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1711.02860
Kasper Green Larsen
Kasper Green Larsen
Constructive Discrepancy Minimization with Hereditary L2 Guarantees
null
null
null
null
cs.DS cs.DM math.CO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In discrepancy minimization problems, we are given a family of sets $\mathcal{S} = \{S_1,\dots,S_m\}$, with each $S_i \in \mathcal{S}$ a subset of some universe $U = \{u_1,\dots,u_n\}$ of $n$ elements. The goal is to find a coloring $\chi : U \to \{-1,+1\}$ of the elements of $U$ such that each set $S \in \mathcal{S}...
[ { "created": "Wed, 8 Nov 2017 08:05:42 GMT", "version": "v1" }, { "created": "Tue, 28 Nov 2017 13:48:15 GMT", "version": "v2" }, { "created": "Tue, 19 Jun 2018 09:21:00 GMT", "version": "v3" }, { "created": "Thu, 13 Dec 2018 09:06:01 GMT", "version": "v4" } ]
2018-12-14
[ [ "Larsen", "Kasper Green", "" ] ]
In discrepancy minimization problems, we are given a family of sets $\mathcal{S} = \{S_1,\dots,S_m\}$, with each $S_i \in \mathcal{S}$ a subset of some universe $U = \{u_1,\dots,u_n\}$ of $n$ elements. The goal is to find a coloring $\chi : U \to \{-1,+1\}$ of the elements of $U$ such that each set $S \in \mathcal{S}$ ...
2103.08590
Adrianna Janik
Adrianna Janik, Jonathan Dodd, Georgiana Ifrim, Kris Sankaran, Kathleen Curran
Interpretability of a Deep Learning Model in the Application of Cardiac MRI Segmentation with an ACDC Challenge Dataset
null
null
10.1117/12.2582227
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Cardiac Magnetic Resonance (CMR) is the most effective tool for the assessment and diagnosis of a heart condition, which malfunction is the world's leading cause of death. Software tools leveraging Artificial Intelligence already enhance radiologists and cardiologists in heart condition assessment but their lack of t...
[ { "created": "Mon, 15 Mar 2021 17:57:40 GMT", "version": "v1" } ]
2021-03-16
[ [ "Janik", "Adrianna", "" ], [ "Dodd", "Jonathan", "" ], [ "Ifrim", "Georgiana", "" ], [ "Sankaran", "Kris", "" ], [ "Curran", "Kathleen", "" ] ]
Cardiac Magnetic Resonance (CMR) is the most effective tool for the assessment and diagnosis of a heart condition, which malfunction is the world's leading cause of death. Software tools leveraging Artificial Intelligence already enhance radiologists and cardiologists in heart condition assessment but their lack of tra...
1201.1363
Anisur Molla Rahaman
Atish Das Sarma, Anisur Rahaman Molla and Gopal Pandurangan
Near-Optimal Random Walk Sampling in Distributed Networks
null
null
null
null
cs.DC cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Performing random walks in networks is a fundamental primitive that has found numerous applications in communication networks such as token management, load balancing, network topology discovery and construction, search, and peer-to-peer membership management. While several such algorithms are ubiquitous, and use num...
[ { "created": "Fri, 6 Jan 2012 08:16:45 GMT", "version": "v1" }, { "created": "Wed, 11 Jan 2012 16:32:42 GMT", "version": "v2" } ]
2012-01-12
[ [ "Sarma", "Atish Das", "" ], [ "Molla", "Anisur Rahaman", "" ], [ "Pandurangan", "Gopal", "" ] ]
Performing random walks in networks is a fundamental primitive that has found numerous applications in communication networks such as token management, load balancing, network topology discovery and construction, search, and peer-to-peer membership management. While several such algorithms are ubiquitous, and use numer...
cs/0305007
Chris Johnson
C. A. Johnson
Computing only minimal answers in disjunctive deductive databases
48 pages
null
null
null
cs.LO
null
A method is presented for computing minimal answers in disjunctive deductive databases under the disjunctive stable model semantics. Such answers are constructed by repeatedly extending partial answers. Our method is complete (in that every minimal answer can be computed) and does not admit redundancy (in the sense t...
[ { "created": "Tue, 13 May 2003 08:27:45 GMT", "version": "v1" } ]
2007-05-23
[ [ "Johnson", "C. A.", "" ] ]
A method is presented for computing minimal answers in disjunctive deductive databases under the disjunctive stable model semantics. Such answers are constructed by repeatedly extending partial answers. Our method is complete (in that every minimal answer can be computed) and does not admit redundancy (in the sense tha...
2406.19087
Florian Mahner
Florian P. Mahner, Lukas Muttenthaler, Umut G\"u\c{c}l\"u, Martin N. Hebart
Dimensions underlying the representational alignment of deep neural networks with humans
null
null
null
null
cs.CV cs.AI cs.LG q-bio.QM
http://creativecommons.org/publicdomain/zero/1.0/
Determining the similarities and differences between humans and artificial intelligence is an important goal both in machine learning and cognitive neuroscience. However, similarities in representations only inform us about the degree of alignment, not the factors that determine it. Drawing upon recent developments i...
[ { "created": "Thu, 27 Jun 2024 11:14:14 GMT", "version": "v1" } ]
2024-06-28
[ [ "Mahner", "Florian P.", "" ], [ "Muttenthaler", "Lukas", "" ], [ "Güçlü", "Umut", "" ], [ "Hebart", "Martin N.", "" ] ]
Determining the similarities and differences between humans and artificial intelligence is an important goal both in machine learning and cognitive neuroscience. However, similarities in representations only inform us about the degree of alignment, not the factors that determine it. Drawing upon recent developments in ...
1703.05260
Ashutosh Modi
Ashutosh Modi and Tatjana Anikina and Simon Ostermann and Manfred Pinkal
InScript: Narrative texts annotated with script information
Paper accepted at LREC 2016, 9 pages, The corpus can be downloaded at: http://www.sfb1102.uni-saarland.de/?page_id=2582
LREC 2016
null
null
cs.CL cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper presents the InScript corpus (Narrative Texts Instantiating Script structure). InScript is a corpus of 1,000 stories centered around 10 different scenarios. Verbs and noun phrases are annotated with event and participant types, respectively. Additionally, the text is annotated with coreference information....
[ { "created": "Wed, 15 Mar 2017 17:01:20 GMT", "version": "v1" } ]
2017-03-16
[ [ "Modi", "Ashutosh", "" ], [ "Anikina", "Tatjana", "" ], [ "Ostermann", "Simon", "" ], [ "Pinkal", "Manfred", "" ] ]
This paper presents the InScript corpus (Narrative Texts Instantiating Script structure). InScript is a corpus of 1,000 stories centered around 10 different scenarios. Verbs and noun phrases are annotated with event and participant types, respectively. Additionally, the text is annotated with coreference information. T...
1007.1717
Petros Petrosyan
R.R. Kamalian, P.A. Petrosyan
A note on interval edge-colorings of graphs
4 pages, minor changes
null
null
null
cs.DM
http://creativecommons.org/licenses/by/3.0/
An edge-coloring of a graph $G$ with colors $1,2,\ldots,t$ is called an interval $t$-coloring if for each $i\in \{1,2,\ldots,t\}$ there is at least one edge of $G$ colored by $i$, and the colors of edges incident to any vertex of $G$ are distinct and form an interval of integers. In this paper we prove that if a conn...
[ { "created": "Sat, 10 Jul 2010 12:25:17 GMT", "version": "v1" }, { "created": "Thu, 12 Aug 2010 06:25:51 GMT", "version": "v2" } ]
2010-08-13
[ [ "Kamalian", "R. R.", "" ], [ "Petrosyan", "P. A.", "" ] ]
An edge-coloring of a graph $G$ with colors $1,2,\ldots,t$ is called an interval $t$-coloring if for each $i\in \{1,2,\ldots,t\}$ there is at least one edge of $G$ colored by $i$, and the colors of edges incident to any vertex of $G$ are distinct and form an interval of integers. In this paper we prove that if a connec...
2406.09984
Simone Lionetti
Adrian Willi, Pascal Baumann, Sophie Erb, Fabian Gr\"oger, Yanick Zeder, Simone Lionetti
Self-Supervised and Few-Shot Learning for Robust Bioaerosol Monitoring
Short communication, 8 pages, 2 figures, 1 table
null
null
null
cs.LG
http://creativecommons.org/licenses/by-sa/4.0/
Real-time bioaerosol monitoring is improving the quality of life for people affected by allergies, but it often relies on deep-learning models which pose challenges for widespread adoption. These models are typically trained in a supervised fashion and require considerable effort to produce large amounts of annotated...
[ { "created": "Fri, 14 Jun 2024 12:48:26 GMT", "version": "v1" } ]
2024-06-17
[ [ "Willi", "Adrian", "" ], [ "Baumann", "Pascal", "" ], [ "Erb", "Sophie", "" ], [ "Gröger", "Fabian", "" ], [ "Zeder", "Yanick", "" ], [ "Lionetti", "Simone", "" ] ]
Real-time bioaerosol monitoring is improving the quality of life for people affected by allergies, but it often relies on deep-learning models which pose challenges for widespread adoption. These models are typically trained in a supervised fashion and require considerable effort to produce large amounts of annotated d...
1910.08283
Muhammad Irfan Yousuf Dr.
Muhammad Irfan Yousuf, Raheel Anwar
Weighted Edge Sampling for Static Graphs
9 pages, 3 figures, Pre-print
null
null
null
cs.DS cs.SI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Graph Sampling provides an efficient yet inexpensive solution for analyzing large graphs. While extracting small representative subgraphs from large graphs, the challenge is to capture the properties of the original graph. Several sampling algorithms have been proposed in previous studies, but they lack in extracting...
[ { "created": "Fri, 18 Oct 2019 06:51:46 GMT", "version": "v1" } ]
2019-10-21
[ [ "Yousuf", "Muhammad Irfan", "" ], [ "Anwar", "Raheel", "" ] ]
Graph Sampling provides an efficient yet inexpensive solution for analyzing large graphs. While extracting small representative subgraphs from large graphs, the challenge is to capture the properties of the original graph. Several sampling algorithms have been proposed in previous studies, but they lack in extracting g...
2010.03190
Yijun Zhou
Yijun Zhou, Yuki Koyama, Masataka Goto, Takeo Igarashi
Generative Melody Composition with Human-in-the-Loop Bayesian Optimization
10 pages, 2 figures, Proceedings of the 2020 Joint Conference on AI Music Creativity (CSMC-MuMe 2020)
null
null
null
cs.SD cs.HC eess.AS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Deep generative models allow even novice composers to generate various melodies by sampling latent vectors. However, finding the desired melody is challenging since the latent space is unintuitive and high-dimensional. In this work, we present an interactive system that supports generative melody composition with hum...
[ { "created": "Wed, 7 Oct 2020 05:54:20 GMT", "version": "v1" } ]
2020-10-08
[ [ "Zhou", "Yijun", "" ], [ "Koyama", "Yuki", "" ], [ "Goto", "Masataka", "" ], [ "Igarashi", "Takeo", "" ] ]
Deep generative models allow even novice composers to generate various melodies by sampling latent vectors. However, finding the desired melody is challenging since the latent space is unintuitive and high-dimensional. In this work, we present an interactive system that supports generative melody composition with human...
2311.08473
Matteo Torzoni
Gabriel Garayalde, Matteo Torzoni, Matteo Bruggi, Alberto Corigliano
Real-time topology optimization via learnable mappings
null
null
10.1002/nme.7502
null
cs.CE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In traditional topology optimization, the computing time required to iteratively update the material distribution within a design domain strongly depends on the complexity or size of the problem, limiting its application in real engineering contexts. This work proposes a multi-stage machine learning strategy that aim...
[ { "created": "Tue, 14 Nov 2023 19:04:16 GMT", "version": "v1" }, { "created": "Mon, 13 May 2024 12:12:51 GMT", "version": "v2" } ]
2024-05-14
[ [ "Garayalde", "Gabriel", "" ], [ "Torzoni", "Matteo", "" ], [ "Bruggi", "Matteo", "" ], [ "Corigliano", "Alberto", "" ] ]
In traditional topology optimization, the computing time required to iteratively update the material distribution within a design domain strongly depends on the complexity or size of the problem, limiting its application in real engineering contexts. This work proposes a multi-stage machine learning strategy that aims ...
1304.6000
Jin Tan
Jin Tan, Dror Baron, and Liyi Dai
Mixture Gaussian Signal Estimation with L_infty Error Metric
null
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We consider the problem of estimating an input signal from noisy measurements in both parallel scalar Gaussian channels and linear mixing systems. The performance of the estimation process is quantified by the $\ell_\infty$ norm error metric. We first study the minimum mean $\ell_\infty$ error estimator in parallel s...
[ { "created": "Mon, 22 Apr 2013 16:09:33 GMT", "version": "v1" } ]
2013-04-23
[ [ "Tan", "Jin", "" ], [ "Baron", "Dror", "" ], [ "Dai", "Liyi", "" ] ]
We consider the problem of estimating an input signal from noisy measurements in both parallel scalar Gaussian channels and linear mixing systems. The performance of the estimation process is quantified by the $\ell_\infty$ norm error metric. We first study the minimum mean $\ell_\infty$ error estimator in parallel sca...
2110.12091
Junwen Bai
Junwen Bai, Weiran Wang, Carla Gomes
Contrastively Disentangled Sequential Variational Autoencoder
Accepted by NeurIPS 2021
null
null
null
cs.LG cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Self-supervised disentangled representation learning is a critical task in sequence modeling. The learnt representations contribute to better model interpretability as well as the data generation, and improve the sample efficiency for downstream tasks. We propose a novel sequence representation learning method, named...
[ { "created": "Fri, 22 Oct 2021 23:00:32 GMT", "version": "v1" } ]
2021-10-26
[ [ "Bai", "Junwen", "" ], [ "Wang", "Weiran", "" ], [ "Gomes", "Carla", "" ] ]
Self-supervised disentangled representation learning is a critical task in sequence modeling. The learnt representations contribute to better model interpretability as well as the data generation, and improve the sample efficiency for downstream tasks. We propose a novel sequence representation learning method, named C...
1707.01603
Fahad Alsifiany
Fahad Alsifiany, Aissa Ikhlef, Jonathon Chambers
On Differential Modulation in Downlink Multiuser MIMO Systems
5 pages, 4 figures
null
null
null
cs.IT math.IT math.NA
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we consider a space time block coded multiuser multiple-input multiple-output (MU-MIMO) system with downlink transmission. Specifically, we propose to use downlink precoding combined with differential modulation (DM) to shift the complexity from the receivers to the transmitter. The block diagonalizati...
