare systems can improve patient outcomes. Yet, uninformed engineering decisions in early-stage research inadvertently hinder the feasibility of such solutions for high-throughput, on-device inference, particularly in settings involving legacy hardware and multi-modal gigap...
[ { "created": "Sun, 10 Sep 2023 17:34:14 GMT", "version": "v1" }, { "created": "Thu, 2 Nov 2023 00:15:19 GMT", "version": "v2" } ]
2023-11-03
[ [ "Sreeram", "Sudarshan", "" ], [ "Kainz", "Bernhard", "" ] ]
Leveraging ML advancements to augment healthcare systems can improve patient outcomes. Yet, uninformed engineering decisions in early-stage research inadvertently hinder the feasibility of such solutions for high-throughput, on-device inference, particularly in settings involving legacy hardware and multi-modal gigapix...
2406.19544
Lei Liu
Xiao Yu, Lei Liu, Xing Hu, Jacky Wai Keung, Jin Liu, Xin Xia
Where Are Large Language Models for Code Generation on GitHub?
null
null
null
null
cs.SE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The increasing use of Large Language Models (LLMs) in software development has garnered significant attention from researchers assessing the quality of the code they generate. However, much of the research focuses on controlled datasets such as HumanEval, which fail to adequately represent how developers actually uti...
[ { "created": "Thu, 27 Jun 2024 21:47:27 GMT", "version": "v1" }, { "created": "Sat, 3 Aug 2024 00:40:02 GMT", "version": "v2" } ]
2024-08-06
[ [ "Yu", "Xiao", "" ], [ "Liu", "Lei", "" ], [ "Hu", "Xing", "" ], [ "Keung", "Jacky Wai", "" ], [ "Liu", "Jin", "" ], [ "Xia", "Xin", "" ] ]
The increasing use of Large Language Models (LLMs) in software development has garnered significant attention from researchers assessing the quality of the code they generate. However, much of the research focuses on controlled datasets such as HumanEval, which fail to adequately represent how developers actually utili...
1812.07712
Ye Wang
Ye Wang, Jongmoo Choi, Yueru Chen, Siyang Li, Qin Huang, Kaitai Zhang, Ming-Sui Lee and C.-C. Jay Kuo
Unsupervised Video Object Segmentation with Distractor-Aware Online Adaptation
11 pages, 6 figures, 4 tables, conference
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Unsupervised video object segmentation is a crucial application in video analysis without knowing any prior information about the objects. It becomes tremendously challenging when multiple objects occur and interact in a given video clip. In this paper, a novel unsupervised video object segmentation approach via dist...
[ { "created": "Wed, 19 Dec 2018 00:45:10 GMT", "version": "v1" } ]
2018-12-20
[ [ "Wang", "Ye", "" ], [ "Choi", "Jongmoo", "" ], [ "Chen", "Yueru", "" ], [ "Li", "Siyang", "" ], [ "Huang", "Qin", "" ], [ "Zhang", "Kaitai", "" ], [ "Lee", "Ming-Sui", "" ], [ "Kuo", "C. -C. Jay...
Unsupervised video object segmentation is a crucial application in video analysis without knowing any prior information about the objects. It becomes tremendously challenging when multiple objects occur and interact in a given video clip. In this paper, a novel unsupervised video object segmentation approach via distra...
2208.12595
Arne Gevaert
Arne Gevaert, Yvan Saeys
PDD-SHAP: Fast Approximations for Shapley Values using Functional Decomposition
null
null
null
null
cs.LG
http://creativecommons.org/licenses/by/4.0/
Because of their strong theoretical properties, Shapley values have become very popular as a way to explain predictions made by black box models. Unfortuately, most existing techniques to compute Shapley values are computationally very expensive. We propose PDD-SHAP, an algorithm that uses an ANOVA-based functional d...
[ { "created": "Fri, 26 Aug 2022 11:49:54 GMT", "version": "v1" } ]
2022-08-29
[ [ "Gevaert", "Arne", "" ], [ "Saeys", "Yvan", "" ] ]
Because of their strong theoretical properties, Shapley values have become very popular as a way to explain predictions made by black box models. Unfortuately, most existing techniques to compute Shapley values are computationally very expensive. We propose PDD-SHAP, an algorithm that uses an ANOVA-based functional dec...
1809.10598
Jaemin Lee
Jaemin Lee, Efstathios Bakolas, Luis Sentis
Trajectory Generation for Robotic Systems with Contact Force Constraints
8 pages, 6 figures
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper presents a trajectory generation method for contact-constrained robotic systems such as manipulators and legged robots. Contact-constrained systems are affected by the interaction forces between the robot and the environment. In turn, these forces determine and constrain state reachability of the robot par...
[ { "created": "Thu, 27 Sep 2018 16:12:55 GMT", "version": "v1" } ]
2018-09-28
[ [ "Lee", "Jaemin", "" ], [ "Bakolas", "Efstathios", "" ], [ "Sentis", "Luis", "" ] ]
This paper presents a trajectory generation method for contact-constrained robotic systems such as manipulators and legged robots. Contact-constrained systems are affected by the interaction forces between the robot and the environment. In turn, these forces determine and constrain state reachability of the robot parts...
2210.03594
Dylan Sam
Rattana Pukdee, Dylan Sam, Maria-Florina Balcan, Pradeep Ravikumar
Label Propagation with Weak Supervision
ICLR 2023, 26 pages, 2 figures
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Semi-supervised learning and weakly supervised learning are important paradigms that aim to reduce the growing demand for labeled data in current machine learning applications. In this paper, we introduce a novel analysis of the classical label propagation algorithm (LPA) (Zhu & Ghahramani, 2002) that moreover takes ...
[ { "created": "Fri, 7 Oct 2022 14:53:02 GMT", "version": "v1" }, { "created": "Sat, 11 Mar 2023 23:55:42 GMT", "version": "v2" }, { "created": "Sun, 9 Apr 2023 20:51:43 GMT", "version": "v3" } ]
2023-04-11
[ [ "Pukdee", "Rattana", "" ], [ "Sam", "Dylan", "" ], [ "Balcan", "Maria-Florina", "" ], [ "Ravikumar", "Pradeep", "" ] ]
Semi-supervised learning and weakly supervised learning are important paradigms that aim to reduce the growing demand for labeled data in current machine learning applications. In this paper, we introduce a novel analysis of the classical label propagation algorithm (LPA) (Zhu & Ghahramani, 2002) that moreover takes ad...
