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2404.00341
Ahmed R. Sadik Dr.-Ing.
Ahmed R.Sadik, Bodo Urban
Ontology in Holonic Cooperative Manufacturing: A Solution to Share and Exchange the Knowledge
null
null
null
null
cs.AI
http://creativecommons.org/licenses/by/4.0/
Cooperative manufacturing is a new trend in industry, which depends on the existence of a collaborative robot. A collaborative robot is usually a light-weight robot which is capable of operating safely with a human co-worker in a shared work environment. During this cooperation, a vast amount of information is exchan...
[ { "created": "Sat, 30 Mar 2024 12:38:47 GMT", "version": "v1" } ]
2024-04-02
[ [ "Sadik", "Ahmed R.", "" ], [ "Urban", "Bodo", "" ] ]
Cooperative manufacturing is a new trend in industry, which depends on the existence of a collaborative robot. A collaborative robot is usually a light-weight robot which is capable of operating safely with a human co-worker in a shared work environment. During this cooperation, a vast amount of information is exchange...
2406.15202
Lucie Guillou
Lucie Guillou, Arnaud Sangnier, Nathalie Sznajder
Phase-Bounded Broadcast Networks over Topologies of Communication
long version of a paper accepted to appear at CONCUR 2024
null
null
null
cs.LO cs.MA
http://creativecommons.org/licenses/by/4.0/
We study networks of processes that all execute the same finite state protocol and that communicate through broadcasts. The processes are organized in a graph (a topology) and only the neighbors of a process in this graph can receive its broadcasts. The coverability problem asks, given a protocol and a state of the p...
[ { "created": "Fri, 21 Jun 2024 14:43:23 GMT", "version": "v1" }, { "created": "Thu, 4 Jul 2024 11:02:35 GMT", "version": "v2" } ]
2024-07-08
[ [ "Guillou", "Lucie", "" ], [ "Sangnier", "Arnaud", "" ], [ "Sznajder", "Nathalie", "" ] ]
We study networks of processes that all execute the same finite state protocol and that communicate through broadcasts. The processes are organized in a graph (a topology) and only the neighbors of a process in this graph can receive its broadcasts. The coverability problem asks, given a protocol and a state of the pro...
2305.08197
Ayman Elhalwagy
Ayman Elhalwagy and Tatiana Kalganova
A Dataset Fusion Algorithm for Generalised Anomaly Detection in Homogeneous Periodic Time Series Datasets
This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible
null
null
null
cs.LG cs.AI eess.SP
http://creativecommons.org/licenses/by/4.0/
The generalisation of Neural Networks (NN) to multiple datasets is often overlooked in literature due to NNs typically being optimised for specific data sources. This becomes especially challenging in time-series-based multi-dataset models due to difficulties in fusing sequential data from different sensors and colle...
[ { "created": "Sun, 14 May 2023 16:24:09 GMT", "version": "v1" } ]
2023-05-16
[ [ "Elhalwagy", "Ayman", "" ], [ "Kalganova", "Tatiana", "" ] ]
The generalisation of Neural Networks (NN) to multiple datasets is often overlooked in literature due to NNs typically being optimised for specific data sources. This becomes especially challenging in time-series-based multi-dataset models due to difficulties in fusing sequential data from different sensors and collect...
2203.00815
Ola Alkhatib Ms.
Ayman Alahmar and Ola Alkhatib
Computerization of Clinical Pathways: A Literature Review and Directions for Future Research
12 pages, 4 figures, 3 tables
2nd. International Symposium of Scientific Research and Innovative Studies (ISSRIS'22), March 2-5, 2022
null
null
cs.AI
http://creativecommons.org/licenses/by/4.0/
Clinical Pathways (CP) are medical management plans developed to standardize patient treatment activities, optimize resource usage, reduce expenses, and improve the quality of healthcare services. Most CPs currently in use are paper-based documents (i.e., not computerized). CP computerization has been an active resea...
[ { "created": "Wed, 2 Mar 2022 01:38:40 GMT", "version": "v1" } ]
2022-03-03
[ [ "Alahmar", "Ayman", "" ], [ "Alkhatib", "Ola", "" ] ]
Clinical Pathways (CP) are medical management plans developed to standardize patient treatment activities, optimize resource usage, reduce expenses, and improve the quality of healthcare services. Most CPs currently in use are paper-based documents (i.e., not computerized). CP computerization has been an active researc...