[ { "created": "Thu, 6 Jul 2017 01:04:25 GMT", "version": "v1" } ]
2017-07-07
[ [ "Alsifiany", "Fahad", "" ], [ "Ikhlef", "Aissa", "" ], [ "Chambers", "Jonathon", "" ] ]
In this paper, we consider a space time block coded multiuser multiple-input multiple-output (MU-MIMO) system with downlink transmission. Specifically, we propose to use downlink precoding combined with differential modulation (DM) to shift the complexity from the receivers to the transmitter. The block diagonalization...
2401.07120
Minrui Xu
Minrui Xu, Dusit Niyato, Jiawen Kang, Zehui Xiong, Yuan Cao, Yulan Gao, Chao Ren, Han Yu
Generative AI-enabled Quantum Computing Networks and Intelligent Resource Allocation
null
null
null
null
cs.NI eess.SP quant-ph
http://creativecommons.org/licenses/by/4.0/
Quantum computing networks enable scalable collaboration and secure information exchange among multiple classical and quantum computing nodes while executing large-scale generative AI computation tasks and advanced quantum algorithms. Quantum computing networks overcome limitations such as the number of qubits and co...
[ { "created": "Sat, 13 Jan 2024 17:16:38 GMT", "version": "v1" } ]
2024-01-17
[ [ "Xu", "Minrui", "" ], [ "Niyato", "Dusit", "" ], [ "Kang", "Jiawen", "" ], [ "Xiong", "Zehui", "" ], [ "Cao", "Yuan", "" ], [ "Gao", "Yulan", "" ], [ "Ren", "Chao", "" ], [ "Yu", "Han", "" ...
Quantum computing networks enable scalable collaboration and secure information exchange among multiple classical and quantum computing nodes while executing large-scale generative AI computation tasks and advanced quantum algorithms. Quantum computing networks overcome limitations such as the number of qubits and cohe...
1911.12884
Graham Campbell
Graham Campbell and Detlef Plump
Efficient Recognition of Graph Languages
Project Report, Department of Computer Science, University of York, 83 pages, 2019. arXiv admin note: substantial text overlap with arXiv:1906.05170
null
null
null
cs.LO cs.CC cs.SC
http://creativecommons.org/licenses/by-nc-nd/4.0/
Graph transformation is the rule-based modification of graphs, and is a discipline dating back to the 1970s. In general, to match the left-hand graph of a fixed rule within a host graph requires polynomial time, but to improve matching performance, D\"orr proposed to equip rules and host graphs with distinguished roo...
[ { "created": "Thu, 28 Nov 2019 22:32:41 GMT", "version": "v1" }, { "created": "Wed, 11 Dec 2019 20:42:37 GMT", "version": "v2" }, { "created": "Fri, 1 Jan 2021 12:34:22 GMT", "version": "v3" } ]
2021-01-05
[ [ "Campbell", "Graham", "" ], [ "Plump", "Detlef", "" ] ]
Graph transformation is the rule-based modification of graphs, and is a discipline dating back to the 1970s. In general, to match the left-hand graph of a fixed rule within a host graph requires polynomial time, but to improve matching performance, D\"orr proposed to equip rules and host graphs with distinguished root ...
2205.00165
Zhijie Deng
Zhijie Deng, Jiaxin Shi, Jun Zhu
NeuralEF: Deconstructing Kernels by Deep Neural Networks
International Conference on Machine Learning (ICML), 2022
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Learning the principal eigenfunctions of an integral operator defined by a kernel and a data distribution is at the core of many machine learning problems. Traditional nonparametric solutions based on the Nystr{\"o}m formula suffer from scalability issues. Recent work has resorted to a parametric approach, i.e., trai...
[ { "created": "Sat, 30 Apr 2022 05:31:07 GMT", "version": "v1" }, { "created": "Mon, 13 Jun 2022 03:03:16 GMT", "version": "v2" }, { "created": "Fri, 17 Jun 2022 12:26:42 GMT", "version": "v3" }, { "created": "Sun, 23 Oct 2022 07:23:14 GMT", "version": "v4" } ]
2022-10-25
[ [ "Deng", "Zhijie", "" ], [ "Shi", "Jiaxin", "" ], [ "Zhu", "Jun", "" ] ]
Learning the principal eigenfunctions of an integral operator defined by a kernel and a data distribution is at the core of many machine learning problems. Traditional nonparametric solutions based on the Nystr{\"o}m formula suffer from scalability issues. Recent work has resorted to a parametric approach, i.e., traini...
2302.11793
Callum Rhys Tilbury
Callum Rhys Tilbury, Filippos Christianos, Stefano V. Albrecht
Revisiting the Gumbel-Softmax in MADDPG
Presented at AAMAS Workshop on Adaptive and Learning Agents, 2023
null
null
null
cs.LG cs.AI cs.MA stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
MADDPG is an algorithm in multi-agent reinforcement learning (MARL) that extends the popular single-agent method, DDPG, to multi-agent scenarios. Importantly, DDPG is an algorithm designed for continuous action spaces, where the gradient of the state-action value function exists. For this algorithm to work in discret...
[ { "created": "Thu, 23 Feb 2023 06:13:51 GMT", "version": "v1" }, { "created": "Wed, 14 Jun 2023 13:43:44 GMT", "version": "v2" } ]
2023-06-16
[ [ "Tilbury", "Callum Rhys", "" ], [ "Christianos", "Filippos", "" ], [ "Albrecht", "Stefano V.", "" ] ]
MADDPG is an algorithm in multi-agent reinforcement learning (MARL) that extends the popular single-agent method, DDPG, to multi-agent scenarios. Importantly, DDPG is an algorithm designed for continuous action spaces, where the gradient of the state-action value function exists. For this algorithm to work in discrete ...
2102.00266
Joanna Grzyb
Joanna Grzyb, Jakub Klikowski, Micha{\l} Wo\'zniak
Hellinger Distance Weighted Ensemble for Imbalanced Data Stream Classification
null
null
null
null
cs.CV
http://creativecommons.org/licenses/by-nc-nd/4.0/
The imbalanced data classification remains a vital problem. The key is to find such methods that classify both the minority and majority class correctly. The paper presents the classifier ensemble for classifying binary, non-stationary and imbalanced data streams where the Hellinger Distance is used to prune the ense...
[ { "created": "Sat, 30 Jan 2021 16:38:42 GMT", "version": "v1" } ]
2021-02-02
[ [ "Grzyb", "Joanna", "" ], [ "Klikowski", "Jakub", "" ], [ "Woźniak", "Michał", "" ] ]
The imbalanced data classification remains a vital problem. The key is to find such methods that classify both the minority and majority class correctly. The paper presents the classifier ensemble for classifying binary, non-stationary and imbalanced data streams where the Hellinger Distance is used to prune the ensemb...
2406.02222
Ran Wei PhD
Ran Wei, Ruizhe Yang, Shijun Liu, Chongsheng Fan, Rong Zhou, Zekun Wu, Haochi Wang, Yifan Cai, Zhe Jiang
Towards an Extensible Model-Based Digital Twin Framework for Space Launch Vehicles
null
null
null
null
cs.SE
http://creativecommons.org/licenses/by/4.0/
The concept of Digital Twin (DT) is increasingly applied to systems on different levels of abstraction across domains, to support monitoring, analysis, diagnosis, decision making and automated control. Whilst the interest in applying DT is growing, the definition of DT is unclear, neither is there a clear pathway to ...
[ { "created": "Tue, 4 Jun 2024 11:31:00 GMT", "version": "v1" } ]
2024-06-05
[ [ "Wei", "Ran", "" ], [ "Yang", "Ruizhe", "" ], [ "Liu", "Shijun", "" ], [ "Fan", "Chongsheng", "" ], [ "Zhou", "Rong", "" ], [ "Wu", "Zekun", "" ], [ "Wang", "Haochi", "" ], [ "Cai", "Yifan", ...
The concept of Digital Twin (DT) is increasingly applied to systems on different levels of abstraction across domains, to support monitoring, analysis, diagnosis, decision making and automated control. Whilst the interest in applying DT is growing, the definition of DT is unclear, neither is there a clear pathway to de...
2203.11014
Xi Liu
Buyun Zhang, Liang Luo, Xi Liu, Jay Li, Zeliang Chen, Weilin Zhang, Xiaohan Wei, Yuchen Hao, Michael Tsang, Wenjun Wang, Yang Liu, Huayu Li, Yasmine Badr, Jongsoo Park, Jiyan Yang, Dheevatsa Mudigere, Ellie Wen
DHEN: A Deep and Hierarchical Ensemble Network for Large-Scale Click-Through Rate Prediction
null
null
null
null
cs.IR cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Learning feature interactions is important to the model performance of online advertising services. As a result, extensive efforts have been devoted to designing effective architectures to learn feature interactions. However, we observe that the practical performance of those designs can vary from dataset to dataset,...
[ { "created": "Fri, 11 Mar 2022 21:19:31 GMT", "version": "v1" } ]
2022-03-22
[ [ "Zhang", "Buyun", "" ], [ "Luo", "Liang", "" ], [ "Liu", "Xi", "" ], [ "Li", "Jay", "" ], [ "Chen", "Zeliang", "" ], [ "Zhang", "Weilin", "" ], [ "Wei", "Xiaohan", "" ], [ "Hao", "Yuchen", "...
Learning feature interactions is important to the model performance of online advertising services. As a result, extensive efforts have been devoted to designing effective architectures to learn feature interactions. However, we observe that the practical performance of those designs can vary from dataset to dataset, e...
1909.03325
James Davenport
James H. Davenport
Formal Methods and CyberSecurity
To appear in "Short Papers FROM 2019"
null
null
null
cs.CR cs.SE
http://creativecommons.org/licenses/by-nc-sa/4.0/
Formal methods have been largely thought of in the context of safety-critical systems, where they have achieved major acceptance. Tens of millions of people trust their lives every day to such systems, based on formal proofs rather than ``we haven't found a bug'' (yet!). Why is ``we haven't found a bug'' an acceptabl...
[ { "created": "Sat, 7 Sep 2019 19:49:19 GMT", "version": "v1" } ]
2019-09-10
[ [ "Davenport", "James H.", "" ] ]
Formal methods have been largely thought of in the context of safety-critical systems, where they have achieved major acceptance. Tens of millions of people trust their lives every day to such systems, based on formal proofs rather than ``we haven't found a bug'' (yet!). Why is ``we haven't found a bug'' an acceptable ...
2207.04075
Sara Fridovich-Keil
Sara Fridovich-Keil, Brian R. Bartoldson, James Diffenderfer, Bhavya Kailkhura, Peer-Timo Bremer
Models Out of Line: A Fourier Lens on Distribution Shift Robustness
null
null
null
null
cs.LG
http://creativecommons.org/licenses/by/4.0/
Improving the accuracy of deep neural networks (DNNs) on out-of-distribution (OOD) data is critical to an acceptance of deep learning (DL) in real world applications. It has been observed that accuracies on in-distribution (ID) versus OOD data follow a linear trend and models that outperform this baseline are excepti...
[ { "created": "Fri, 8 Jul 2022 18:05:58 GMT", "version": "v1" } ]
2022-07-12
[ [ "Fridovich-Keil", "Sara", "" ], [ "Bartoldson", "Brian R.", "" ], [ "Diffenderfer", "James", "" ], [ "Kailkhura", "Bhavya", "" ], [ "Bremer", "Peer-Timo", "" ] ]
Improving the accuracy of deep neural networks (DNNs) on out-of-distribution (OOD) data is critical to an acceptance of deep learning (DL) in real world applications. It has been observed that accuracies on in-distribution (ID) versus OOD data follow a linear trend and models that outperform this baseline are exception...
2403.11572
Chia-Ming Lee
Chih-Chung Hsu and Chia-Ming Lee and Ming-Shyen Wu
Augment Before Copy-Paste: Data and Memory Efficiency-Oriented Instance Segmentation Framework for Sport-scenes
null
null
null
null
cs.CV cs.MM
http://creativecommons.org/licenses/by/4.0/
Instance segmentation is a fundamental task in computer vision with broad applications across various industries. In recent years, with the proliferation of deep learning and artificial intelligence applications, how to train effective models with limited data has become a pressing issue for both academia and industr...
[ { "created": "Mon, 18 Mar 2024 08:44:40 GMT", "version": "v1" } ]
2024-03-19
[ [ "Hsu", "Chih-Chung", "" ], [ "Lee", "Chia-Ming", "" ], [ "Wu", "Ming-Shyen", "" ] ]
Instance segmentation is a fundamental task in computer vision with broad applications across various industries. In recent years, with the proliferation of deep learning and artificial intelligence applications, how to train effective models with limited data has become a pressing issue for both academia and industry....
1412.3701
Thorsten Wissmann
Felix Klein (1) and Martin Zimmermann (1) ((1) Reactive Systems Group, Saarland University, Germany)
How Much Lookahead is Needed to Win Infinite Games?
null
Logical Methods in Computer Science, Volume 12, Issue 3 (April 27, 2017) lmcs:2011
10.2168/LMCS-12(3:4)2016
null
cs.GT cs.FL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Delay games are two-player games of infinite duration in which one player may delay her moves to obtain a lookahead on her opponent's moves. For $\omega$-regular winning conditions it is known that such games can be solved in doubly-exponential time and that doubly-exponential lookahead is sufficient. We improve up...
[ { "created": "Thu, 11 Dec 2014 16:13:12 GMT", "version": "v1" }, { "created": "Thu, 29 Oct 2015 10:44:14 GMT", "version": "v2" }, { "created": "Thu, 19 May 2016 20:28:42 GMT", "version": "v3" }, { "created": "Thu, 25 Aug 2016 12:29:45 GMT", "version": "v4" }, { "c...
2018-03-30
[ [ "Klein", "Felix", "" ], [ "Zimmermann", "Martin", "" ] ]
Delay games are two-player games of infinite duration in which one player may delay her moves to obtain a lookahead on her opponent's moves. For $\omega$-regular winning conditions it is known that such games can be solved in doubly-exponential time and that doubly-exponential lookahead is sufficient. We improve upon b...