1912.08530
Alexander Willner
Andrea Hamm, Alexander Willner, Ina Schieferdecker
Edge Computing: A Comprehensive Survey of Current Initiatives and a Roadmap for a Sustainable Edge Computing Development
15 pages
15th International Conference on Wirtschaftsinformatik (2020)
null
null
cs.DC eess.SP
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Edge Computing is a new distributed Cloud Computing paradigm in which computing and storage capabilities are pushed to the topological edge of a network. However, various standards and implementations are promoted by different initiatives. Lead by a reference architecture model for Edge Computing, current initiatives...
[ { "created": "Wed, 18 Dec 2019 11:26:22 GMT", "version": "v1" } ]
2020-01-13
[ [ "Hamm", "Andrea", "" ], [ "Willner", "Alexander", "" ], [ "Schieferdecker", "Ina", "" ] ]
Edge Computing is a new distributed Cloud Computing paradigm in which computing and storage capabilities are pushed to the topological edge of a network. However, various standards and implementations are promoted by different initiatives. Lead by a reference architecture model for Edge Computing, current initiatives a...
cs/0104002
Judith Beumer
Sudharshan Vazhkudai, Steven Tuecke, and Ian Foster
Replica Selection in the Globus Data Grid
8 pages, 6 figures
null
null
ANL/MCS-P869-0201
cs.DC
null
The Globus Data Grid architecture provides a scalable infrastructure for the management of storage resources and data that are distributed across Grid environments. These services are designed to support a variety of scientific applications, ranging from high-energy physics to computational genomics, that require acc...
[ { "created": "Mon, 2 Apr 2001 18:19:06 GMT", "version": "v1" } ]
2007-05-23
[ [ "Vazhkudai", "Sudharshan", "" ], [ "Tuecke", "Steven", "" ], [ "Foster", "Ian", "" ] ]
The Globus Data Grid architecture provides a scalable infrastructure for the management of storage resources and data that are distributed across Grid environments. These services are designed to support a variety of scientific applications, ranging from high-energy physics to computational genomics, that require acces...
2010.02825
Lois Orosa
Leonid Yavits, Lois Orosa, Suyash Mahar, Jo\~ao Dinis Ferreira, Mattan Erez, Ran Ginosar, Onur Mutlu
WoLFRaM: Enhancing Wear-Leveling and Fault Tolerance in Resistive Memories using Programmable Address Decoders
To appear in ICCD 2020
null
null
null
cs.AR cs.ET
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Resistive memories have limited lifetime caused by limited write endurance and highly non-uniform write access patterns. Two main techniques to mitigate endurance-related memory failures are 1) wear-leveling, to evenly distribute the writes across the entire memory, and 2) fault tolerance, to correct memory cell fail...
[ { "created": "Tue, 6 Oct 2020 15:38:56 GMT", "version": "v1" } ]
2020-10-07
[ [ "Yavits", "Leonid", "" ], [ "Orosa", "Lois", "" ], [ "Mahar", "Suyash", "" ], [ "Ferreira", "João Dinis", "" ], [ "Erez", "Mattan", "" ], [ "Ginosar", "Ran", "" ], [ "Mutlu", "Onur", "" ] ]
Resistive memories have limited lifetime caused by limited write endurance and highly non-uniform write access patterns. Two main techniques to mitigate endurance-related memory failures are 1) wear-leveling, to evenly distribute the writes across the entire memory, and 2) fault tolerance, to correct memory cell failur...
2212.00115
Seth Karten
Seth Karten, Mycal Tucker, Siva Kailas, Katia Sycara
Towards True Lossless Sparse Communication in Multi-Agent Systems
12 pages, 6 figures
null
null
null
cs.LG cs.MA
http://creativecommons.org/licenses/by/4.0/
Communication enables agents to cooperate to achieve their goals. Learning when to communicate, i.e., sparse (in time) communication, and whom to message is particularly important when bandwidth is limited. Recent work in learning sparse individualized communication, however, suffers from high variance during trainin...
[ { "created": "Wed, 30 Nov 2022 20:43:34 GMT", "version": "v1" } ]
2022-12-02
[ [ "Karten", "Seth", "" ], [ "Tucker", "Mycal", "" ], [ "Kailas", "Siva", "" ], [ "Sycara", "Katia", "" ] ]
Communication enables agents to cooperate to achieve their goals. Learning when to communicate, i.e., sparse (in time) communication, and whom to message is particularly important when bandwidth is limited. Recent work in learning sparse individualized communication, however, suffers from high variance during training,...
1005.5613
Secretary Aircc Journal
Murtaza Ali Khan (Royal University for Women, Bahrain)
An Automated Algorithm for Approximation of Temporal Video Data Using Linear B'EZIER Fitting
14 Pages, IJMA 2010
International journal of Multimedia & Its Applications 2.2 (2010) 81-94
10.5121/ijma.2010.2207
null
cs.MM
http://creativecommons.org/licenses/by-nc-sa/3.0/
This paper presents an efficient method for approximation of temporal video data using linear Bezier fitting. For a given sequence of frames, the proposed method estimates the intensity variations of each pixel in temporal dimension using linear Bezier fitting in Euclidean space. Fitting of each segment ensures upper...
[ { "created": "Mon, 31 May 2010 08:11:59 GMT", "version": "v1" } ]
2010-07-15
[ [ "Khan", "Murtaza Ali", "", "Royal University for Women, Bahrain" ] ]
This paper presents an efficient method for approximation of temporal video data using linear Bezier fitting. For a given sequence of frames, the proposed method estimates the intensity variations of each pixel in temporal dimension using linear Bezier fitting in Euclidean space. Fitting of each segment ensures upper b...
2110.10349
Shengheng Liu
Shengheng Liu, Chong Zheng, Yongming Huang, Tony Q. S. Quek
Distributed Reinforcement Learning for Privacy-Preserving Dynamic Edge Caching
15 pages, 9 figures, under review with the IEEE Journal on Selected Areas in Communications
null
10.1109/JSAC.2022.3142348
null
cs.LG cs.AI cs.CR cs.MM
http://creativecommons.org/licenses/by/4.0/
Mobile edge computing (MEC) is a prominent computing paradigm which expands the application fields of wireless communication. Due to the limitation of the capacities of user equipments and MEC servers, edge caching (EC) optimization is crucial to the effective utilization of the caching resources in MEC-enabled wirel...