1807.08934
Vinod Kumar Chauhan
Vinod Kumar Chauhan, Anuj Sharma, Kalpana Dahiya
SAAGs: Biased Stochastic Variance Reduction Methods for Large-scale Learning
Final journal version. Appl Intell (2019)
null
10.1007/s10489-019-01450-3
null
cs.LG cs.AI stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Stochastic approximation is one of the effective approach to deal with the large-scale machine learning problems and the recent research has focused on reduction of variance, caused by the noisy approximations of the gradients. In this paper, we have proposed novel variants of SAAG-I and II (Stochastic Average Adjust...
[ { "created": "Tue, 24 Jul 2018 07:36:21 GMT", "version": "v1" }, { "created": "Mon, 24 Dec 2018 10:04:22 GMT", "version": "v2" }, { "created": "Sat, 6 Apr 2019 05:04:23 GMT", "version": "v3" } ]
2019-04-09
[ [ "Chauhan", "Vinod Kumar", "" ], [ "Sharma", "Anuj", "" ], [ "Dahiya", "Kalpana", "" ] ]
Stochastic approximation is one of the effective approach to deal with the large-scale machine learning problems and the recent research has focused on reduction of variance, caused by the noisy approximations of the gradients. In this paper, we have proposed novel variants of SAAG-I and II (Stochastic Average Adjusted...
2312.00622
Jose Pablo Folch
Jose Pablo Folch, James Odgers, Shiqiang Zhang, Robert M Lee, Behrang Shafei, David Walz, Calvin Tsay, Mark van der Wilk, Ruth Misener
Practical Path-based Bayesian Optimization
6 main pages, 12 with references and appendix. 4 figures, 2 tables. To appear in NeurIPS 2023 Workshop on Adaptive Experimental Design and Active Learning in the Real World
NeurIPS 2023 Workshop on Adaptive Experimental Design and Active Learning in the Real World
null
null
cs.LG math.OC stat.ME
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
There has been a surge in interest in data-driven experimental design with applications to chemical engineering and drug manufacturing. Bayesian optimization (BO) has proven to be adaptable to such cases, since we can model the reactions of interest as expensive black-box functions. Sometimes, the cost of this black-...
[ { "created": "Fri, 1 Dec 2023 14:39:11 GMT", "version": "v1" } ]
2023-12-04
[ [ "Folch", "Jose Pablo", "" ], [ "Odgers", "James", "" ], [ "Zhang", "Shiqiang", "" ], [ "Lee", "Robert M", "" ], [ "Shafei", "Behrang", "" ], [ "Walz", "David", "" ], [ "Tsay", "Calvin", "" ], [ "van...
There has been a surge in interest in data-driven experimental design with applications to chemical engineering and drug manufacturing. Bayesian optimization (BO) has proven to be adaptable to such cases, since we can model the reactions of interest as expensive black-box functions. Sometimes, the cost of this black-bo...
1904.12768
Roy Dong
Tyler Westenbroek and Roy Dong and Lillian J. Ratliff and S. Shankar Sastry
Competitive Statistical Estimation with Strategic Data Sources
accepted in the IEEE Transactions on Automatic Control
null
null
null
cs.GT stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In recent years, data has played an increasingly important role in the economy as a good in its own right. In many settings, data aggregators cannot directly verify the quality of the data they purchase, nor the effort exerted by data sources when creating the data. Recent work has explored mechanisms to ensure that ...
[ { "created": "Mon, 29 Apr 2019 15:26:05 GMT", "version": "v1" } ]
2019-04-30
[ [ "Westenbroek", "Tyler", "" ], [ "Dong", "Roy", "" ], [ "Ratliff", "Lillian J.", "" ], [ "Sastry", "S. Shankar", "" ] ]
In recent years, data has played an increasingly important role in the economy as a good in its own right. In many settings, data aggregators cannot directly verify the quality of the data they purchase, nor the effort exerted by data sources when creating the data. Recent work has explored mechanisms to ensure that th...
2302.01772
Youssef Allouah
Youssef Allouah, Sadegh Farhadkhani, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot, John Stephan
Fixing by Mixing: A Recipe for Optimal Byzantine ML under Heterogeneity
Accepted paper at AISTATS 2023
null
null
null
cs.LG cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Byzantine machine learning (ML) aims to ensure the resilience of distributed learning algorithms to misbehaving (or Byzantine) machines. Although this problem received significant attention, prior works often assume the data held by the machines to be homogeneous, which is seldom true in practical settings. Data hete...
[ { "created": "Fri, 3 Feb 2023 14:30:25 GMT", "version": "v1" } ]
2023-02-06
[ [ "Allouah", "Youssef", "" ], [ "Farhadkhani", "Sadegh", "" ], [ "Guerraoui", "Rachid", "" ], [ "Gupta", "Nirupam", "" ], [ "Pinot", "Rafael", "" ], [ "Stephan", "John", "" ] ]
Byzantine machine learning (ML) aims to ensure the resilience of distributed learning algorithms to misbehaving (or Byzantine) machines. Although this problem received significant attention, prior works often assume the data held by the machines to be homogeneous, which is seldom true in practical settings. Data hetero...