1003.5196
Christoph Lange
Christoph Lange
SWiM -- A Semantic Wiki for Mathematical Knowledge Management
null
S. Bechhofer, M. Hauswirth, J. Hoffmann, M. Koubarakis. The Semantic Web: Research and Applications. ESWC 2008. LNCS 5021, Springer 2008
10.1007/978-3-540-68234-9_68
null
cs.DL cs.MS math.HO
http://creativecommons.org/licenses/by/3.0/
SWiM is a semantic wiki for collaboratively building, editing and browsing mathematical knowledge represented in the domain-specific structural semantic markup language OMDoc. It motivates users to contribute to collections of mathematical knowledge by instantly sharing the benefits of knowledge-powered services with...
[ { "created": "Fri, 26 Mar 2010 18:17:01 GMT", "version": "v1" } ]
2010-03-29
[ [ "Lange", "Christoph", "" ] ]
SWiM is a semantic wiki for collaboratively building, editing and browsing mathematical knowledge represented in the domain-specific structural semantic markup language OMDoc. It motivates users to contribute to collections of mathematical knowledge by instantly sharing the benefits of knowledge-powered services with t...
2302.09149
Niklas K\"uhl
Niklas K\"uhl, Hendrik Fischer, Michael Hinze, Thomas Rung
An Incremental Singular Value Decomposition Approach for Large-Scale Spatially Parallel & Distributed but Temporally Serial Data -- Applied to Technical Flows
null
null
null
null
cs.MS cs.DC physics.comp-ph physics.flu-dyn
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The paper presents a strategy to construct an incremental Singular Value Decomposition (SVD) for time-evolving, spatially 3D discrete data sets. A low memory access procedure for reducing and deploying the snapshot data is presented. Considered examples refer to Computational Fluid Dynamic (CFD) results extracted fro...
[ { "created": "Fri, 17 Feb 2023 21:19:54 GMT", "version": "v1" } ]
2023-02-21
[ [ "Kühl", "Niklas", "" ], [ "Fischer", "Hendrik", "" ], [ "Hinze", "Michael", "" ], [ "Rung", "Thomas", "" ] ]
The paper presents a strategy to construct an incremental Singular Value Decomposition (SVD) for time-evolving, spatially 3D discrete data sets. A low memory access procedure for reducing and deploying the snapshot data is presented. Considered examples refer to Computational Fluid Dynamic (CFD) results extracted from ...
2108.04230
Songyang Zhang
Songyang Zhang and Lin Song and Songtao Liu and Zheng Ge and Zeming Li and Xuming He and Jian Sun
Workshop on Autonomous Driving at CVPR 2021: Technical Report for Streaming Perception Challenge
Report of the 1st Place of Streaming Perception Challenge(Workshop on Autonomous Driving at CVPR 2021)
null
null
null
cs.CV cs.AI
http://creativecommons.org/licenses/by/4.0/
In this report, we introduce our real-time 2D object detection system for the realistic autonomous driving scenario. Our detector is built on a newly designed YOLO model, called YOLOX. On the Argoverse-HD dataset, our system achieves 41.0 streaming AP, which surpassed second place by 7.8/6.1 on detection-only track/f...
[ { "created": "Tue, 27 Jul 2021 06:36:06 GMT", "version": "v1" } ]
2021-08-10
[ [ "Zhang", "Songyang", "" ], [ "Song", "Lin", "" ], [ "Liu", "Songtao", "" ], [ "Ge", "Zheng", "" ], [ "Li", "Zeming", "" ], [ "He", "Xuming", "" ], [ "Sun", "Jian", "" ] ]
In this report, we introduce our real-time 2D object detection system for the realistic autonomous driving scenario. Our detector is built on a newly designed YOLO model, called YOLOX. On the Argoverse-HD dataset, our system achieves 41.0 streaming AP, which surpassed second place by 7.8/6.1 on detection-only track/ful...
cs/0211041
Lyubov Vassilevskaya
A.V. Averin (NSI, Moscow), L.A. Vassilevskaya (DESY, Hamburg)
An Approach to Automatic Indexing of Scientific Publications in High Energy Physics for Database SPIRES HEP
23 pages, 4 figures
null
null
DESY L-02-02 (November 2002)
cs.IR cs.DL
null
We introduce an approach to automatic indexing of e-prints based on a pattern-matching technique making extensive use of an Associative Patterns Dictionary (APD), developed by us. Entries in the APD consist of natural language phrases with the same semantic interpretation as a set of keywords from a controlled vocabu...
[ { "created": "Thu, 28 Nov 2002 17:33:19 GMT", "version": "v1" } ]
2007-05-23
[ [ "Averin", "A. V.", "", "NSI, Moscow" ], [ "Vassilevskaya", "L. A.", "", "DESY, Hamburg" ] ]
We introduce an approach to automatic indexing of e-prints based on a pattern-matching technique making extensive use of an Associative Patterns Dictionary (APD), developed by us. Entries in the APD consist of natural language phrases with the same semantic interpretation as a set of keywords from a controlled vocabula...
2007.06559
Jiaxuan You
Jiaxuan You, Jure Leskovec, Kaiming He, Saining Xie
Graph Structure of Neural Networks
ICML 2020, with open-source code
null
null
null
cs.LG cs.CV cs.SI stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Neural networks are often represented as graphs of connections between neurons. However, despite their wide use, there is currently little understanding of the relationship between the graph structure of the neural network and its predictive performance. Here we systematically investigate how does the graph structure...
[ { "created": "Mon, 13 Jul 2020 17:59:31 GMT", "version": "v1" }, { "created": "Thu, 27 Aug 2020 17:58:07 GMT", "version": "v2" } ]
2020-08-28
[ [ "You", "Jiaxuan", "" ], [ "Leskovec", "Jure", "" ], [ "He", "Kaiming", "" ], [ "Xie", "Saining", "" ] ]
Neural networks are often represented as graphs of connections between neurons. However, despite their wide use, there is currently little understanding of the relationship between the graph structure of the neural network and its predictive performance. Here we systematically investigate how does the graph structure o...
1102.1139
Zoltan Esik
Zoltan Esik
Residuated Park Theories
null
null
null
null
cs.LO math.LO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
When $L$ is a complete lattice, the collection $\Mon_L$ of all monotone functions $L^p \to L^n$, $n,p \geq 0$, forms a Lawvere theory. We enrich this Lawvere theory with the binary supremum operation $\vee$, an operation of (left) residuation $\res$ and the parameterized least fixed point operation $^\dagger$. We exh...
[ { "created": "Sun, 6 Feb 2011 11:08:57 GMT", "version": "v1" } ]
2015-03-18
[ [ "Esik", "Zoltan", "" ] ]
When $L$ is a complete lattice, the collection $\Mon_L$ of all monotone functions $L^p \to L^n$, $n,p \geq 0$, forms a Lawvere theory. We enrich this Lawvere theory with the binary supremum operation $\vee$, an operation of (left) residuation $\res$ and the parameterized least fixed point operation $^\dagger$. We exhib...
2206.06658
Xiaoyuan Zhang
Yukun Bao, Liang Shen, Xiaoyuan Zhang, Yanmei Huang and Changrui Deng
A novel MDPSO-SVR hybrid model for feature selection in electricity consumption forecasting
null
null
null
null
cs.NE
http://creativecommons.org/licenses/by/4.0/
Electricity consumption forecasting has vital importance for the energy planning of a country. Of the enabling machine learning models, support vector regression (SVR) has been widely used to set up forecasting models due to its superior generalization for unseen data. However, one key procedure for the predictive mo...
[ { "created": "Tue, 14 Jun 2022 07:50:04 GMT", "version": "v1" }, { "created": "Thu, 15 Sep 2022 07:35:16 GMT", "version": "v2" } ]
2022-09-16
[ [ "Bao", "Yukun", "" ], [ "Shen", "Liang", "" ], [ "Zhang", "Xiaoyuan", "" ], [ "Huang", "Yanmei", "" ], [ "Deng", "Changrui", "" ] ]
Electricity consumption forecasting has vital importance for the energy planning of a country. Of the enabling machine learning models, support vector regression (SVR) has been widely used to set up forecasting models due to its superior generalization for unseen data. However, one key procedure for the predictive mode...
2212.06921
Dylan Sam
Dylan Sam, J. Zico Kolter
Losses over Labels: Weakly Supervised Learning via Direct Loss Construction
13 pages, 3 figures, AAAI 2023
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Owing to the prohibitive costs of generating large amounts of labeled data, programmatic weak supervision is a growing paradigm within machine learning. In this setting, users design heuristics that provide noisy labels for subsets of the data. These weak labels are combined (typically via a graphical model) to form ...
[ { "created": "Tue, 13 Dec 2022 22:29:14 GMT", "version": "v1" }, { "created": "Wed, 4 Oct 2023 23:32:44 GMT", "version": "v2" } ]
2023-10-06
[ [ "Sam", "Dylan", "" ], [ "Kolter", "J. Zico", "" ] ]
Owing to the prohibitive costs of generating large amounts of labeled data, programmatic weak supervision is a growing paradigm within machine learning. In this setting, users design heuristics that provide noisy labels for subsets of the data. These weak labels are combined (typically via a graphical model) to form ps...
1701.03360
Jaeyoung Kim
Jaeyoung Kim, Mostafa El-Khamy, and Jungwon Lee
Residual LSTM: Design of a Deep Recurrent Architecture for Distant Speech Recognition
null
null
null
null
cs.LG cs.AI cs.SD
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, a novel architecture for a deep recurrent neural network, residual LSTM is introduced. A plain LSTM has an internal memory cell that can learn long term dependencies of sequential data. It also provides a temporal shortcut path to avoid vanishing or exploding gradients in the temporal domain. The resid...
[ { "created": "Tue, 10 Jan 2017 20:03:37 GMT", "version": "v1" }, { "created": "Wed, 15 Mar 2017 00:23:45 GMT", "version": "v2" }, { "created": "Mon, 5 Jun 2017 18:51:08 GMT", "version": "v3" } ]
2017-06-07
[ [ "Kim", "Jaeyoung", "" ], [ "El-Khamy", "Mostafa", "" ], [ "Lee", "Jungwon", "" ] ]
In this paper, a novel architecture for a deep recurrent neural network, residual LSTM is introduced. A plain LSTM has an internal memory cell that can learn long term dependencies of sequential data. It also provides a temporal shortcut path to avoid vanishing or exploding gradients in the temporal domain. The residua...
2307.15164
Vivek Kumar Dr.
Vivek Kumar, Sushmita Singh and Prayag Tiwari
VISU at WASSA 2023 Shared Task: Detecting Emotions in Reaction to News Stories Leveraging BERT and Stacked Embeddings
null
null
null
null
cs.CL cs.AI cs.LG
http://creativecommons.org/licenses/by/4.0/
Our system, VISU, participated in the WASSA 2023 Shared Task (3) of Emotion Classification from essays written in reaction to news articles. Emotion detection from complex dialogues is challenging and often requires context/domain understanding. Therefore in this research, we have focused on developing deep learning ...
[ { "created": "Thu, 27 Jul 2023 19:42:22 GMT", "version": "v1" } ]
2023-07-31
[ [ "Kumar", "Vivek", "" ], [ "Singh", "Sushmita", "" ], [ "Tiwari", "Prayag", "" ] ]
Our system, VISU, participated in the WASSA 2023 Shared Task (3) of Emotion Classification from essays written in reaction to news articles. Emotion detection from complex dialogues is challenging and often requires context/domain understanding. Therefore in this research, we have focused on developing deep learning (D...
2305.08183
Wei Yuan
Wei Yuan, Shilong Yuan, Chaoqun Yang, Quoc Viet Hung Nguyen, Hongzhi Yin
Manipulating Visually-aware Federated Recommender Systems and Its Countermeasures
null
null
null
null
cs.IR
http://creativecommons.org/licenses/by-nc-sa/4.0/
Federated recommender systems (FedRecs) have been widely explored recently due to their ability to protect user data privacy. In FedRecs, a central server collaboratively learns recommendation models by sharing model public parameters with clients, thereby offering a privacy-preserving solution. Unfortunately, the ex...
[ { "created": "Sun, 14 May 2023 15:22:52 GMT", "version": "v1" }, { "created": "Tue, 16 May 2023 22:26:01 GMT", "version": "v2" } ]
2023-05-18
[ [ "Yuan", "Wei", "" ], [ "Yuan", "Shilong", "" ], [ "Yang", "Chaoqun", "" ], [ "Nguyen", "Quoc Viet Hung", "" ], [ "Yin", "Hongzhi", "" ] ]
Federated recommender systems (FedRecs) have been widely explored recently due to their ability to protect user data privacy. In FedRecs, a central server collaboratively learns recommendation models by sharing model public parameters with clients, thereby offering a privacy-preserving solution. Unfortunately, the expo...
1906.04526
Lukas Lindenroth
Lukas Lindenroth, Richard James Housden, Shuangyi Wang, Junghwan Back, Kawal Rhode and Hongbin Liu
Design and integration of a parallel, soft robotic end-effector for extracorporeal ultrasound
null
IEEE Transactions on Biomedical Engineering, vol. 67, no. 8, pp. 2215-2229, Aug. 2020
10.1109/TBME.2019.2957609
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Objective: In this work we address limitations in state-of-the-art ultrasound robots by designing and integrating a novel soft robotic system for ultrasound imaging. It employs the inherent qualities of soft fluidic actuators to establish safe, adaptable interaction between ultrasound probe and patient. Methods: We a...
[ { "created": "Tue, 11 Jun 2019 12:26:53 GMT", "version": "v1" }, { "created": "Mon, 20 Jul 2020 22:31:59 GMT", "version": "v2" }, { "created": "Wed, 22 Jul 2020 20:32:48 GMT", "version": "v3" } ]
2020-07-24
[ [ "Lindenroth", "Lukas", "" ], [ "Housden", "Richard James", "" ], [ "Wang", "Shuangyi", "" ], [ "Back", "Junghwan", "" ], [ "Rhode", "Kawal", "" ], [ "Liu", "Hongbin", "" ] ]
Objective: In this work we address limitations in state-of-the-art ultrasound robots by designing and integrating a novel soft robotic system for ultrasound imaging. It employs the inherent qualities of soft fluidic actuators to establish safe, adaptable interaction between ultrasound probe and patient. Methods: We acq...
2106.02968
Rafid Mahmood
Rafid Mahmood, Sanja Fidler, Marc T. Law
Low Budget Active Learning via Wasserstein Distance: An Integer Programming Approach
null
null
null
null
cs.LG math.OC
http://creativecommons.org/licenses/by-nc-nd/4.0/
Active learning is the process of training a model with limited labeled data by selecting a core subset of an unlabeled data pool to label. The large scale of data sets used in deep learning forces most sample selection strategies to employ efficient heuristics. This paper introduces an integer optimization problem f...