[ { "created": "Wed, 20 Oct 2021 02:48:27 GMT", "version": "v1" }, { "created": "Tue, 2 Nov 2021 03:52:07 GMT", "version": "v2" } ]
2022-07-12
[ [ "Liu", "Shengheng", "" ], [ "Zheng", "Chong", "" ], [ "Huang", "Yongming", "" ], [ "Quek", "Tony Q. S.", "" ] ]
Mobile edge computing (MEC) is a prominent computing paradigm which expands the application fields of wireless communication. Due to the limitation of the capacities of user equipments and MEC servers, edge caching (EC) optimization is crucial to the effective utilization of the caching resources in MEC-enabled wireles...
2102.06366
Sahaj Garg
Sahaj Garg, Anirudh Jain, Joe Lou, Mitchell Nahmias
Confounding Tradeoffs for Neural Network Quantization
null
null
null
null
cs.LG cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Many neural network quantization techniques have been developed to decrease the computational and memory footprint of deep learning. However, these methods are evaluated subject to confounding tradeoffs that may affect inference acceleration or resource complexity in exchange for higher accuracy. In this work, we art...
[ { "created": "Fri, 12 Feb 2021 06:58:08 GMT", "version": "v1" } ]
2021-02-15
[ [ "Garg", "Sahaj", "" ], [ "Jain", "Anirudh", "" ], [ "Lou", "Joe", "" ], [ "Nahmias", "Mitchell", "" ] ]
Many neural network quantization techniques have been developed to decrease the computational and memory footprint of deep learning. However, these methods are evaluated subject to confounding tradeoffs that may affect inference acceleration or resource complexity in exchange for higher accuracy. In this work, we artic...
1610.04988
Atle Rygg
Atle Rygg, Marta Molinas, Chen Zhang and Xu Cai
Coupled and decoupled impedance models compared in power electronics systems
8 pages, 8 figures
null
null
null
cs.SY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper provides a comparative analysis of impedance models for power electronic converters and systems for the purpose of stability investigations. Such models can be divided into either decoupled models or matrix models. A decoupled impedance model is highly appealing since the Single-Input-Single-Output (SISO) ...
[ { "created": "Mon, 17 Oct 2016 07:15:50 GMT", "version": "v1" } ]
2016-10-18
[ [ "Rygg", "Atle", "" ], [ "Molinas", "Marta", "" ], [ "Zhang", "Chen", "" ], [ "Cai", "Xu", "" ] ]
This paper provides a comparative analysis of impedance models for power electronic converters and systems for the purpose of stability investigations. Such models can be divided into either decoupled models or matrix models. A decoupled impedance model is highly appealing since the Single-Input-Single-Output (SISO) st...
1901.02585
Adib Rastegarnia
Douglas Comer, Adib Rastegarnia
Externalization of Packet Processing in Software Defined Networking
4 pages, under review
null
null
null
cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Current SDN controllers aggregate all control plane subsystems into a monolithic program. A controller that follows the aggregated approach defines its own set of programming interfaces and services, making application development dependent on a particular SDN controller and restricting portability of management appl...
[ { "created": "Wed, 9 Jan 2019 02:38:33 GMT", "version": "v1" } ]
2019-01-10
[ [ "Comer", "Douglas", "" ], [ "Rastegarnia", "Adib", "" ] ]
Current SDN controllers aggregate all control plane subsystems into a monolithic program. A controller that follows the aggregated approach defines its own set of programming interfaces and services, making application development dependent on a particular SDN controller and restricting portability of management applic...
2108.05914
V. Arvind
Vikraman Arvind and Venkatesan Guruswami
CNF Satisfiability in a Subspace and Related Problems
null
null
null
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We introduce the problem of finding a satisfying assignment to a CNF formula that must further belong to a prescribed input subspace. Equivalent formulations of the problem include finding a point outside a union of subspaces (the Union-of-Subspace Avoidance (USA) problem), and finding a common zero of a system of po...
[ { "created": "Thu, 12 Aug 2021 18:32:38 GMT", "version": "v1" } ]
2021-08-16
[ [ "Arvind", "Vikraman", "" ], [ "Guruswami", "Venkatesan", "" ] ]
We introduce the problem of finding a satisfying assignment to a CNF formula that must further belong to a prescribed input subspace. Equivalent formulations of the problem include finding a point outside a union of subspaces (the Union-of-Subspace Avoidance (USA) problem), and finding a common zero of a system of poly...
2010.02089
Jiaqi Ma
Jiaqi Ma, Bo Chang, Xuefei Zhang, Qiaozhu Mei
CopulaGNN: Towards Integrating Representational and Correlational Roles of Graphs in Graph Neural Networks
ICLR 2021
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Graph-structured data are ubiquitous. However, graphs encode diverse types of information and thus play different roles in data representation. In this paper, we distinguish the \textit{representational} and the \textit{correlational} roles played by the graphs in node-level prediction tasks, and we investigate how G...
[ { "created": "Mon, 5 Oct 2020 15:20:04 GMT", "version": "v1" }, { "created": "Thu, 18 Mar 2021 21:54:58 GMT", "version": "v2" } ]
2021-03-22
[ [ "Ma", "Jiaqi", "" ], [ "Chang", "Bo", "" ], [ "Zhang", "Xuefei", "" ], [ "Mei", "Qiaozhu", "" ] ]
Graph-structured data are ubiquitous. However, graphs encode diverse types of information and thus play different roles in data representation. In this paper, we distinguish the \textit{representational} and the \textit{correlational} roles played by the graphs in node-level prediction tasks, and we investigate how Gra...
2308.15474
Richard Chen J
Richard J. Chen, Tong Ding, Ming Y. Lu, Drew F. K. Williamson, Guillaume Jaume, Bowen Chen, Andrew Zhang, Daniel Shao, Andrew H. Song, Muhammad Shaban, Mane Williams, Anurag Vaidya, Sharifa Sahai, Lukas Oldenburg, Luca L. Weishaupt, Judy J. Wang, Walt Williams, Long Phi Le, Georg Gerber, Faisal Mahmood
A General-Purpose Self-Supervised Model for Computational Pathology
null
null
null
null
cs.CV cs.AI q-bio.TO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Tissue phenotyping is a fundamental computational pathology (CPath) task in learning objective characterizations of histopathologic biomarkers in anatomic pathology. However, whole-slide imaging (WSI) poses a complex computer vision problem in which the large-scale image resolutions of WSIs and the enormous diversity...