2403.02738
Congzhi Zhang
Congzhi Zhang, Linhai Zhang, Jialong Wu, Deyu Zhou, Yulan He
Causal Prompting: Debiasing Large Language Model Prompting based on Front-Door Adjustment
null
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Despite the notable advancements of existing prompting methods, such as In-Context Learning and Chain-of-Thought for Large Language Models (LLMs), they still face challenges related to various biases. Traditional debiasing methods primarily focus on the model training stage, including approaches based on data augment...
[ { "created": "Tue, 5 Mar 2024 07:47:34 GMT", "version": "v1" }, { "created": "Wed, 22 May 2024 16:21:38 GMT", "version": "v2" } ]
2024-05-24
[ [ "Zhang", "Congzhi", "" ], [ "Zhang", "Linhai", "" ], [ "Wu", "Jialong", "" ], [ "Zhou", "Deyu", "" ], [ "He", "Yulan", "" ] ]
Despite the notable advancements of existing prompting methods, such as In-Context Learning and Chain-of-Thought for Large Language Models (LLMs), they still face challenges related to various biases. Traditional debiasing methods primarily focus on the model training stage, including approaches based on data augmentat...
2403.05600
Ha Manh Bui
Ha Manh Bui and Anqi Liu
Density-Regression: Efficient and Distance-Aware Deep Regressor for Uncertainty Estimation under Distribution Shifts
International Conference on Artificial Intelligence and Statistics, 2024
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Morden deep ensembles technique achieves strong uncertainty estimation performance by going through multiple forward passes with different models. This is at the price of a high storage space and a slow speed in the inference (test) time. To address this issue, we propose Density-Regression, a method that leverages t...
[ { "created": "Thu, 7 Mar 2024 23:20:34 GMT", "version": "v1" } ]
2024-03-13
[ [ "Bui", "Ha Manh", "" ], [ "Liu", "Anqi", "" ] ]
Morden deep ensembles technique achieves strong uncertainty estimation performance by going through multiple forward passes with different models. This is at the price of a high storage space and a slow speed in the inference (test) time. To address this issue, we propose Density-Regression, a method that leverages the...
2402.18101
Qiao Wang
Qiao Wang and Zheng Yuan
Assessing the Efficacy of Grammar Error Correction: A Human Evaluation Approach in the Japanese Context
2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
In this study, we evaluated the performance of the state-of-the-art sequence tagging grammar error detection and correction model (SeqTagger) using Japanese university students' writing samples. With an automatic annotation toolkit, ERRANT, we first evaluated SeqTagger's performance on error correction with human exp...
[ { "created": "Wed, 28 Feb 2024 06:43:43 GMT", "version": "v1" }, { "created": "Thu, 29 Feb 2024 10:53:40 GMT", "version": "v2" } ]
2024-03-01
[ [ "Wang", "Qiao", "" ], [ "Yuan", "Zheng", "" ] ]
In this study, we evaluated the performance of the state-of-the-art sequence tagging grammar error detection and correction model (SeqTagger) using Japanese university students' writing samples. With an automatic annotation toolkit, ERRANT, we first evaluated SeqTagger's performance on error correction with human exper...
2207.09019
Jingwang Ling
Jingwang Ling, Zhibo Wang, Ming Lu, Quan Wang, Chen Qian, Feng Xu
Structure-aware Editable Morphable Model for 3D Facial Detail Animation and Manipulation
ECCV 2022
null
null
null
cs.CV cs.GR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Morphable models are essential for the statistical modeling of 3D faces. Previous works on morphable models mostly focus on large-scale facial geometry but ignore facial details. This paper augments morphable models in representing facial details by learning a Structure-aware Editable Morphable Model (SEMM). SEMM int...
[ { "created": "Tue, 19 Jul 2022 01:48:07 GMT", "version": "v1" } ]
2022-07-20
[ [ "Ling", "Jingwang", "" ], [ "Wang", "Zhibo", "" ], [ "Lu", "Ming", "" ], [ "Wang", "Quan", "" ], [ "Qian", "Chen", "" ], [ "Xu", "Feng", "" ] ]
Morphable models are essential for the statistical modeling of 3D faces. Previous works on morphable models mostly focus on large-scale facial geometry but ignore facial details. This paper augments morphable models in representing facial details by learning a Structure-aware Editable Morphable Model (SEMM). SEMM intro...