[ { "created": "Sat, 5 Jun 2021 21:25:03 GMT", "version": "v1" }, { "created": "Sat, 12 Jun 2021 23:04:04 GMT", "version": "v2" }, { "created": "Sat, 5 Mar 2022 20:43:26 GMT", "version": "v3" }, { "created": "Tue, 7 Mar 2023 00:09:11 GMT", "version": "v4" } ]
2023-03-08
[ [ "Mahmood", "Rafid", "" ], [ "Fidler", "Sanja", "" ], [ "Law", "Marc T.", "" ] ]
Active learning is the process of training a model with limited labeled data by selecting a core subset of an unlabeled data pool to label. The large scale of data sets used in deep learning forces most sample selection strategies to employ efficient heuristics. This paper introduces an integer optimization problem for...
2212.07206
Cem Suulker
Cem Suulker, Sophie Skach, Kaspar Althoefer
A Fabric Soft Robotic Exoskeleton with Novel Elastic Band Integrated Actuators for Hand Rehabilitation
2 pages, 4 figures, conference
Conference on New Technologies for Computer and Robot Assisted Surgery (CRAS 2022)
null
null
cs.RO
http://creativecommons.org/licenses/by/4.0/
Common disabilities like stroke and spinal cord injuries may cause loss of motor function in hands. They can be treated with robot assisted rehabilitation techniques, like continuously opening and closing the hand with help of a robot, in a cheaper, and less time consuming manner than traditional methods. Hand exoske...
[ { "created": "Wed, 14 Dec 2022 13:08:19 GMT", "version": "v1" } ]
2022-12-15
[ [ "Suulker", "Cem", "" ], [ "Skach", "Sophie", "" ], [ "Althoefer", "Kaspar", "" ] ]
Common disabilities like stroke and spinal cord injuries may cause loss of motor function in hands. They can be treated with robot assisted rehabilitation techniques, like continuously opening and closing the hand with help of a robot, in a cheaper, and less time consuming manner than traditional methods. Hand exoskele...
2407.14249
Martin Menabue
Martin Menabue, Emanuele Frascaroli, Matteo Boschini, Lorenzo Bonicelli, Angelo Porrello, Simone Calderara
An Attention-based Representation Distillation Baseline for Multi-Label Continual Learning
Accepted at LOD 2024
null
null
null
cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The field of Continual Learning (CL) has inspired numerous researchers over the years, leading to increasingly advanced countermeasures to the issue of catastrophic forgetting. Most studies have focused on the single-class scenario, where each example comes with a single label. The recent literature has successfully ...
[ { "created": "Fri, 19 Jul 2024 12:30:03 GMT", "version": "v1" } ]
2024-07-22
[ [ "Menabue", "Martin", "" ], [ "Frascaroli", "Emanuele", "" ], [ "Boschini", "Matteo", "" ], [ "Bonicelli", "Lorenzo", "" ], [ "Porrello", "Angelo", "" ], [ "Calderara", "Simone", "" ] ]
The field of Continual Learning (CL) has inspired numerous researchers over the years, leading to increasingly advanced countermeasures to the issue of catastrophic forgetting. Most studies have focused on the single-class scenario, where each example comes with a single label. The recent literature has successfully ta...
2207.07522
Wencan Cheng
Wencan Cheng and Jong Hwan Ko
Bi-PointFlowNet: Bidirectional Learning for Point Cloud Based Scene Flow Estimation
Accepted as a conference paper at European Conference on Computer Vision (ECCV) 2022
null
null
null
cs.CV cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Scene flow estimation, which extracts point-wise motion between scenes, is becoming a crucial task in many computer vision tasks. However, all of the existing estimation methods utilize only the unidirectional features, restricting the accuracy and generality. This paper presents a novel scene flow estimation archite...
[ { "created": "Fri, 15 Jul 2022 15:14:53 GMT", "version": "v1" } ]
2022-07-18
[ [ "Cheng", "Wencan", "" ], [ "Ko", "Jong Hwan", "" ] ]
Scene flow estimation, which extracts point-wise motion between scenes, is becoming a crucial task in many computer vision tasks. However, all of the existing estimation methods utilize only the unidirectional features, restricting the accuracy and generality. This paper presents a novel scene flow estimation architect...
2201.08368
Lloyd Montgomery
Lloyd Montgomery, Clara L\"uders, Walid Maalej
An Alternative Issue Tracking Dataset of Public Jira Repositories
5 pages
null
10.1145/3524842.3528486
null
cs.SE
http://creativecommons.org/licenses/by/4.0/
Organisations use issue tracking systems (ITSs) to track and document their projects' work in units called issues. This style of documentation encourages evolutionary refinement, as each issue can be independently improved, commented on, linked to other issues, and progressed through the organisational workflow. Comm...
[ { "created": "Thu, 20 Jan 2022 18:52:36 GMT", "version": "v1" }, { "created": "Mon, 31 Jan 2022 16:09:20 GMT", "version": "v2" }, { "created": "Fri, 25 Mar 2022 16:17:18 GMT", "version": "v3" } ]
2022-03-28
[ [ "Montgomery", "Lloyd", "" ], [ "Lüders", "Clara", "" ], [ "Maalej", "Walid", "" ] ]
Organisations use issue tracking systems (ITSs) to track and document their projects' work in units called issues. This style of documentation encourages evolutionary refinement, as each issue can be independently improved, commented on, linked to other issues, and progressed through the organisational workflow. Common...
2003.07907
Ozan Tonguz K.
Keith Shannon, Elias Towe, and Ozan K. Tonguz
On the Use of Quantum Entanglement in Secure Communications: A Survey
null
null
null
null
cs.CR quant-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Quantum computing and quantum communications are exciting new frontiers in computing and communications. Indeed, the massive investments made by the governments of the US, China, and EU in these new technologies are not a secret and are based on the expected potential of these technologies to revolutionize communicat...
[ { "created": "Tue, 17 Mar 2020 19:32:40 GMT", "version": "v1" } ]
2020-03-20
[ [ "Shannon", "Keith", "" ], [ "Towe", "Elias", "" ], [ "Tonguz", "Ozan K.", "" ] ]
Quantum computing and quantum communications are exciting new frontiers in computing and communications. Indeed, the massive investments made by the governments of the US, China, and EU in these new technologies are not a secret and are based on the expected potential of these technologies to revolutionize communicatio...
2011.08366
Hiroto Yasumi
Hiroto Yasumi, Fukuhito Ooshita, Michiko Inoue, S\'ebastien Tixeuil
Uniform Bipartition in the Population Protocol Model with Arbitrary Communication Graphs
null
null
null
null
cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we focus on the uniform bipartition problem in the population protocol model. This problem aims to divide a population into two groups of equal size. In particular, we consider the problem in the context of \emph{arbitrary} communication graphs. As a result, we clarify the solvability of the uniform bi...
[ { "created": "Tue, 17 Nov 2020 02:06:21 GMT", "version": "v1" }, { "created": "Wed, 18 Nov 2020 02:18:22 GMT", "version": "v2" } ]
2020-11-19
[ [ "Yasumi", "Hiroto", "" ], [ "Ooshita", "Fukuhito", "" ], [ "Inoue", "Michiko", "" ], [ "Tixeuil", "Sébastien", "" ] ]
In this paper, we focus on the uniform bipartition problem in the population protocol model. This problem aims to divide a population into two groups of equal size. In particular, we consider the problem in the context of \emph{arbitrary} communication graphs. As a result, we clarify the solvability of the uniform bipa...
2310.17752
Ligeng Zhu
Ligeng Zhu, Lanxiang Hu, Ji Lin, Wei-Chen Wang, Wei-Ming Chen, Chuang Gan, Song Han
PockEngine: Sparse and Efficient Fine-tuning in a Pocket
null
56th IEEE/ACM International Symposium on Microarchitecture (MICRO 2023)
10.1145/3613424.3614307
null
cs.LG
http://creativecommons.org/licenses/by/4.0/
On-device learning and efficient fine-tuning enable continuous and privacy-preserving customization (e.g., locally fine-tuning large language models on personalized data). However, existing training frameworks are designed for cloud servers with powerful accelerators (e.g., GPUs, TPUs) and lack the optimizations for ...
[ { "created": "Thu, 26 Oct 2023 19:46:11 GMT", "version": "v1" } ]
2023-10-30
[ [ "Zhu", "Ligeng", "" ], [ "Hu", "Lanxiang", "" ], [ "Lin", "Ji", "" ], [ "Wang", "Wei-Chen", "" ], [ "Chen", "Wei-Ming", "" ], [ "Gan", "Chuang", "" ], [ "Han", "Song", "" ] ]
On-device learning and efficient fine-tuning enable continuous and privacy-preserving customization (e.g., locally fine-tuning large language models on personalized data). However, existing training frameworks are designed for cloud servers with powerful accelerators (e.g., GPUs, TPUs) and lack the optimizations for le...
1810.10801
Yulia Sandamirskaya
Sebastian Glatz, Julien N.P. Martel, Raphaela Kreiser, Ning Qiao, and Yulia Sandamirskaya
Adaptive motor control and learning in a spiking neural network realised on a mixed-signal neuromorphic processor
6+1 pages, 4 figures, will appear in one of the Robotics conferences
IEEE International Conference on Robotics and Automation (ICRA) 2019
null
null
cs.ET cs.NE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Neuromorphic computing is a new paradigm for design of both the computing hardware and algorithms inspired by biological neural networks. The event-based nature and the inherent parallelism make neuromorphic computing a promising paradigm for building efficient neural network based architectures for control of fast a...
[ { "created": "Thu, 25 Oct 2018 09:22:17 GMT", "version": "v1" } ]
2019-07-10
[ [ "Glatz", "Sebastian", "" ], [ "Martel", "Julien N. P.", "" ], [ "Kreiser", "Raphaela", "" ], [ "Qiao", "Ning", "" ], [ "Sandamirskaya", "Yulia", "" ] ]
Neuromorphic computing is a new paradigm for design of both the computing hardware and algorithms inspired by biological neural networks. The event-based nature and the inherent parallelism make neuromorphic computing a promising paradigm for building efficient neural network based architectures for control of fast and...
2106.11051
Omar Alolayan
Omar S. Alolayan, Samuel J. Raymond, Justin B. Montgomery and John R. Williams
Towards Better Shale Gas Production Forecasting Using Transfer Learning
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Deep neural networks can generate more accurate shale gas production forecasts in counties with a limited number of sample wells by utilizing transfer learning. This paper provides a way of transferring the knowledge gained from other deep neural network models trained on adjacent counties into the county of interest...
[ { "created": "Mon, 21 Jun 2021 12:37:44 GMT", "version": "v1" } ]
2021-06-22
[ [ "Alolayan", "Omar S.", "" ], [ "Raymond", "Samuel J.", "" ], [ "Montgomery", "Justin B.", "" ], [ "Williams", "John R.", "" ] ]
Deep neural networks can generate more accurate shale gas production forecasts in counties with a limited number of sample wells by utilizing transfer learning. This paper provides a way of transferring the knowledge gained from other deep neural network models trained on adjacent counties into the county of interest. ...
2106.04812
Kshitij Tayal
Kshitij Tayal, Raunak Manekar, Zhong Zhuang, David Yang, Vipin Kumar, Felix Hofmann, Ju Sun
Phase Retrieval using Single-Instance Deep Generative Prior
null
null
null
null
cs.LG eess.IV
http://creativecommons.org/licenses/by/4.0/
Several deep learning methods for phase retrieval exist, but most of them fail on realistic data without precise support information. We propose a novel method based on single-instance deep generative prior that works well on complex-valued crystal data.
[ { "created": "Wed, 9 Jun 2021 05:11:33 GMT", "version": "v1" }, { "created": "Tue, 22 Jun 2021 19:59:54 GMT", "version": "v2" } ]
2021-06-24
[ [ "Tayal", "Kshitij", "" ], [ "Manekar", "Raunak", "" ], [ "Zhuang", "Zhong", "" ], [ "Yang", "David", "" ], [ "Kumar", "Vipin", "" ], [ "Hofmann", "Felix", "" ], [ "Sun", "Ju", "" ] ]
Several deep learning methods for phase retrieval exist, but most of them fail on realistic data without precise support information. We propose a novel method based on single-instance deep generative prior that works well on complex-valued crystal data.
2112.01379
Joseph Tien
Matthew T. Osborne, Samuel S. Malloy, Erik C. Nisbet, Robert M. Bond, Joseph H. Tien
Sentinel node approach to monitoring online COVID-19 misinformation
null
null
null
null
cs.SI
http://creativecommons.org/licenses/by-nc-sa/4.0/
Understanding how different online communities engage with COVID-19 misinformation is critical for public health response, as misinformation confined to a small, isolated community of users poses a different public health risk than misinformation being consumed by a large population spanning many diverse communities....
[ { "created": "Thu, 2 Dec 2021 16:12:38 GMT", "version": "v1" } ]
2021-12-03
[ [ "Osborne", "Matthew T.", "" ], [ "Malloy", "Samuel S.", "" ], [ "Nisbet", "Erik C.", "" ], [ "Bond", "Robert M.", "" ], [ "Tien", "Joseph H.", "" ] ]
Understanding how different online communities engage with COVID-19 misinformation is critical for public health response, as misinformation confined to a small, isolated community of users poses a different public health risk than misinformation being consumed by a large population spanning many diverse communities. H...
1408.6228
M. Rizwan Jameel Qureshi Dr.
M. Rizwan Jameel Qureshi
Estimation of the new agile XP process model for medium-scale projects using industrial case studies
3 pages, 1 figure
International Journal of Machine Learning and Computing, online October 2013; Vol. 3, No. 5, 2013, pp. 393-395
10.7763/IJMLC.2013.V3.346
null
cs.SE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Agile is one of the terms with which software professionals are quite familiar. Agile models promote fast development to develop high quality software. XP process model is one of the most widely used and most documented agile models. XP model is meant for small-scale projects. Since XP model is a good model, therefor...
[ { "created": "Tue, 26 Aug 2014 14:07:34 GMT", "version": "v1" } ]
2014-08-28
[ [ "Qureshi", "M. Rizwan Jameel", "" ] ]
Agile is one of the terms with which software professionals are quite familiar. Agile models promote fast development to develop high quality software. XP process model is one of the most widely used and most documented agile models. XP model is meant for small-scale projects. Since XP model is a good model, therefore ...