[ { "created": "Tue, 29 Aug 2023 17:52:10 GMT", "version": "v1" } ]
2023-08-30
[ [ "Chen", "Richard J.", "" ], [ "Ding", "Tong", "" ], [ "Lu", "Ming Y.", "" ], [ "Williamson", "Drew F. K.", "" ], [ "Jaume", "Guillaume", "" ], [ "Chen", "Bowen", "" ], [ "Zhang", "Andrew", "" ], [ "...
Tissue phenotyping is a fundamental computational pathology (CPath) task in learning objective characterizations of histopathologic biomarkers in anatomic pathology. However, whole-slide imaging (WSI) poses a complex computer vision problem in which the large-scale image resolutions of WSIs and the enormous diversity o...
1803.03981
Staal Vinterbo PhD
Staal A. Vinterbo
A Simple Algorithm for Estimating Distribution Parameters from $n$-Dimensional Randomized Binary Responses
Accepted at Information Security - 21th International Conference, ISC 2018. Adapted to meet article length requirements. Fixed typo. Results unchanged
null
null
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Randomized response is attractive for privacy preserving data collection because the provided privacy can be quantified by means such as differential privacy. However, recovering and analyzing statistics involving multiple dependent randomized binary attributes can be difficult, posing a significant barrier to use. I...
[ { "created": "Sun, 11 Mar 2018 16:11:43 GMT", "version": "v1" }, { "created": "Tue, 3 Jul 2018 01:29:51 GMT", "version": "v2" }, { "created": "Fri, 13 Jul 2018 15:24:50 GMT", "version": "v3" } ]
2018-07-16
[ [ "Vinterbo", "Staal A.", "" ] ]
Randomized response is attractive for privacy preserving data collection because the provided privacy can be quantified by means such as differential privacy. However, recovering and analyzing statistics involving multiple dependent randomized binary attributes can be difficult, posing a significant barrier to use. In ...
1707.07062
Xinyu Hua
Xinyu Hua, Lu Wang
A Pilot Study of Domain Adaptation Effect for Neural Abstractive Summarization
This paper is accepted by EMNLP 2017 Workshop on New Frontiers in Summarization
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We study the problem of domain adaptation for neural abstractive summarization. We make initial efforts in investigating what information can be transferred to a new domain. Experimental results on news stories and opinion articles indicate that neural summarization model benefits from pre-training based on extractiv...
[ { "created": "Fri, 21 Jul 2017 22:42:52 GMT", "version": "v1" } ]
2017-07-25
[ [ "Hua", "Xinyu", "" ], [ "Wang", "Lu", "" ] ]
We study the problem of domain adaptation for neural abstractive summarization. We make initial efforts in investigating what information can be transferred to a new domain. Experimental results on news stories and opinion articles indicate that neural summarization model benefits from pre-training based on extractive ...
1211.5433
Emanuele Giaquinta
Emanuele Giaquinta and Szymon Grabowski and Kimmo Fredriksson
Approximate pattern matching with k-mismatches in packed text
This paper is an extended version of the article that appeared in Information Processing Letters 113(19-21):693-697 (2013), http://dx.doi.org/10.1016/j.ipl.2013.07.002
null
null
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Given strings $P$ of length $m$ and $T$ of length $n$ over an alphabet of size $\sigma$, the string matching with $k$-mismatches problem is to find the positions of all the substrings in $T$ that are at Hamming distance at most $k$ from $P$. If $T$ can be read only one character at the time the best known bounds are ...
[ { "created": "Fri, 23 Nov 2012 08:30:45 GMT", "version": "v1" }, { "created": "Fri, 4 Jan 2013 12:02:24 GMT", "version": "v2" }, { "created": "Wed, 31 Jul 2013 12:45:11 GMT", "version": "v3" } ]
2013-08-01
[ [ "Giaquinta", "Emanuele", "" ], [ "Grabowski", "Szymon", "" ], [ "Fredriksson", "Kimmo", "" ] ]
Given strings $P$ of length $m$ and $T$ of length $n$ over an alphabet of size $\sigma$, the string matching with $k$-mismatches problem is to find the positions of all the substrings in $T$ that are at Hamming distance at most $k$ from $P$. If $T$ can be read only one character at the time the best known bounds are $O...
2405.16112
Shaokui Wei
Shaokui Wei, Hongyuan Zha, Baoyuan Wu
Mitigating Backdoor Attack by Injecting Proactive Defensive Backdoor
13 pages, 5 figures and 5 tables
null
null
null
cs.CR cs.CV
http://creativecommons.org/licenses/by-nc-nd/4.0/
Data-poisoning backdoor attacks are serious security threats to machine learning models, where an adversary can manipulate the training dataset to inject backdoors into models. In this paper, we focus on in-training backdoor defense, aiming to train a clean model even when the dataset may be potentially poisoned. Unl...
[ { "created": "Sat, 25 May 2024 07:52:26 GMT", "version": "v1" } ]
2024-05-28
[ [ "Wei", "Shaokui", "" ], [ "Zha", "Hongyuan", "" ], [ "Wu", "Baoyuan", "" ] ]
Data-poisoning backdoor attacks are serious security threats to machine learning models, where an adversary can manipulate the training dataset to inject backdoors into models. In this paper, we focus on in-training backdoor defense, aiming to train a clean model even when the dataset may be potentially poisoned. Unlik...
1109.6794
Miguel Goul\~ao
Pedro Gabriel, Miguel Goul\~ao, and Vasco Amaral
Do Software Languages Engineers Evaluate their Languages?
null
Proceedings of the XIII Congreso Iberoamericano en "Software Engineering" (CIbSE'2010), Universidad del Azuay, ISBN-978-9978-325-10-0, Cuenca, Ecuador, April 2010
null
null
cs.SE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Domain Specific Languages (DSLs) can contribute to increment productivity, while reducing the required maintenance and programming expertise. We hypothesize that Software Languages Engineering (SLE) developers consistently skip, or relax, Language Evaluation. Based on the experience of engineering other types of soft...
[ { "created": "Fri, 30 Sep 2011 11:25:41 GMT", "version": "v1" } ]
2016-11-25
[ [ "Gabriel", "Pedro", "" ], [ "Goulão", "Miguel", "" ], [ "Amaral", "Vasco", "" ] ]
Domain Specific Languages (DSLs) can contribute to increment productivity, while reducing the required maintenance and programming expertise. We hypothesize that Software Languages Engineering (SLE) developers consistently skip, or relax, Language Evaluation. Based on the experience of engineering other types of softwa...