2012.08408
Zhuonan Liang
Zhuonan Liang, Ziheng Liu, Huaze Shi, Yunlong Chen, Yanbin Cai, Yating Liang, Yafan Feng, Yuqing Yang, Jing Zhang, Peng Fu
SPOC learner's final grade prediction based on a novel sampling batch normalization embedded neural network method
11 pages, 5 figures, ICAIS 2021
Multimed Tools Appl (2022)
10.1007/s11042-022-13628-y
null
cs.CV
http://creativecommons.org/licenses/by-nc-nd/4.0/
Recent years have witnessed the rapid growth of Small Private Online Courses (SPOC) which is able to highly customized and personalized to adapt variable educational requests, in which machine learning techniques are explored to summarize and predict the learner's performance, mostly focus on the final grade. However...
[ { "created": "Tue, 15 Dec 2020 16:36:42 GMT", "version": "v1" }, { "created": "Fri, 11 Nov 2022 07:29:44 GMT", "version": "v2" } ]
2022-11-14
[ [ "Liang", "Zhuonan", "" ], [ "Liu", "Ziheng", "" ], [ "Shi", "Huaze", "" ], [ "Chen", "Yunlong", "" ], [ "Cai", "Yanbin", "" ], [ "Liang", "Yating", "" ], [ "Feng", "Yafan", "" ], [ "Yang", "Yuqi...
Recent years have witnessed the rapid growth of Small Private Online Courses (SPOC) which is able to highly customized and personalized to adapt variable educational requests, in which machine learning techniques are explored to summarize and predict the learner's performance, mostly focus on the final grade. However, ...
2312.17532
Yuncheng Huang
Yuncheng Huang, Qianyu He, Jiaqing Liang, Sihang Jiang, Yanghua Xiao and Yunwen Chen
Enhancing Quantitative Reasoning Skills of Large Language Models through Dimension Perception
Accepted in the 40th IEEE International Conference on Data Engineering (ICDE 2024)
null
null
null
cs.CL cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Quantities are distinct and critical components of texts that characterize the magnitude properties of entities, providing a precise perspective for the understanding of natural language, especially for reasoning tasks. In recent years, there has been a flurry of research on reasoning tasks based on large language mo...
[ { "created": "Fri, 29 Dec 2023 09:29:37 GMT", "version": "v1" } ]
2024-01-01
[ [ "Huang", "Yuncheng", "" ], [ "He", "Qianyu", "" ], [ "Liang", "Jiaqing", "" ], [ "Jiang", "Sihang", "" ], [ "Xiao", "Yanghua", "" ], [ "Chen", "Yunwen", "" ] ]
Quantities are distinct and critical components of texts that characterize the magnitude properties of entities, providing a precise perspective for the understanding of natural language, especially for reasoning tasks. In recent years, there has been a flurry of research on reasoning tasks based on large language mode...
2206.00510
Zuowu Zheng
Zuowu Zheng, Changwang Zhang, Xiaofeng Gao, Guihai Chen
HIEN: Hierarchical Intention Embedding Network for Click-Through Rate Prediction
Accepted by SIGIR 2022
null
10.1145/3477495.3531988
null
cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Click-through rate (CTR) prediction plays an important role in online advertising and recommendation systems, which aims at estimating the probability of a user clicking on a specific item. Feature interaction modeling and user interest modeling methods are two popular domains in CTR prediction, and they have been st...
[ { "created": "Wed, 1 Jun 2022 14:14:14 GMT", "version": "v1" } ]
2022-06-02
[ [ "Zheng", "Zuowu", "" ], [ "Zhang", "Changwang", "" ], [ "Gao", "Xiaofeng", "" ], [ "Chen", "Guihai", "" ] ]
Click-through rate (CTR) prediction plays an important role in online advertising and recommendation systems, which aims at estimating the probability of a user clicking on a specific item. Feature interaction modeling and user interest modeling methods are two popular domains in CTR prediction, and they have been stud...
2003.04421
Roman Sokolovskii
Roman Sokolovskii and Alexandre Graell i Amat and Fredrik Br\"annstr\"om
Finite-Length Scaling of Spatially Coupled LDPC Codes Under Window Decoding Over the BEC
Published in IEEE Transactions on Communications (Early Access). This paper was presented in part at the IEEE Information Theory Workshop (ITW), Visby, Sweden, August 2019 (arXiv:1904.10410)
null
10.1109/TCOMM.2020.3010958
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We analyze the finite-length performance of spatially coupled low-density parity-check (SC-LDPC) codes under window decoding over the binary erasure channel. In particular, we propose a refinement of the scaling law by Olmos and Urbanke for the frame error rate (FER) of terminated SC-LDPC ensembles under full belief ...
[ { "created": "Mon, 9 Mar 2020 21:33:09 GMT", "version": "v1" }, { "created": "Tue, 25 Aug 2020 14:41:51 GMT", "version": "v2" } ]
2020-08-26
[ [ "Sokolovskii", "Roman", "" ], [ "Amat", "Alexandre Graell i", "" ], [ "Brännström", "Fredrik", "" ] ]
We analyze the finite-length performance of spatially coupled low-density parity-check (SC-LDPC) codes under window decoding over the binary erasure channel. In particular, we propose a refinement of the scaling law by Olmos and Urbanke for the frame error rate (FER) of terminated SC-LDPC ensembles under full belief pr...
2406.14167
Andrey Kutuzov
Mariia Fedorova, Andrey Kutuzov, Yves Scherrer
Definition generation for lexical semantic change detection
Findings of ACL 2024
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
We use contextualized word definitions generated by large language models as semantic representations in the task of diachronic lexical semantic change detection (LSCD). In short, generated definitions are used as `senses', and the change score of a target word is retrieved by comparing their distributions in two tim...
[ { "created": "Thu, 20 Jun 2024 10:13:08 GMT", "version": "v1" }, { "created": "Wed, 31 Jul 2024 16:20:45 GMT", "version": "v2" } ]
2024-08-01
[ [ "Fedorova", "Mariia", "" ], [ "Kutuzov", "Andrey", "" ], [ "Scherrer", "Yves", "" ] ]
We use contextualized word definitions generated by large language models as semantic representations in the task of diachronic lexical semantic change detection (LSCD). In short, generated definitions are used as `senses', and the change score of a target word is retrieved by comparing their distributions in two time ...
1906.09567
Mohsen Ghodrat
Mohsen Ghodrat and Horacio J Marquez
On the Local Input-Output Stability of Event-Triggered Control Systems
37 pages, 6 figures
IEEE Trans. Autom. Control 64(1), 2019, 174-189
10.1109/TAC.2018.2809594
null
cs.SY eess.SY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper studies performance preserving event design in nonlinear event-based control systems based on a local L2-type performance criterion. Considering a finite gain local L2-stable disturbance driven continuous-time system, we propose a triggering mechanism so that the resulting sampled-data system preserves sim...
[ { "created": "Sun, 23 Jun 2019 09:15:43 GMT", "version": "v1" }, { "created": "Sun, 21 Jul 2019 06:44:34 GMT", "version": "v2" } ]
2019-07-23
[ [ "Ghodrat", "Mohsen", "" ], [ "Marquez", "Horacio J", "" ] ]
This paper studies performance preserving event design in nonlinear event-based control systems based on a local L2-type performance criterion. Considering a finite gain local L2-stable disturbance driven continuous-time system, we propose a triggering mechanism so that the resulting sampled-data system preserves simil...
2101.05605
Rui Liu
Rui Liu and Sen Liu and Xiaoli Zhang
A Physics-Informed Machine Learning Model for Porosity Analysis in Laser Powder Bed Fusion Additive Manufacturing
14 pages
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
To control part quality, it is critical to analyze pore generation mechanisms, laying theoretical foundation for future porosity control. Current porosity analysis models use machine setting parameters, such as laser angle and part pose. However, these setting-based models are machine dependent, hence they often do n...
[ { "created": "Wed, 13 Jan 2021 01:29:01 GMT", "version": "v1" } ]
2021-01-15
[ [ "Liu", "Rui", "" ], [ "Liu", "Sen", "" ], [ "Zhang", "Xiaoli", "" ] ]
To control part quality, it is critical to analyze pore generation mechanisms, laying theoretical foundation for future porosity control. Current porosity analysis models use machine setting parameters, such as laser angle and part pose. However, these setting-based models are machine dependent, hence they often do not...
2009.12216
Jon McCormack
Jon McCormack and Andy Lomas
Deep Learning of Individual Aesthetics
Author preprint of article for Neural Computing and Applications. arXiv admin note: substantial text overlap with arXiv:2004.06874
null
null
null
cs.NE cs.GR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Accurate evaluation of human aesthetic preferences represents a major challenge for creative evolutionary and generative systems research. Prior work has tended to focus on feature measures of the artefact, such as symmetry, complexity and coherence. However, research models from Psychology suggest that human aesthet...
[ { "created": "Thu, 24 Sep 2020 03:04:28 GMT", "version": "v1" } ]
2020-09-28
[ [ "McCormack", "Jon", "" ], [ "Lomas", "Andy", "" ] ]
Accurate evaluation of human aesthetic preferences represents a major challenge for creative evolutionary and generative systems research. Prior work has tended to focus on feature measures of the artefact, such as symmetry, complexity and coherence. However, research models from Psychology suggest that human aesthetic...
1410.5782
Sean Sedwards
Axel Legay, Sean Sedwards and Louis-Marie Traonouez
Lightweight Monte Carlo Verification of Markov Decision Processes with Rewards
16 pages, 4 figures, 1 table
null
null
null
cs.LO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Markov decision processes are useful models of concurrency optimisation problems, but are often intractable for exhaustive verification methods. Recent work has introduced lightweight approximative techniques that sample directly from scheduler space, bringing the prospect of scalable alternatives to standard numeric...
[ { "created": "Mon, 20 Oct 2014 05:56:26 GMT", "version": "v1" }, { "created": "Sun, 15 Feb 2015 10:25:43 GMT", "version": "v2" }, { "created": "Mon, 23 Mar 2015 11:54:05 GMT", "version": "v3" } ]
2015-03-24
[ [ "Legay", "Axel", "" ], [ "Sedwards", "Sean", "" ], [ "Traonouez", "Louis-Marie", "" ] ]
Markov decision processes are useful models of concurrency optimisation problems, but are often intractable for exhaustive verification methods. Recent work has introduced lightweight approximative techniques that sample directly from scheduler space, bringing the prospect of scalable alternatives to standard numerical...
1107.5478
Santosh Vempala
Daniel Dadush and Santosh Vempala
Deterministic Construction of an Approximate M-Ellipsoid and its Application to Derandomizing Lattice Algorithms
null
null
null
null
cs.CC math.FA
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We give a deterministic O(log n)^n algorithm for the {\em Shortest Vector Problem (SVP)} of a lattice under {\em any} norm, improving on the previous best deterministic bound of n^O(n) for general norms and nearly matching the bound of 2^O(n) for the standard Euclidean norm established by Micciancio and Voulgaris (ST...
[ { "created": "Wed, 27 Jul 2011 14:05:55 GMT", "version": "v1" } ]
2011-07-28
[ [ "Dadush", "Daniel", "" ], [ "Vempala", "Santosh", "" ] ]
We give a deterministic O(log n)^n algorithm for the {\em Shortest Vector Problem (SVP)} of a lattice under {\em any} norm, improving on the previous best deterministic bound of n^O(n) for general norms and nearly matching the bound of 2^O(n) for the standard Euclidean norm established by Micciancio and Voulgaris (STOC...
1002.0139
Kadirvelu SivaKumar
P.S Hiremath, Siddu P. Algur
Extraction of Flat and Nested Data Records from Web Pages
10 Pages IEEE format, International Journal on Computer Science and Engineering, IJCSE 2010, ISSN 0975-3397, Impact Factor 0.583
International Journal on Computer Science and Engineering, IJCSE, Vol. 2, No. 1 January 2010
null
IJEST10-02-01-07
cs.DB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper studies the problem of identification and extraction of flat and nested data records from a given web page. With the explosive growth of information sources available on the World Wide Web, it has become increasingly difficult to identify the relevant pieces of information, since web pages are often clutte...
[ { "created": "Sun, 31 Jan 2010 16:39:26 GMT", "version": "v1" } ]
2010-02-02
[ [ "Hiremath", "P. S", "" ], [ "Algur", "Siddu P.", "" ] ]
This paper studies the problem of identification and extraction of flat and nested data records from a given web page. With the explosive growth of information sources available on the World Wide Web, it has become increasingly difficult to identify the relevant pieces of information, since web pages are often cluttere...
2205.04114
Wei Zhu
Wei Zhu, Le Lu, Jing Xiao, Mei Han, Jiebo Luo, Adam P. Harrison
Localized Adversarial Domain Generalization
null
null
null
null
cs.LG
http://creativecommons.org/licenses/by/4.0/
Deep learning methods can struggle to handle domain shifts not seen in training data, which can cause them to not generalize well to unseen domains. This has led to research attention on domain generalization (DG), which aims to the model's generalization ability to out-of-distribution. Adversarial domain generalizat...
[ { "created": "Mon, 9 May 2022 08:30:31 GMT", "version": "v1" } ]
2022-05-10
[ [ "Zhu", "Wei", "" ], [ "Lu", "Le", "" ], [ "Xiao", "Jing", "" ], [ "Han", "Mei", "" ], [ "Luo", "Jiebo", "" ], [ "Harrison", "Adam P.", "" ] ]
Deep learning methods can struggle to handle domain shifts not seen in training data, which can cause them to not generalize well to unseen domains. This has led to research attention on domain generalization (DG), which aims to the model's generalization ability to out-of-distribution. Adversarial domain generalizatio...
2103.05961
Jian Zhang
Chong Mou, Jian Zhang, Xiaopeng Fan, Hangfan Liu, Ronggang Wang
COLA-Net: Collaborative Attention Network for Image Restoration
11 pages, 6 tables, 9 figures, to be published in IEEE Transactions on Multimedia
null
10.1109/TMM.2021.3063916
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Local and non-local attention-based methods have been well studied in various image restoration tasks while leading to promising performance. However, most of the existing methods solely focus on one type of attention mechanism (local or non-local). Furthermore, by exploiting the self-similarity of natural images, ex...
[ { "created": "Wed, 10 Mar 2021 09:33:17 GMT", "version": "v1" } ]
2021-03-11
[ [ "Mou", "Chong", "" ], [ "Zhang", "Jian", "" ], [ "Fan", "Xiaopeng", "" ], [ "Liu", "Hangfan", "" ], [ "Wang", "Ronggang", "" ] ]
Local and non-local attention-based methods have been well studied in various image restoration tasks while leading to promising performance. However, most of the existing methods solely focus on one type of attention mechanism (local or non-local). Furthermore, by exploiting the self-similarity of natural images, exis...
2407.11798
Branden Butler
Branden Butler, Sixing Yu, Arya Mazaheri, and Ali Jannesari
PipeInfer: Accelerating LLM Inference using Asynchronous Pipelined Speculation
11 pages, submitted to SC24 conference
null
null
null
cs.CL cs.DC cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Inference of Large Language Models (LLMs) across computer clusters has become a focal point of research in recent times, with many acceleration techniques taking inspiration from CPU speculative execution. These techniques reduce bottlenecks associated with memory bandwidth, but also increase end-to-end latency per i...
[ { "created": "Tue, 16 Jul 2024 14:52:02 GMT", "version": "v1" } ]
2024-07-17
[ [ "Butler", "Branden", "" ], [ "Yu", "Sixing", "" ], [ "Mazaheri", "Arya", "" ], [ "Jannesari", "Ali", "" ] ]
Inference of Large Language Models (LLMs) across computer clusters has become a focal point of research in recent times, with many acceleration techniques taking inspiration from CPU speculative execution. These techniques reduce bottlenecks associated with memory bandwidth, but also increase end-to-end latency per inf...
1812.06081
Sendong Zhao
Sendong Zhao, Ting Liu, Sicheng Zhao, Fei Wang
A Neural Multi-Task Learning Framework to Jointly Model Medical Named Entity Recognition and Normalization
AAAI-2019
null
null
null
cs.CL cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
State-of-the-art studies have demonstrated the superiority of joint modelling over pipeline implementation for medical named entity recognition and normalization due to the mutual benefits between the two processes. To exploit these benefits in a more sophisticated way, we propose a novel deep neural multi-task learn...
[ { "created": "Fri, 14 Dec 2018 18:59:41 GMT", "version": "v1" } ]
2018-12-17
[ [ "Zhao", "Sendong", "" ], [ "Liu", "Ting", "" ], [ "Zhao", "Sicheng", "" ], [ "Wang", "Fei", "" ] ]
State-of-the-art studies have demonstrated the superiority of joint modelling over pipeline implementation for medical named entity recognition and normalization due to the mutual benefits between the two processes. To exploit these benefits in a more sophisticated way, we propose a novel deep neural multi-task learnin...
2205.09445
Jiahui Wang Mr
Jiahui Wang, Zhenyou Wang, Shanna Zhuang, Hui Wang
Cross-Enhancement Transformer for Action Segmentation
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Temporal convolutions have been the paradigm of choice in action segmentation, which enhances long-term receptive fields by increasing convolution layers. However, high layers cause the loss of local information necessary for frame recognition. To solve the above problem, a novel encoder-decoder structure is proposed...
[ { "created": "Thu, 19 May 2022 10:06:30 GMT", "version": "v1" } ]
2022-05-20
[ [ "Wang", "Jiahui", "" ], [ "Wang", "Zhenyou", "" ], [ "Zhuang", "Shanna", "" ], [ "Wang", "Hui", "" ] ]
Temporal convolutions have been the paradigm of choice in action segmentation, which enhances long-term receptive fields by increasing convolution layers. However, high layers cause the loss of local information necessary for frame recognition. To solve the above problem, a novel encoder-decoder structure is proposed i...
1903.10636
Annalisa Massini
Novella Bartolini, Ting He, Viviana Arrigoni, Annalisa Massini, Hana Khamfroush
On Fundamental Bounds of Failure Identifiability by Boolean Network Tomography
null
null
null
null
cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Boolean network tomography is a powerful tool to infer the state (working/failed) of individual nodes from path-level measurements obtained by egde-nodes. We consider the problem of optimizing the capability of identifying network failures through the design of monitoring schemes. Finding an optimal solution is NP-ha...
[ { "created": "Tue, 26 Mar 2019 00:03:10 GMT", "version": "v1" } ]
2019-03-27
[ [ "Bartolini", "Novella", "" ], [ "He", "Ting", "" ], [ "Arrigoni", "Viviana", "" ], [ "Massini", "Annalisa", "" ], [ "Khamfroush", "Hana", "" ] ]
Boolean network tomography is a powerful tool to infer the state (working/failed) of individual nodes from path-level measurements obtained by egde-nodes. We consider the problem of optimizing the capability of identifying network failures through the design of monitoring schemes. Finding an optimal solution is NP-hard...
1804.09113
Benjamin Planche
Sergey Zakharov, Benjamin Planche, Ziyan Wu, Andreas Hutter, Harald Kosch, Slobodan Ilic
Keep it Unreal: Bridging the Realism Gap for 2.5D Recognition with Geometry Priors Only
10 pages + supplemetary material + references. The first two authors contributed equally to this work
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
With the increasing availability of large databases of 3D CAD models, depth-based recognition methods can be trained on an uncountable number of synthetically rendered images. However, discrepancies with the real data acquired from various depth sensors still noticeably impede progress. Previous works adopted unsuper...
[ { "created": "Tue, 24 Apr 2018 16:02:59 GMT", "version": "v1" }, { "created": "Thu, 24 May 2018 16:08:07 GMT", "version": "v2" } ]
2018-05-25
[ [ "Zakharov", "Sergey", "" ], [ "Planche", "Benjamin", "" ], [ "Wu", "Ziyan", "" ], [ "Hutter", "Andreas", "" ], [ "Kosch", "Harald", "" ], [ "Ilic", "Slobodan", "" ] ]
With the increasing availability of large databases of 3D CAD models, depth-based recognition methods can be trained on an uncountable number of synthetically rendered images. However, discrepancies with the real data acquired from various depth sensors still noticeably impede progress. Previous works adopted unsupervi...
2010.09559
Cristi\'an Bravo
Mar\'ia \'Oskarsd\'ottir and Cristi\'an Bravo
Multilayer Network Analysis for Improved Credit Risk Prediction
24 pages, 15 figures. v4 - accepted
Omega 105: 102520 (2021)
10.1016/j.omega.2021.102520
null
cs.SI cs.LG
http://creativecommons.org/licenses/by-nc-nd/4.0/
We present a multilayer network model for credit risk assessment. Our model accounts for multiple connections between borrowers (such as their geographic location and their economic activity) and allows for explicitly modelling the interaction between connected borrowers. We develop a multilayer personalized PageRank...
[ { "created": "Mon, 19 Oct 2020 14:39:53 GMT", "version": "v1" }, { "created": "Thu, 11 Feb 2021 22:57:28 GMT", "version": "v2" }, { "created": "Tue, 1 Jun 2021 23:01:03 GMT", "version": "v3" }, { "created": "Mon, 26 Jul 2021 17:00:17 GMT", "version": "v4" } ]
2021-07-27
[ [ "Óskarsdóttir", "María", "" ], [ "Bravo", "Cristián", "" ] ]
We present a multilayer network model for credit risk assessment. Our model accounts for multiple connections between borrowers (such as their geographic location and their economic activity) and allows for explicitly modelling the interaction between connected borrowers. We develop a multilayer personalized PageRank a...
2103.15980
Jose-Luis Blanco-Claraco
Jos\'e Luis Blanco-Claraco
A tutorial on $\mathbf{SE}(3)$ transformation parameterizations and on-manifold optimization
68 pages, 6 figures; v2 in arXiv; see history of document versions on page 3 for full change log of the technical report since 2010
null
null
UMA-MAPIR-012010
cs.RO cs.CV
http://creativecommons.org/licenses/by-nc-sa/4.0/
An arbitrary rigid transformation in $\mathbf{SE}(3)$ can be separated into two parts, namely, a translation and a rigid rotation. This technical report reviews, under a unifying viewpoint, three common alternatives to representing the rotation part: sets of three (yaw-pitch-roll) Euler angles, orthogonal rotation ma...
[ { "created": "Mon, 29 Mar 2021 22:43:49 GMT", "version": "v1" }, { "created": "Thu, 7 Apr 2022 07:09:18 GMT", "version": "v2" } ]
2022-04-08
[ [ "Blanco-Claraco", "José Luis", "" ] ]
An arbitrary rigid transformation in $\mathbf{SE}(3)$ can be separated into two parts, namely, a translation and a rigid rotation. This technical report reviews, under a unifying viewpoint, three common alternatives to representing the rotation part: sets of three (yaw-pitch-roll) Euler angles, orthogonal rotation matr...
2406.09404
Junkun Chen
Jun-Kun Chen, Samuel Rota Bul\`o, Norman M\"uller, Lorenzo Porzi, Peter Kontschieder, Yu-Xiong Wang
ConsistDreamer: 3D-Consistent 2D Diffusion for High-Fidelity Scene Editing
CVPR 2024
null
null
null
cs.CV cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper proposes ConsistDreamer - a novel framework that lifts 2D diffusion models with 3D awareness and 3D consistency, thus enabling high-fidelity instruction-guided scene editing. To overcome the fundamental limitation of missing 3D consistency in 2D diffusion models, our key insight is to introduce three syner...
[ { "created": "Thu, 13 Jun 2024 17:59:32 GMT", "version": "v1" } ]
2024-06-14
[ [ "Chen", "Jun-Kun", "" ], [ "Bulò", "Samuel Rota", "" ], [ "Müller", "Norman", "" ], [ "Porzi", "Lorenzo", "" ], [ "Kontschieder", "Peter", "" ], [ "Wang", "Yu-Xiong", "" ] ]
This paper proposes ConsistDreamer - a novel framework that lifts 2D diffusion models with 3D awareness and 3D consistency, thus enabling high-fidelity instruction-guided scene editing. To overcome the fundamental limitation of missing 3D consistency in 2D diffusion models, our key insight is to introduce three synerge...
1602.05231
Simon Thorne
Mahmood H. Shubbak, Simon Thorne
Development and Experimentation of a Software Tool for Identifying High Risk Spreadsheets for Auditing
22 pages, 11 Colour Figures, 4 Tables
Proc. 16th EuSpRIG Conf. "Spreadsheet Risk Management" (2015) pp47-78 ISBN: 978-1-905404-52-0
null
null
cs.SE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Heavy use of spreadsheets by organisations bears many potential risks such as errors, ambiguity, data loss, duplication, and fraud. In this paper these risks are briefly outlined along with their available mitigation methods such as: documentation, centralisation, auditing and user training. However, because of the l...
[ { "created": "Tue, 16 Feb 2016 22:29:47 GMT", "version": "v1" } ]
2016-02-22
[ [ "Shubbak", "Mahmood H.", "" ], [ "Thorne", "Simon", "" ] ]
Heavy use of spreadsheets by organisations bears many potential risks such as errors, ambiguity, data loss, duplication, and fraud. In this paper these risks are briefly outlined along with their available mitigation methods such as: documentation, centralisation, auditing and user training. However, because of the lar...
2210.12681
Atsuyuki Miyai
Atsuyuki Miyai, Qing Yu, Daiki Ikami, Go Irie, Kiyoharu Aizawa
Rethinking Rotation in Self-Supervised Contrastive Learning: Adaptive Positive or Negative Data Augmentation
Accepted at the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) 2023
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Rotation is frequently listed as a candidate for data augmentation in contrastive learning but seldom provides satisfactory improvements. We argue that this is because the rotated image is always treated as either positive or negative. The semantics of an image can be rotation-invariant or rotation-variant, so whethe...
[ { "created": "Sun, 23 Oct 2022 09:37:47 GMT", "version": "v1" }, { "created": "Thu, 24 Nov 2022 05:57:56 GMT", "version": "v2" } ]
2022-11-28
[ [ "Miyai", "Atsuyuki", "" ], [ "Yu", "Qing", "" ], [ "Ikami", "Daiki", "" ], [ "Irie", "Go", "" ], [ "Aizawa", "Kiyoharu", "" ] ]
Rotation is frequently listed as a candidate for data augmentation in contrastive learning but seldom provides satisfactory improvements. We argue that this is because the rotated image is always treated as either positive or negative. The semantics of an image can be rotation-invariant or rotation-variant, so whether ...
2105.08191
Gangadharan Esakki
Gangadharan Esakki, Andreas Panayides, Venkatesh Jatla, Marios Pattichis
Adaptive Video Encoding For Different Video Codecs
Video codecs, Video signal processing, Video coding, Video compression, Video quality, Video streaming, Adaptive video streaming, Versatile Video Coding, AV1, HEVC
IEEE Access 2021
10.1109/ACCESS.2021.3077313
null
cs.MM eess.IV
http://creativecommons.org/licenses/by-nc-sa/4.0/
By 2022, we expect video traffic to reach 82% of the total internet traffic. Undoubtedly, the abundance of video-driven applications will likely lead internet video traffic percentage to a further increase in the near future, enabled by associate advances in video devices' capabilities. In response to this ever-growi...
[ { "created": "Mon, 17 May 2021 23:06:20 GMT", "version": "v1" } ]
2021-05-19
[ [ "Esakki", "Gangadharan", "" ], [ "Panayides", "Andreas", "" ], [ "Jatla", "Venkatesh", "" ], [ "Pattichis", "Marios", "" ] ]
By 2022, we expect video traffic to reach 82% of the total internet traffic. Undoubtedly, the abundance of video-driven applications will likely lead internet video traffic percentage to a further increase in the near future, enabled by associate advances in video devices' capabilities. In response to this ever-growing...
1311.1757
Boleslaw Szymanski
Boleslaw K. Szymanski, Xin Lin, Andrea Asztalos, Sameet Sreenivasan
Failure dynamics of the global risk network
null
Scientific Reports 5:10998, June 18, 2015
10.1038/srep10998
null
cs.CY cs.SI physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Risks threatening modern societies form an intricately interconnected network that often underlies crisis situations. Yet, little is known about how risk materializations in distinct domains influence each other. Here we present an approach in which expert assessments of risks likelihoods and influence underlie a qua...
[ { "created": "Thu, 7 Nov 2013 17:26:09 GMT", "version": "v1" }, { "created": "Tue, 19 Nov 2013 02:57:29 GMT", "version": "v2" }, { "created": "Mon, 9 Dec 2013 04:10:35 GMT", "version": "v3" }, { "created": "Mon, 19 Jan 2015 16:38:48 GMT", "version": "v4" }, { "cre...
2016-05-03
[ [ "Szymanski", "Boleslaw K.", "" ], [ "Lin", "Xin", "" ], [ "Asztalos", "Andrea", "" ], [ "Sreenivasan", "Sameet", "" ] ]
Risks threatening modern societies form an intricately interconnected network that often underlies crisis situations. Yet, little is known about how risk materializations in distinct domains influence each other. Here we present an approach in which expert assessments of risks likelihoods and influence underlie a quant...