2305.19500
Yulin Chen
Yulin Chen, Ning Ding, Xiaobin Wang, Shengding Hu, Hai-Tao Zheng, Zhiyuan Liu, Pengjun Xie
Exploring Lottery Prompts for Pre-trained Language Models
Accepted to ACL 2023
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Consistently scaling pre-trained language models (PLMs) imposes substantial burdens on model adaptation, necessitating more efficient alternatives to conventional fine-tuning. Given the advantage of prompting in the zero-shot setting and the observed performance fluctuation among different prompts, we explore the ins...
[ { "created": "Wed, 31 May 2023 02:17:04 GMT", "version": "v1" } ]
2023-06-01
[ [ "Chen", "Yulin", "" ], [ "Ding", "Ning", "" ], [ "Wang", "Xiaobin", "" ], [ "Hu", "Shengding", "" ], [ "Zheng", "Hai-Tao", "" ], [ "Liu", "Zhiyuan", "" ], [ "Xie", "Pengjun", "" ] ]
Consistently scaling pre-trained language models (PLMs) imposes substantial burdens on model adaptation, necessitating more efficient alternatives to conventional fine-tuning. Given the advantage of prompting in the zero-shot setting and the observed performance fluctuation among different prompts, we explore the insta...
1904.01543
Christopher Morris
Christopher Morris, Gaurav Rattan, Petra Mutzel
Weisfeiler and Leman go sparse: Towards scalable higher-order graph embeddings
Accepted at NeurIPS 2020, extented version with proofs
null
null
null
cs.DS cs.DM stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Graph kernels based on the $1$-dimensional Weisfeiler-Leman algorithm and corresponding neural architectures recently emerged as powerful tools for (supervised) learning with graphs. However, due to the purely local nature of the algorithms, they might miss essential patterns in the given data and can only handle bin...
[ { "created": "Tue, 2 Apr 2019 16:59:19 GMT", "version": "v1" }, { "created": "Wed, 14 Aug 2019 17:23:50 GMT", "version": "v2" }, { "created": "Mon, 19 Oct 2020 15:54:46 GMT", "version": "v3" } ]
2020-10-20
[ [ "Morris", "Christopher", "" ], [ "Rattan", "Gaurav", "" ], [ "Mutzel", "Petra", "" ] ]
Graph kernels based on the $1$-dimensional Weisfeiler-Leman algorithm and corresponding neural architectures recently emerged as powerful tools for (supervised) learning with graphs. However, due to the purely local nature of the algorithms, they might miss essential patterns in the given data and can only handle binar...
2104.14556
Zhiheng Li
Zhiheng Li, Chenliang Xu
Discover the Unknown Biased Attribute of an Image Classifier
ICCV 2021
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Recent works find that AI algorithms learn biases from data. Therefore, it is urgent and vital to identify biases in AI algorithms. However, the previous bias identification pipeline overly relies on human experts to conjecture potential biases (e.g., gender), which may neglect other underlying biases not realized by...
[ { "created": "Thu, 29 Apr 2021 17:59:30 GMT", "version": "v1" }, { "created": "Tue, 8 Jun 2021 17:59:55 GMT", "version": "v2" }, { "created": "Sun, 3 Oct 2021 04:20:23 GMT", "version": "v3" } ]
2021-10-05
[ [ "Li", "Zhiheng", "" ], [ "Xu", "Chenliang", "" ] ]
Recent works find that AI algorithms learn biases from data. Therefore, it is urgent and vital to identify biases in AI algorithms. However, the previous bias identification pipeline overly relies on human experts to conjecture potential biases (e.g., gender), which may neglect other underlying biases not realized by h...
2210.10523
Theodor Schnitzler
Theodor Schnitzler, Katharina Kohls, Evangelos Bitsikas, Christina P\"opper
Hope of Delivery: Extracting User Locations From Mobile Instant Messengers
33 pages, 23 figures, 9 tables, NDSS 2023
null
10.14722/ndss.2023.23188
null
cs.CR
http://creativecommons.org/licenses/by/4.0/
Mobile instant messengers such as WhatsApp use delivery status notifications in order to inform users if a sent message has successfully reached its destination. This is useful and important information for the sender due to the often asynchronous use of the messenger service. However, as we demonstrate in this paper...
[ { "created": "Wed, 19 Oct 2022 12:57:47 GMT", "version": "v1" } ]
2022-10-20
[ [ "Schnitzler", "Theodor", "" ], [ "Kohls", "Katharina", "" ], [ "Bitsikas", "Evangelos", "" ], [ "Pöpper", "Christina", "" ] ]
Mobile instant messengers such as WhatsApp use delivery status notifications in order to inform users if a sent message has successfully reached its destination. This is useful and important information for the sender due to the often asynchronous use of the messenger service. However, as we demonstrate in this paper, ...
2110.13484
Tianxu Li
Tianxu Li, Kun Zhu, Nguyen Cong Luong, Dusit Niyato, Qihui Wu, Yang Zhang, Bing Chen
Applications of Multi-Agent Reinforcement Learning in Future Internet: A Comprehensive Survey
null
null
null
null
cs.AI cs.LG cs.MA
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Future Internet involves several emerging technologies such as 5G and beyond 5G networks, vehicular networks, unmanned aerial vehicle (UAV) networks, and Internet of Things (IoTs). Moreover, future Internet becomes heterogeneous and decentralized with a large number of involved network entities. Each entity may need ...
[ { "created": "Tue, 26 Oct 2021 08:26:55 GMT", "version": "v1" }, { "created": "Mon, 7 Mar 2022 07:55:43 GMT", "version": "v2" }, { "created": "Sat, 10 Sep 2022 02:51:49 GMT", "version": "v3" } ]
2022-09-13
[ [ "Li", "Tianxu", "" ], [ "Zhu", "Kun", "" ], [ "Luong", "Nguyen Cong", "" ], [ "Niyato", "Dusit", "" ], [ "Wu", "Qihui", "" ], [ "Zhang", "Yang", "" ], [ "Chen", "Bing", "" ] ]
Future Internet involves several emerging technologies such as 5G and beyond 5G networks, vehicular networks, unmanned aerial vehicle (UAV) networks, and Internet of Things (IoTs). Moreover, future Internet becomes heterogeneous and decentralized with a large number of involved network entities. Each entity may need to...
1912.01116
Jeremy Gordon
Jeremy Gordon, David Rawlinson, Subutai Ahmad
Long Distance Relationships without Time Travel: Boosting the Performance of a Sparse Predictive Autoencoder in Sequence Modeling
9 pages, 6 figures, 4 tables
null
null
null
cs.LG cs.CL cs.NE stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In sequence learning tasks such as language modelling, Recurrent Neural Networks must learn relationships between input features separated by time. State of the art models such as LSTM and Transformer are trained by backpropagation of losses into prior hidden states and inputs held in memory. This allows gradients to...
[ { "created": "Mon, 2 Dec 2019 23:00:13 GMT", "version": "v1" } ]
2019-12-04
[ [ "Gordon", "Jeremy", "" ], [ "Rawlinson", "David", "" ], [ "Ahmad", "Subutai", "" ] ]
In sequence learning tasks such as language modelling, Recurrent Neural Networks must learn relationships between input features separated by time. State of the art models such as LSTM and Transformer are trained by backpropagation of losses into prior hidden states and inputs held in memory. This allows gradients to f...
1706.08211
Seong-Gyun Jeong
Seong-Gyun Jeong, Jiwon Kim, Sujung Kim, Jaesik Min
End-to-end Learning of Image based Lane-Change Decision
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We propose an image based end-to-end learning framework that helps lane-change decisions for human drivers and autonomous vehicles. The proposed system, Safe Lane-Change Aid Network (SLCAN), trains a deep convolutional neural network to classify the status of adjacent lanes from rear view images acquired by cameras m...
[ { "created": "Mon, 26 Jun 2017 02:59:56 GMT", "version": "v1" } ]
2017-06-27
[ [ "Jeong", "Seong-Gyun", "" ], [ "Kim", "Jiwon", "" ], [ "Kim", "Sujung", "" ], [ "Min", "Jaesik", "" ] ]
We propose an image based end-to-end learning framework that helps lane-change decisions for human drivers and autonomous vehicles. The proposed system, Safe Lane-Change Aid Network (SLCAN), trains a deep convolutional neural network to classify the status of adjacent lanes from rear view images acquired by cameras mou...
1402.6880
Mark Keane
M.T. Keane and A. Gerow
It's distributions all the way down!: Second order changes in statistical distributions also occur
null
Behavioral & Brain Sciences, 2014, 37(1), 87
10.1017/S0140525X13001763
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The textual, big-data literature misses Bentley, OBrien, & Brocks (Bentley et als) message on distributions; it largely examines the first-order effects of how a single, signature distribution can predict population behaviour, neglecting second-order effects involving distributional shifts, either between signature d...
[ { "created": "Thu, 27 Feb 2014 12:12:11 GMT", "version": "v1" } ]
2019-08-19
[ [ "Keane", "M. T.", "" ], [ "Gerow", "A.", "" ] ]
The textual, big-data literature misses Bentley, OBrien, & Brocks (Bentley et als) message on distributions; it largely examines the first-order effects of how a single, signature distribution can predict population behaviour, neglecting second-order effects involving distributional shifts, either between signature dis...
2103.04886
George Dasoulas
George Dasoulas, Kevin Scaman, Aladin Virmaux
Lipschitz Normalization for Self-Attention Layers with Application to Graph Neural Networks
18 pages. Proceedings of the 38th International Conference on Machine Learning, PMLR 139, 2021. Copyright 2021 by the author(s)
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Attention based neural networks are state of the art in a large range of applications. However, their performance tends to degrade when the number of layers increases. In this work, we show that enforcing Lipschitz continuity by normalizing the attention scores can significantly improve the performance of deep attent...
[ { "created": "Mon, 8 Mar 2021 16:47:16 GMT", "version": "v1" }, { "created": "Wed, 12 May 2021 23:46:25 GMT", "version": "v2" }, { "created": "Mon, 13 Sep 2021 14:38:02 GMT", "version": "v3" } ]
2021-09-14
[ [ "Dasoulas", "George", "" ], [ "Scaman", "Kevin", "" ], [ "Virmaux", "Aladin", "" ] ]
Attention based neural networks are state of the art in a large range of applications. However, their performance tends to degrade when the number of layers increases. In this work, we show that enforcing Lipschitz continuity by normalizing the attention scores can significantly improve the performance of deep attentio...
2406.05761
Seungone Kim
Seungone Kim, Juyoung Suk, Ji Yong Cho, Shayne Longpre, Chaeeun Kim, Dongkeun Yoon, Guijin Son, Yejin Cho, Sheikh Shafayat, Jinheon Baek, Sue Hyun Park, Hyeonbin Hwang, Jinkyung Jo, Hyowon Cho, Haebin Shin, Seongyun Lee, Hanseok Oh, Noah Lee, Namgyu Ho, Se June Joo, Miyoung Ko, Yoonjoo Lee, Hyungjoo Chae, Jamin...
The BiGGen Bench: A Principled Benchmark for Fine-grained Evaluation of Language Models with Language Models
Work in Progress
null
null
null
cs.CL
http://creativecommons.org/licenses/by-nc-nd/4.0/
As language models (LMs) become capable of handling a wide range of tasks, their evaluation is becoming as challenging as their development. Most generation benchmarks currently assess LMs using abstract evaluation criteria like helpfulness and harmlessness, which often lack the flexibility and granularity of human a...
[ { "created": "Sun, 9 Jun 2024 12:30:30 GMT", "version": "v1" } ]
2024-06-11
[ [ "Kim", "Seungone", "" ], [ "Suk", "Juyoung", "" ], [ "Cho", "Ji Yong", "" ], [ "Longpre", "Shayne", "" ], [ "Kim", "Chaeeun", "" ], [ "Yoon", "Dongkeun", "" ], [ "Son", "Guijin", "" ], [ "Cho", ...
As language models (LMs) become capable of handling a wide range of tasks, their evaluation is becoming as challenging as their development. Most generation benchmarks currently assess LMs using abstract evaluation criteria like helpfulness and harmlessness, which often lack the flexibility and granularity of human ass...
2203.13040
Mariya Evtimova-Gardair
Mariya Evtimova-Gardair, Tasho Tashev
Semantic system for searching of employees
132-136 pages, 9 figures,International Conference on Applied Physics, Simulation and Computing (APSAC)Croatia, Dubrovnik, Sept.28-29 2018
International Journal of Economics and Management Systems, ISSN:2367-8925, Vol.3,2018, p.132-136
null
ISSN: 2367-8925
cs.IR cs.CY
http://creativecommons.org/licenses/by-nc-nd/4.0/
Many people have stress to leave their job and start a new one because of the new environment and not enough knowledge about the culture and structure about the new organization they are going to work in. New employees in company normally need to integrate in their working place environment quicker to start doing the...