1903.01067
Antoni Rosinol
Antoni Rosinol, Torsten Sattler, Marc Pollefeys, Luca Carlone
Incremental Visual-Inertial 3D Mesh Generation with Structural Regularities
7 pages, 5 figures, ICRA accepted
IEEE Int. Conf. Robot. Autom. (ICRA), 2019
null
null
cs.CV cs.CG cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Visual-Inertial Odometry (VIO) algorithms typically rely on a point cloud representation of the scene that does not model the topology of the environment. A 3D mesh instead offers a richer, yet lightweight, model. Nevertheless, building a 3D mesh out of the sparse and noisy 3D landmarks triangulated by a VIO algorith...
[ { "created": "Mon, 4 Mar 2019 04:24:50 GMT", "version": "v1" }, { "created": "Mon, 29 Jul 2019 16:36:41 GMT", "version": "v2" } ]
2019-07-30
[ [ "Rosinol", "Antoni", "" ], [ "Sattler", "Torsten", "" ], [ "Pollefeys", "Marc", "" ], [ "Carlone", "Luca", "" ] ]
Visual-Inertial Odometry (VIO) algorithms typically rely on a point cloud representation of the scene that does not model the topology of the environment. A 3D mesh instead offers a richer, yet lightweight, model. Nevertheless, building a 3D mesh out of the sparse and noisy 3D landmarks triangulated by a VIO algorithm ...
2010.14957
Oliver Niggemann
Benedikt Eiteneuer and Nemanja Hranisavljevic and Oliver Niggemann
Dimensionality Reduction and Anomaly Detection for CPPS Data using Autoencoder
Copyright IEEE 2019
2019 IEEE International Conference on Industrial Technology (ICIT)
10.1109/ICIT.2019.8755116
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Unsupervised anomaly detection (AD) is a major topic in the field of Cyber-Physical Production Systems (CPPSs). A closely related concern is dimensionality reduction (DR) which is: 1) often used as a preprocessing step in an AD solution, 2) a sort of AD, if a measure of observation conformity to the learned data mani...
[ { "created": "Wed, 28 Oct 2020 13:16:58 GMT", "version": "v1" } ]
2020-10-29
[ [ "Eiteneuer", "Benedikt", "" ], [ "Hranisavljevic", "Nemanja", "" ], [ "Niggemann", "Oliver", "" ] ]
Unsupervised anomaly detection (AD) is a major topic in the field of Cyber-Physical Production Systems (CPPSs). A closely related concern is dimensionality reduction (DR) which is: 1) often used as a preprocessing step in an AD solution, 2) a sort of AD, if a measure of observation conformity to the learned data manifo...
1911.05640
F{\i}rat Tuna
Firat Tuna
Neural Network Processing Neural Networks: An efficient way to learn higher order functions
null
null
null
null
cs.LG cs.NE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Functions are rich in meaning and can be interpreted in a variety of ways. Neural networks were proven to be capable of approximating a large class of functions[1]. In this paper, we propose a new class of neural networks called "Neural Network Processing Neural Networks" (NNPNNs), which inputs neural networks and nu...
[ { "created": "Wed, 6 Nov 2019 19:15:34 GMT", "version": "v1" }, { "created": "Tue, 14 Jan 2020 23:11:27 GMT", "version": "v2" } ]
2020-01-16
[ [ "Tuna", "Firat", "" ] ]
Functions are rich in meaning and can be interpreted in a variety of ways. Neural networks were proven to be capable of approximating a large class of functions[1]. In this paper, we propose a new class of neural networks called "Neural Network Processing Neural Networks" (NNPNNs), which inputs neural networks and nume...
1810.11584
Rodrigo de Lamare
T. Cunha and R. C. de Lamare
Study of Joint Automatic Gain Control and MMSE Receiver Design Techniques for Quantized Multiuser Multiple-Antenna Systems
3 figures, 6 pages
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper presents the development of a joint optimization of an automatic gain control (AGC) algorithm and a linear \textit{minimum mean square error} (MMSE) receiver for multi-user multiple input multiple output (MU-MIMO) systems with coarsely quantized signals. The optimization of the AGC is based on the minimiza...
[ { "created": "Sat, 27 Oct 2018 02:57:59 GMT", "version": "v1" } ]
2018-10-30
[ [ "Cunha", "T.", "" ], [ "de Lamare", "R. C.", "" ] ]
This paper presents the development of a joint optimization of an automatic gain control (AGC) algorithm and a linear \textit{minimum mean square error} (MMSE) receiver for multi-user multiple input multiple output (MU-MIMO) systems with coarsely quantized signals. The optimization of the AGC is based on the minimizati...
2201.08901
Shashank Shekhar
Shashank Shekhar, Avinash Patel, Mrinal Haloi, Asif Salim
An Ensemble Model for Face Liveness Detection
Accepted and presented at MLDM 2022. To be published in Lattice journal
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
In this paper, we present a passive method to detect face presentation attack a.k.a face liveness detection using an ensemble deep learning technique. Face liveness detection is one of the key steps involved in user identity verification of customers during the online onboarding/transaction processes. During identity...
[ { "created": "Wed, 19 Jan 2022 12:43:39 GMT", "version": "v1" } ]
2022-01-25
[ [ "Shekhar", "Shashank", "" ], [ "Patel", "Avinash", "" ], [ "Haloi", "Mrinal", "" ], [ "Salim", "Asif", "" ] ]
In this paper, we present a passive method to detect face presentation attack a.k.a face liveness detection using an ensemble deep learning technique. Face liveness detection is one of the key steps involved in user identity verification of customers during the online onboarding/transaction processes. During identity v...
2108.09378
Alexandre Morgand
Alexandre Morgand (1) Mohamed Tamaazousti (2) and Adrien Bartoli (3) ((1) SLAMcore ltd, London, UK (2) Universit\'e Paris Saclay, CEA, LIST, Gif-sur-Yvette, France (3) IP-UMR 6602 - CNRS/UCA/CHU, Clermont-Ferrand, France)
A Multiple-View Geometric Model for Specularity Prediction on General Curved Surfaces
null
null
null
null
cs.CV cs.GR
http://creativecommons.org/licenses/by/4.0/
Specularity prediction is essential to many computer vision applications, giving important visual cues usable in Augmented Reality (AR), Simultaneous Localisation and Mapping (SLAM), 3D reconstruction and material modeling. However, it is a challenging task requiring numerous information from the scene including the ...
[ { "created": "Fri, 20 Aug 2021 21:21:26 GMT", "version": "v1" }, { "created": "Wed, 21 Dec 2022 19:09:26 GMT", "version": "v2" } ]
2022-12-23
[ [ "Morgand", "Alexandre", "" ], [ "Tamaazousti", "Mohamed", "" ], [ "Bartoli", "Adrien", "" ] ]
Specularity prediction is essential to many computer vision applications, giving important visual cues usable in Augmented Reality (AR), Simultaneous Localisation and Mapping (SLAM), 3D reconstruction and material modeling. However, it is a challenging task requiring numerous information from the scene including the ca...
1006.3128
Galen Reeves
Galen Reeves and Michael Gastpar
The Sampling Rate-Distortion Tradeoff for Sparsity Pattern Recovery in Compressed Sensing
null
IEEE Transactions on Information Theory, vo. 58, no. 10, pp. 3065-3092, May, 2012
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recovery of the sparsity pattern (or support) of an unknown sparse vector from a limited number of noisy linear measurements is an important problem in compressed sensing. In the high-dimensional setting, it is known that recovery with a vanishing fraction of errors is impossible if the measurement rate and the per-s...
[ { "created": "Wed, 16 Jun 2010 03:24:19 GMT", "version": "v1" }, { "created": "Mon, 25 Jun 2012 19:19:06 GMT", "version": "v2" } ]
2012-06-26
[ [ "Reeves", "Galen", "" ], [ "Gastpar", "Michael", "" ] ]
Recovery of the sparsity pattern (or support) of an unknown sparse vector from a limited number of noisy linear measurements is an important problem in compressed sensing. In the high-dimensional setting, it is known that recovery with a vanishing fraction of errors is impossible if the measurement rate and the per-sam...
2303.17338
Kaya Turgut
Kaya Turgut and Helin Dutagaci
Local region-learning modules for point cloud classification
null
Machine Vision and Applications 35, 16 (2024)
10.1007/s00138-023-01495-y
null
cs.CV
http://creativecommons.org/licenses/by-nc-nd/4.0/
Data organization via forming local regions is an integral part of deep learning networks that process 3D point clouds in a hierarchical manner. At each level, the point cloud is sampled to extract representative points and these points are used to be centers of local regions. The organization of local regions is of ...
[ { "created": "Thu, 30 Mar 2023 12:45:46 GMT", "version": "v1" }, { "created": "Tue, 19 Dec 2023 10:06:08 GMT", "version": "v2" } ]
2023-12-27
[ [ "Turgut", "Kaya", "" ], [ "Dutagaci", "Helin", "" ] ]
Data organization via forming local regions is an integral part of deep learning networks that process 3D point clouds in a hierarchical manner. At each level, the point cloud is sampled to extract representative points and these points are used to be centers of local regions. The organization of local regions is of co...
2010.11127
Gokcen Yilmaz Dayanikli
Gokcen Y. Dayanikli, Rees R. Hatch, Ryan M. Gerdes, Hongjie Wang, Regan Zane
Electromagnetic Sensor and Actuator Attacks on Power Converters for Electric Vehicles
Accepted by IEEE S&P Workshop on the Internet of Safe Things 2020
null
10.1109/SPW50608.2020.00032
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Alleviating range anxiety for electric vehicles (i.e., whether such vehicles can be relied upon to travel long distances in a timely manner) is critical for sustainable transportation. Extremely fast charging (XFC), whereby electric vehicles (EV) can be quickly recharged in the time frame it takes to refuel an intern...
[ { "created": "Wed, 21 Oct 2020 16:38:24 GMT", "version": "v1" } ]
2021-01-01
[ [ "Dayanikli", "Gokcen Y.", "" ], [ "Hatch", "Rees R.", "" ], [ "Gerdes", "Ryan M.", "" ], [ "Wang", "Hongjie", "" ], [ "Zane", "Regan", "" ] ]
Alleviating range anxiety for electric vehicles (i.e., whether such vehicles can be relied upon to travel long distances in a timely manner) is critical for sustainable transportation. Extremely fast charging (XFC), whereby electric vehicles (EV) can be quickly recharged in the time frame it takes to refuel an internal...
2305.00429
Rathindra Nath Dutta
Rathindra Nath Dutta, Subhojit Sarkar and Sasthi C. Ghosh
A Dynamic Obstacle Tracking Strategy for Proactive Handoffs in Millimeter-wave Networks
null
null
null
null
cs.NI eess.SP
http://creativecommons.org/licenses/by/4.0/
Stringent line-of-sight demands necessitated by the fast attenuating nature of millimeter waves (mmWaves) through obstacles pose one of the central problems of next generation wireless networks. These mmWave links are easily disrupted due to obstacles, including vehicles and pedestrians, which cause degradation in li...
[ { "created": "Sun, 30 Apr 2023 09:12:11 GMT", "version": "v1" }, { "created": "Wed, 12 Jul 2023 14:03:17 GMT", "version": "v2" } ]
2023-07-13
[ [ "Dutta", "Rathindra Nath", "" ], [ "Sarkar", "Subhojit", "" ], [ "Ghosh", "Sasthi C.", "" ] ]
Stringent line-of-sight demands necessitated by the fast attenuating nature of millimeter waves (mmWaves) through obstacles pose one of the central problems of next generation wireless networks. These mmWave links are easily disrupted due to obstacles, including vehicles and pedestrians, which cause degradation in link...
1703.09643
Tshilidzi Marwala
Bo Xing and Tshilidzi Marwala
Implications of the Fourth Industrial Age on Higher Education
Submitted to The Thinker
null
null
null
cs.CY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Higher education in the fourth industrial revolution, HE 4.0, is a complex, dialectical and exciting opportunity which can potentially transform society for the better. The fourth industrial revolution is powered by artificial intelligence and it will transform the workplace from tasks based characteristics to the hu...
[ { "created": "Fri, 17 Mar 2017 10:12:27 GMT", "version": "v1" } ]
2017-03-29
[ [ "Xing", "Bo", "" ], [ "Marwala", "Tshilidzi", "" ] ]
Higher education in the fourth industrial revolution, HE 4.0, is a complex, dialectical and exciting opportunity which can potentially transform society for the better. The fourth industrial revolution is powered by artificial intelligence and it will transform the workplace from tasks based characteristics to the huma...
1601.03481
Tirtharaj Dash
Tirtharaj Dash, H.S. Behera
A Fuzzy MLP Approach for Non-linear Pattern Classification
The final version of this paper has been published in "International Conference on Communication and Computing (ICC-2014)" [http://www.elsevierst.com/conference_book_download_chapter.php?cbid=86#chapter41]
In Proc: K.R. Venugopal, S.C. Lingareddy (eds.) International Conference on Communication and Computing (ICC- 2014), Bangalore, India (June 12-14, 2014), Computer Networks and Security, 314-323
null
null
cs.NE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In case of decision making problems, classification of pattern is a complex and crucial task. Pattern classification using multilayer perceptron (MLP) trained with back propagation learning becomes much complex with increase in number of layers, number of nodes and number of epochs and ultimate increases computationa...
[ { "created": "Sat, 19 Sep 2015 12:45:19 GMT", "version": "v1" } ]
2016-01-15
[ [ "Dash", "Tirtharaj", "" ], [ "Behera", "H. S.", "" ] ]
In case of decision making problems, classification of pattern is a complex and crucial task. Pattern classification using multilayer perceptron (MLP) trained with back propagation learning becomes much complex with increase in number of layers, number of nodes and number of epochs and ultimate increases computational ...
1903.03096
Pascal Lamblin
Eleni Triantafillou, Tyler Zhu, Vincent Dumoulin, Pascal Lamblin, Utku Evci, Kelvin Xu, Ross Goroshin, Carles Gelada, Kevin Swersky, Pierre-Antoine Manzagol, Hugo Larochelle
Meta-Dataset: A Dataset of Datasets for Learning to Learn from Few Examples
Code available at https://github.com/google-research/meta-dataset
International Conference on Learning Representations (2020)
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Few-shot classification refers to learning a classifier for new classes given only a few examples. While a plethora of models have emerged to tackle it, we find the procedure and datasets that are used to assess their progress lacking. To address this limitation, we propose Meta-Dataset: a new benchmark for training ...
[ { "created": "Thu, 7 Mar 2019 18:48:55 GMT", "version": "v1" }, { "created": "Tue, 22 Oct 2019 16:04:30 GMT", "version": "v2" }, { "created": "Fri, 14 Feb 2020 22:22:53 GMT", "version": "v3" }, { "created": "Wed, 8 Apr 2020 15:58:20 GMT", "version": "v4" } ]
2020-04-09
[ [ "Triantafillou", "Eleni", "" ], [ "Zhu", "Tyler", "" ], [ "Dumoulin", "Vincent", "" ], [ "Lamblin", "Pascal", "" ], [ "Evci", "Utku", "" ], [ "Xu", "Kelvin", "" ], [ "Goroshin", "Ross", "" ], [ "Gel...
Few-shot classification refers to learning a classifier for new classes given only a few examples. While a plethora of models have emerged to tackle it, we find the procedure and datasets that are used to assess their progress lacking. To address this limitation, we propose Meta-Dataset: a new benchmark for training an...
2406.08796
Janghoon Han
Janghoon Han, Changho Lee, Joongbo Shin, Stanley Jungkyu Choi, Honglak Lee, Kynghoon Bae
Deep Exploration of Cross-Lingual Zero-Shot Generalization in Instruction Tuning
Findings of ACL 2024 (Camera-ready), by Janghoon Han and Changho Lee, with equal contribution
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Instruction tuning has emerged as a powerful technique, significantly boosting zero-shot performance on unseen tasks. While recent work has explored cross-lingual generalization by applying instruction tuning to multilingual models, previous studies have primarily focused on English, with a limited exploration of non...
[ { "created": "Thu, 13 Jun 2024 04:10:17 GMT", "version": "v1" } ]
2024-06-14
[ [ "Han", "Janghoon", "" ], [ "Lee", "Changho", "" ], [ "Shin", "Joongbo", "" ], [ "Choi", "Stanley Jungkyu", "" ], [ "Lee", "Honglak", "" ], [ "Bae", "Kynghoon", "" ] ]
Instruction tuning has emerged as a powerful technique, significantly boosting zero-shot performance on unseen tasks. While recent work has explored cross-lingual generalization by applying instruction tuning to multilingual models, previous studies have primarily focused on English, with a limited exploration of non-E...
2405.19534
Angelica Chen
Angelica Chen, Sadhika Malladi, Lily H. Zhang, Xinyi Chen, Qiuyi Zhang, Rajesh Ranganath, Kyunghyun Cho
Preference Learning Algorithms Do Not Learn Preference Rankings
null
null
null
null
cs.LG cs.AI cs.CL
http://creativecommons.org/licenses/by/4.0/
Preference learning algorithms (e.g., RLHF and DPO) are frequently used to steer LLMs to produce generations that are more preferred by humans, but our understanding of their inner workings is still limited. In this work, we study the conventional wisdom that preference learning trains models to assign higher likelih...
[ { "created": "Wed, 29 May 2024 21:29:44 GMT", "version": "v1" } ]
2024-05-31
[ [ "Chen", "Angelica", "" ], [ "Malladi", "Sadhika", "" ], [ "Zhang", "Lily H.", "" ], [ "Chen", "Xinyi", "" ], [ "Zhang", "Qiuyi", "" ], [ "Ranganath", "Rajesh", "" ], [ "Cho", "Kyunghyun", "" ] ]
Preference learning algorithms (e.g., RLHF and DPO) are frequently used to steer LLMs to produce generations that are more preferred by humans, but our understanding of their inner workings is still limited. In this work, we study the conventional wisdom that preference learning trains models to assign higher likelihoo...
2209.06345
Chenhui Zhao
Chenhui Zhao and Xiang Li and Rabih Younes
Self-supervised Multi-Modal Video Forgery Attack Detection
null
null
null
null
cs.MM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Video forgery attack threatens the surveillance system by replacing the video captures with unrealistic synthesis, which can be powered by the latest augment reality and virtual reality technologies. From the machine perception aspect, visual objects often have RF signatures that are naturally synchronized with them ...
[ { "created": "Tue, 13 Sep 2022 23:41:26 GMT", "version": "v1" }, { "created": "Sat, 24 Dec 2022 00:28:18 GMT", "version": "v2" } ]
2022-12-27
[ [ "Zhao", "Chenhui", "" ], [ "Li", "Xiang", "" ], [ "Younes", "Rabih", "" ] ]
Video forgery attack threatens the surveillance system by replacing the video captures with unrealistic synthesis, which can be powered by the latest augment reality and virtual reality technologies. From the machine perception aspect, visual objects often have RF signatures that are naturally synchronized with them du...
2404.12984
Marek Wodzinski
Mateusz Daniol, Daria Hemmerling, Jakub Sikora, Pawel Jemiolo, Marek Wodzinski, Magdalena Wojcik-Pedziwiatr
Eye-tracking in Mixed Reality for Diagnosis of Neurodegenerative Diseases
null
null
null
null
cs.HC cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Parkinson's disease ranks as the second most prevalent neurodegenerative disorder globally. This research aims to develop a system leveraging Mixed Reality capabilities for tracking and assessing eye movements. In this paper, we present a medical scenario and outline the development of an application designed to capt...
[ { "created": "Fri, 19 Apr 2024 16:34:15 GMT", "version": "v1" }, { "created": "Mon, 3 Jun 2024 10:45:42 GMT", "version": "v2" } ]
2024-06-04
[ [ "Daniol", "Mateusz", "" ], [ "Hemmerling", "Daria", "" ], [ "Sikora", "Jakub", "" ], [ "Jemiolo", "Pawel", "" ], [ "Wodzinski", "Marek", "" ], [ "Wojcik-Pedziwiatr", "Magdalena", "" ] ]
Parkinson's disease ranks as the second most prevalent neurodegenerative disorder globally. This research aims to develop a system leveraging Mixed Reality capabilities for tracking and assessing eye movements. In this paper, we present a medical scenario and outline the development of an application designed to captur...
1205.2931
Douglas S Bridges
Douglas S Bridges (University of Canterbury)
Precompact Apartness Spaces
null
Logical Methods in Computer Science, Volume 8, Issue 2 (June 25, 2012) lmcs:1052
10.2168/LMCS-8(2:15)2012
null
cs.LO math.GN
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present a notion of precompactness, and study some of its properties, in the context of apartness spaces whose apartness structure is not necessarily induced by any uniform one. The presentation lies entirely with a Bishop-style constructive framework, and is a contribution to the ongoing development of the constr...
[ { "created": "Mon, 14 May 2012 02:29:38 GMT", "version": "v1" }, { "created": "Mon, 18 Jun 2012 17:06:29 GMT", "version": "v2" }, { "created": "Thu, 21 Jun 2012 21:43:49 GMT", "version": "v3" }, { "created": "Mon, 25 Jun 2012 11:20:03 GMT", "version": "v4" } ]
2015-07-01
[ [ "Bridges", "Douglas S", "", "University of Canterbury" ] ]
We present a notion of precompactness, and study some of its properties, in the context of apartness spaces whose apartness structure is not necessarily induced by any uniform one. The presentation lies entirely with a Bishop-style constructive framework, and is a contribution to the ongoing development of the construc...
2010.05324
Tharindu Ranasinghe Mr
Tharindu Ranasinghe, Marcos Zampieri
Multilingual Offensive Language Identification with Cross-lingual Embeddings
Accepted to EMNLP 2020
null
null
null
cs.CL cs.LG
http://creativecommons.org/licenses/by/4.0/
Offensive content is pervasive in social media and a reason for concern to companies and government organizations. Several studies have been recently published investigating methods to detect the various forms of such content (e.g. hate speech, cyberbulling, and cyberaggression). The clear majority of these studies d...
[ { "created": "Sun, 11 Oct 2020 19:17:24 GMT", "version": "v1" } ]
2020-10-13
[ [ "Ranasinghe", "Tharindu", "" ], [ "Zampieri", "Marcos", "" ] ]
Offensive content is pervasive in social media and a reason for concern to companies and government organizations. Several studies have been recently published investigating methods to detect the various forms of such content (e.g. hate speech, cyberbulling, and cyberaggression). The clear majority of these studies dea...
2302.00032
Deniz Oktay
Deniz Oktay, Mehran Mirramezani, Eder Medina, Ryan P. Adams
Neuromechanical Autoencoders: Learning to Couple Elastic and Neural Network Nonlinearity
ICLR 2023 Spotlight
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Intelligent biological systems are characterized by their embodiment in a complex environment and the intimate interplay between their nervous systems and the nonlinear mechanical properties of their bodies. This coordination, in which the dynamics of the motor system co-evolved to reduce the computational burden on ...
[ { "created": "Tue, 31 Jan 2023 19:04:28 GMT", "version": "v1" } ]
2023-02-02
[ [ "Oktay", "Deniz", "" ], [ "Mirramezani", "Mehran", "" ], [ "Medina", "Eder", "" ], [ "Adams", "Ryan P.", "" ] ]
Intelligent biological systems are characterized by their embodiment in a complex environment and the intimate interplay between their nervous systems and the nonlinear mechanical properties of their bodies. This coordination, in which the dynamics of the motor system co-evolved to reduce the computational burden on th...
1907.11496
Xin Wang
Xin Wang, Bo Wu, Yun Ye, Yueqi Zhong
Outfit Compatibility Prediction and Diagnosis with Multi-Layered Comparison Network
9 pages, 6 figures, Proceedings of the 27th ACM International Conference on Multimedia
null
10.1145/3343031.3350909
null
cs.CV cs.LG cs.MM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Existing works about fashion outfit compatibility focus on predicting the overall compatibility of a set of fashion items with their information from different modalities. However, there are few works explore how to explain the prediction, which limits the persuasiveness and effectiveness of the model. In this work, ...
[ { "created": "Fri, 26 Jul 2019 11:39:15 GMT", "version": "v1" }, { "created": "Thu, 22 Aug 2019 03:56:30 GMT", "version": "v2" } ]
2019-08-23
[ [ "Wang", "Xin", "" ], [ "Wu", "Bo", "" ], [ "Ye", "Yun", "" ], [ "Zhong", "Yueqi", "" ] ]
Existing works about fashion outfit compatibility focus on predicting the overall compatibility of a set of fashion items with their information from different modalities. However, there are few works explore how to explain the prediction, which limits the persuasiveness and effectiveness of the model. In this work, we...
1302.3591
Suzanne M. Mahoney
Suzanne M. Mahoney, Kathryn Blackmond Laskey
Network Engineering for Complex Belief Networks
Appears in Proceedings of the Twelfth Conference on Uncertainty in Artificial Intelligence (UAI1996)
null
null
UAI-P-1996-PG-389-396
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Like any large system development effort, the construction of a complex belief network model requires systems engineering to manage the design and construction process. We propose a rapid prototyping approach to network engineering. We describe criteria for identifying network modules and the use of "stubs" to repres...
[ { "created": "Wed, 13 Feb 2013 14:15:26 GMT", "version": "v1" } ]
2013-02-18
[ [ "Mahoney", "Suzanne M.", "" ], [ "Laskey", "Kathryn Blackmond", "" ] ]
Like any large system development effort, the construction of a complex belief network model requires systems engineering to manage the design and construction process. We propose a rapid prototyping approach to network engineering. We describe criteria for identifying network modules and the use of "stubs" to represen...
2207.06497
Qibang Liu
Qibang Liu and Muhao Chen and Robert E. Skelton
An extended ordinary state-based peridynamics for non-spherical horizons
19 pages, 9 figures
null
10.1016/j.cma.2022.115712
null
cs.CE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This work presents an extended ordinary state-based peridynamics (XOSBPD) model for the non-spherical horizons. Based on the OSBPD, we derive the XOSBPD by introducing the Lagrange multipliers to guarantee the non-local dilatation and non-local strain energy density (SED) are equal to local dilatation and local SED, ...
[ { "created": "Sat, 18 Jun 2022 20:13:21 GMT", "version": "v1" }, { "created": "Fri, 15 Jul 2022 06:11:49 GMT", "version": "v2" } ]
2022-11-09
[ [ "Liu", "Qibang", "" ], [ "Chen", "Muhao", "" ], [ "Skelton", "Robert E.", "" ] ]
This work presents an extended ordinary state-based peridynamics (XOSBPD) model for the non-spherical horizons. Based on the OSBPD, we derive the XOSBPD by introducing the Lagrange multipliers to guarantee the non-local dilatation and non-local strain energy density (SED) are equal to local dilatation and local SED, re...
2309.07400
Ziyu Guo
Ziyu Guo, Weiqin Zhao, Shujun Wang, and Lequan Yu
HIGT: Hierarchical Interaction Graph-Transformer for Whole Slide Image Analysis
Accepted by MICCAI2023; Code is available in https://github.com/HKU-MedAI/HIGT
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In computation pathology, the pyramid structure of gigapixel Whole Slide Images (WSIs) has recently been studied for capturing various information from individual cell interactions to tissue microenvironments. This hierarchical structure is believed to be beneficial for cancer diagnosis and prognosis tasks. However, ...
[ { "created": "Thu, 14 Sep 2023 03:04:06 GMT", "version": "v1" } ]
2023-09-15
[ [ "Guo", "Ziyu", "" ], [ "Zhao", "Weiqin", "" ], [ "Wang", "Shujun", "" ], [ "Yu", "Lequan", "" ] ]
In computation pathology, the pyramid structure of gigapixel Whole Slide Images (WSIs) has recently been studied for capturing various information from individual cell interactions to tissue microenvironments. This hierarchical structure is believed to be beneficial for cancer diagnosis and prognosis tasks. However, mo...
2110.12615
Quanquan Gu
Heyang Zhao and Dongruo Zhou and Quanquan Gu
Linear Contextual Bandits with Adversarial Corruptions
27 pages, 1 figure
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We study the linear contextual bandit problem in the presence of adversarial corruption, where the interaction between the player and a possibly infinite decision set is contaminated by an adversary that can corrupt the reward up to a corruption level $C$ measured by the sum of the largest alteration on rewards in ea...
[ { "created": "Mon, 25 Oct 2021 02:53:24 GMT", "version": "v1" } ]
2021-10-26
[ [ "Zhao", "Heyang", "" ], [ "Zhou", "Dongruo", "" ], [ "Gu", "Quanquan", "" ] ]
We study the linear contextual bandit problem in the presence of adversarial corruption, where the interaction between the player and a possibly infinite decision set is contaminated by an adversary that can corrupt the reward up to a corruption level $C$ measured by the sum of the largest alteration on rewards in each...