[ { "created": "Thu, 24 Mar 2022 12:41:04 GMT", "version": "v1" } ]
2022-03-28
[ [ "Evtimova-Gardair", "Mariya", "" ], [ "Tashev", "Tasho", "" ] ]
Many people have stress to leave their job and start a new one because of the new environment and not enough knowledge about the culture and structure about the new organization they are going to work in. New employees in company normally need to integrate in their working place environment quicker to start doing their...
2407.06738
Jonas Spenger
Aleksey Veresov (1), Jonas Spenger (1), Paris Carbone (1 and 2), Philipp Haller (1) ((1) KTH Royal Institute of Technology, (2) RISE Research Institutes of Sweden)
Failure Transparency in Stateful Dataflow Systems (Technical Report)
26 pages, 12 figures, 44 pages including references and appendix with proofs, technical report, ECOOP 2024
null
null
null
cs.PL cs.DC
http://creativecommons.org/licenses/by/4.0/
Failure transparency enables users to reason about distributed systems at a higher level of abstraction, where complex failure-handling logic is hidden. This is especially true for stateful dataflow systems, which are the backbone of many cloud applications. In particular, this paper focuses on proving failure transp...
[ { "created": "Tue, 9 Jul 2024 10:32:26 GMT", "version": "v1" } ]
2024-07-10
[ [ "Veresov", "Aleksey", "", "1 and 2" ], [ "Spenger", "Jonas", "", "1 and 2" ], [ "Carbone", "Paris", "", "1 and 2" ], [ "Haller", "Philipp", "" ] ]
Failure transparency enables users to reason about distributed systems at a higher level of abstraction, where complex failure-handling logic is hidden. This is especially true for stateful dataflow systems, which are the backbone of many cloud applications. In particular, this paper focuses on proving failure transpar...
cs/9911008
John Watrous
John Watrous (University of Calgary)
On quantum and classical space-bounded processes with algebraic transition amplitudes
18 pages. Appears in FOCS '99
null
null
null
cs.CC quant-ph
null
We define a class of stochastic processes based on evolutions and measurements of quantum systems, and consider the complexity of predicting their long-term behavior. It is shown that a very general class of decision problems regarding these stochastic processes can be efficiently solved classically in the space-boun...
[ { "created": "Tue, 16 Nov 1999 21:55:07 GMT", "version": "v1" } ]
2007-05-23
[ [ "Watrous", "John", "", "University of Calgary" ] ]
We define a class of stochastic processes based on evolutions and measurements of quantum systems, and consider the complexity of predicting their long-term behavior. It is shown that a very general class of decision problems regarding these stochastic processes can be efficiently solved classically in the space-bounde...
2001.08439
Johan Kwisthout
Johan Kwisthout, Nils Donselaar
On the computational power and complexity of Spiking Neural Networks
null
null
null
null
cs.CC cs.NE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The last decade has seen the rise of neuromorphic architectures based on artificial spiking neural networks, such as the SpiNNaker, TrueNorth, and Loihi systems. The massive parallelism and co-locating of computation and memory in these architectures potentially allows for an energy usage that is orders of magnitude ...
[ { "created": "Thu, 23 Jan 2020 10:40:16 GMT", "version": "v1" } ]
2020-01-24
[ [ "Kwisthout", "Johan", "" ], [ "Donselaar", "Nils", "" ] ]
The last decade has seen the rise of neuromorphic architectures based on artificial spiking neural networks, such as the SpiNNaker, TrueNorth, and Loihi systems. The massive parallelism and co-locating of computation and memory in these architectures potentially allows for an energy usage that is orders of magnitude lo...
2407.02466
Ignat Georgiev
Ignat Georgiev, Varun Giridhar, Nicklas Hansen and Animesh Garg
PWM: Policy Learning with Large World Models
Visualizations and code available at https://www.imgeorgiev.com/pwm
null
null
null
cs.LG cs.AI cs.RO
http://creativecommons.org/licenses/by/4.0/
Reinforcement Learning (RL) has achieved impressive results on complex tasks but struggles in multi-task settings with different embodiments. World models offer scalability by learning a simulation of the environment, yet they often rely on inefficient gradient-free optimization methods. We introduce Policy learning ...
[ { "created": "Tue, 2 Jul 2024 17:47:03 GMT", "version": "v1" }, { "created": "Wed, 3 Jul 2024 13:24:02 GMT", "version": "v2" } ]
2024-07-04
[ [ "Georgiev", "Ignat", "" ], [ "Giridhar", "Varun", "" ], [ "Hansen", "Nicklas", "" ], [ "Garg", "Animesh", "" ] ]
Reinforcement Learning (RL) has achieved impressive results on complex tasks but struggles in multi-task settings with different embodiments. World models offer scalability by learning a simulation of the environment, yet they often rely on inefficient gradient-free optimization methods. We introduce Policy learning wi...
2302.05519
Tarik A. Rashid
Jaza M. Abdullah, Tarik A. Rashid, Bestan B. Maaroof, Seyedali Mirjalili
Multi objective Fitness Dependent Optimizer Algorithm
29 pages
null
null
null
cs.NE
http://creativecommons.org/licenses/by/4.0/
This paper proposes the multi objective variant of the recently introduced fitness dependent optimizer (FDO). The algorithm is called a Multi objective Fitness Dependent Optimizer (MOFDO) and is equipped with all five types of knowledge (situational, normative, topographical, domain, and historical knowledge) as in F...
[ { "created": "Thu, 26 Jan 2023 06:33:53 GMT", "version": "v1" } ]
2023-02-14
[ [ "Abdullah", "Jaza M.", "" ], [ "Rashid", "Tarik A.", "" ], [ "Maaroof", "Bestan B.", "" ], [ "Mirjalili", "Seyedali", "" ] ]
This paper proposes the multi objective variant of the recently introduced fitness dependent optimizer (FDO). The algorithm is called a Multi objective Fitness Dependent Optimizer (MOFDO) and is equipped with all five types of knowledge (situational, normative, topographical, domain, and historical knowledge) as in FDO...
2309.08365
Yao Yuan
Yao Yuan, Pan Gao, XiaoYang Tan
M$^3$Net: Multilevel, Mixed and Multistage Attention Network for Salient Object Detection
null
null
null
null
cs.CV cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Most existing salient object detection methods mostly use U-Net or feature pyramid structure, which simply aggregates feature maps of different scales, ignoring the uniqueness and interdependence of them and their respective contributions to the final prediction. To overcome these, we propose the M$^3$Net, i.e., the ...
[ { "created": "Fri, 15 Sep 2023 12:46:14 GMT", "version": "v1" } ]
2023-09-18
[ [ "Yuan", "Yao", "" ], [ "Gao", "Pan", "" ], [ "Tan", "XiaoYang", "" ] ]
Most existing salient object detection methods mostly use U-Net or feature pyramid structure, which simply aggregates feature maps of different scales, ignoring the uniqueness and interdependence of them and their respective contributions to the final prediction. To overcome these, we propose the M$^3$Net, i.e., the Mu...
1809.00961
Ram Krishna Pandey
Ram Krishna Pandey, Nabagata Saha, Samarjit Karmakar, A G Ramakrishnan
MSCE: An edge preserving robust loss function for improving super-resolution algorithms
Accepted in ICONIP-2018
null
null
null
cs.CV cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
With the recent advancement in the deep learning technologies such as CNNs and GANs, there is significant improvement in the quality of the images reconstructed by deep learning based super-resolution (SR) techniques. In this work, we propose a robust loss function based on the preservation of edges obtained by the C...
[ { "created": "Sat, 25 Aug 2018 22:00:10 GMT", "version": "v1" } ]
2018-09-05
[ [ "Pandey", "Ram Krishna", "" ], [ "Saha", "Nabagata", "" ], [ "Karmakar", "Samarjit", "" ], [ "Ramakrishnan", "A G", "" ] ]
With the recent advancement in the deep learning technologies such as CNNs and GANs, there is significant improvement in the quality of the images reconstructed by deep learning based super-resolution (SR) techniques. In this work, we propose a robust loss function based on the preservation of edges obtained by the Can...
2211.14090
Miaoyu Li
Miaoyu Li, Ying Fu, Yulun Zhang
Spatial-Spectral Transformer for Hyperspectral Image Denoising
null
null
null
null
cs.CV eess.IV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Hyperspectral image (HSI) denoising is a crucial preprocessing procedure for the subsequent HSI applications. Unfortunately, though witnessing the development of deep learning in HSI denoising area, existing convolution-based methods face the trade-off between computational efficiency and capability to model non-loca...
[ { "created": "Fri, 25 Nov 2022 13:18:45 GMT", "version": "v1" } ]
2022-11-28
[ [ "Li", "Miaoyu", "" ], [ "Fu", "Ying", "" ], [ "Zhang", "Yulun", "" ] ]
Hyperspectral image (HSI) denoising is a crucial preprocessing procedure for the subsequent HSI applications. Unfortunately, though witnessing the development of deep learning in HSI denoising area, existing convolution-based methods face the trade-off between computational efficiency and capability to model non-local ...
1709.03683
Yan Zhao
Yan Zhao, Xiao Fang, David Simchi-Levi
A Practically Competitive and Provably Consistent Algorithm for Uplift Modeling
Accepted by 2017 IEEE International Conference on Data Mining
null
null
null
cs.LG cs.AI stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Randomized experiments have been critical tools of decision making for decades. However, subjects can show significant heterogeneity in response to treatments in many important applications. Therefore it is not enough to simply know which treatment is optimal for the entire population. What we need is a model that co...
[ { "created": "Tue, 12 Sep 2017 03:49:57 GMT", "version": "v1" } ]
2017-09-13
[ [ "Zhao", "Yan", "" ], [ "Fang", "Xiao", "" ], [ "Simchi-Levi", "David", "" ] ]
Randomized experiments have been critical tools of decision making for decades. However, subjects can show significant heterogeneity in response to treatments in many important applications. Therefore it is not enough to simply know which treatment is optimal for the entire population. What we need is a model that corr...
1805.06066
Alexander Toshev
Arsalan Mousavian, Alexander Toshev, Marek Fiser, Jana Kosecka, Ayzaan Wahid, James Davidson
Visual Representations for Semantic Target Driven Navigation
Accepted to ICRA 2019 and ECCV 2018 Workshop on Visual Learning and Embodied Agents in Simulation Environments
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
What is a good visual representation for autonomous agents? We address this question in the context of semantic visual navigation, which is the problem of a robot finding its way through a complex environment to a target object, e.g. go to the refrigerator. Instead of acquiring a metric semantic map of an environment...
[ { "created": "Tue, 15 May 2018 23:26:52 GMT", "version": "v1" }, { "created": "Sun, 10 Mar 2019 00:49:41 GMT", "version": "v2" }, { "created": "Tue, 2 Jul 2019 18:05:37 GMT", "version": "v3" } ]
2019-07-04
[ [ "Mousavian", "Arsalan", "" ], [ "Toshev", "Alexander", "" ], [ "Fiser", "Marek", "" ], [ "Kosecka", "Jana", "" ], [ "Wahid", "Ayzaan", "" ], [ "Davidson", "James", "" ] ]
What is a good visual representation for autonomous agents? We address this question in the context of semantic visual navigation, which is the problem of a robot finding its way through a complex environment to a target object, e.g. go to the refrigerator. Instead of acquiring a metric semantic map of an environment a...
1901.09388
Yun Ma
Yun Ma, Dongwei Xiang, Shuyu Zheng, Deyu Tian, Xuanzhe Liu
Moving Deep Learning into Web Browser: How Far Can We Go?
null
null
null
null
cs.SE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recently, several JavaScript-based deep learning frameworks have emerged, making it possible to perform deep learning tasks directly in browsers. However, little is known on what and how well we can do with these frameworks for deep learning in browsers. To bridge the knowledge gap, in this paper, we conduct the firs...
[ { "created": "Sun, 27 Jan 2019 14:54:51 GMT", "version": "v1" }, { "created": "Sun, 24 Mar 2019 06:44:08 GMT", "version": "v2" } ]
2019-03-26
[ [ "Ma", "Yun", "" ], [ "Xiang", "Dongwei", "" ], [ "Zheng", "Shuyu", "" ], [ "Tian", "Deyu", "" ], [ "Liu", "Xuanzhe", "" ] ]
Recently, several JavaScript-based deep learning frameworks have emerged, making it possible to perform deep learning tasks directly in browsers. However, little is known on what and how well we can do with these frameworks for deep learning in browsers. To bridge the knowledge gap, in this paper, we conduct the first ...