1803.10195
Tomas Petricek
Tomas Petricek (The Alan Turing Institute, United Kingdom)
What we talk about when we talk about monads
null
The Art, Science, and Engineering of Programming, 2018, Vol. 2, Issue 3, Article 12
10.22152/programming-journal.org/2018/2/12
null
cs.PL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Computer science provides an in-depth understanding of technical aspects of programming concepts, but if we want to understand how programming concepts evolve, how programmers think and talk about them and how they are used in practice, we need to consider a broader perspective that includes historical, philosophical...
[ { "created": "Tue, 27 Mar 2018 17:35:50 GMT", "version": "v1" } ]
2018-03-28
[ [ "Petricek", "Tomas", "", "The Alan Turing Institute, United Kingdom" ] ]
Computer science provides an in-depth understanding of technical aspects of programming concepts, but if we want to understand how programming concepts evolve, how programmers think and talk about them and how they are used in practice, we need to consider a broader perspective that includes historical, philosophical a...
2307.03110
Arjun Sridhar
Bhavna Gopal, Arjun Sridhar, Tunhou Zhang and Yiran Chen
LISSNAS: Locality-based Iterative Search Space Shrinkage for Neural Architecture Search
null
IJCAI 2023
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Search spaces hallmark the advancement of Neural Architecture Search (NAS). Large and complex search spaces with versatile building operators and structures provide more opportunities to brew promising architectures, yet pose severe challenges on efficient exploration and exploitation. Subsequently, several search sp...
[ { "created": "Thu, 6 Jul 2023 16:28:51 GMT", "version": "v1" } ]
2023-07-07
[ [ "Gopal", "Bhavna", "" ], [ "Sridhar", "Arjun", "" ], [ "Zhang", "Tunhou", "" ], [ "Chen", "Yiran", "" ] ]
Search spaces hallmark the advancement of Neural Architecture Search (NAS). Large and complex search spaces with versatile building operators and structures provide more opportunities to brew promising architectures, yet pose severe challenges on efficient exploration and exploitation. Subsequently, several search spac...
2212.07495
Tooba Imtiaz
Tooba Imtiaz, Morgan Kohler, Jared Miller, Zifeng Wang, Mario Sznaier, Octavia Camps, Jennifer Dy
SAIF: Sparse Adversarial and Imperceptible Attack Framework
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Adversarial attacks hamper the decision-making ability of neural networks by perturbing the input signal. The addition of calculated small distortion to images, for instance, can deceive a well-trained image classification network. In this work, we propose a novel attack technique called Sparse Adversarial and Interp...
[ { "created": "Wed, 14 Dec 2022 20:28:50 GMT", "version": "v1" }, { "created": "Wed, 6 Dec 2023 10:55:40 GMT", "version": "v2" } ]
2023-12-07
[ [ "Imtiaz", "Tooba", "" ], [ "Kohler", "Morgan", "" ], [ "Miller", "Jared", "" ], [ "Wang", "Zifeng", "" ], [ "Sznaier", "Mario", "" ], [ "Camps", "Octavia", "" ], [ "Dy", "Jennifer", "" ] ]
Adversarial attacks hamper the decision-making ability of neural networks by perturbing the input signal. The addition of calculated small distortion to images, for instance, can deceive a well-trained image classification network. In this work, we propose a novel attack technique called Sparse Adversarial and Interpre...
2003.06959
Pei Xu
Pei Xu and Ioannis Karamouzas
PFPN: Continuous Control of Physically Simulated Characters using Particle Filtering Policy Network
Motion, Interaction and Games (MIG '21)
null
10.1145/3487983.3488301
null
cs.LG cs.GR stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Data-driven methods for physics-based character control using reinforcement learning have been successfully applied to generate high-quality motions. However, existing approaches typically rely on Gaussian distributions to represent the action policy, which can prematurely commit to suboptimal actions when solving hi...
[ { "created": "Mon, 16 Mar 2020 00:35:36 GMT", "version": "v1" }, { "created": "Sat, 3 Oct 2020 15:27:37 GMT", "version": "v2" }, { "created": "Tue, 13 Oct 2020 22:49:38 GMT", "version": "v3" }, { "created": "Fri, 1 Oct 2021 14:09:40 GMT", "version": "v4" } ]
2021-10-06
[ [ "Xu", "Pei", "" ], [ "Karamouzas", "Ioannis", "" ] ]
Data-driven methods for physics-based character control using reinforcement learning have been successfully applied to generate high-quality motions. However, existing approaches typically rely on Gaussian distributions to represent the action policy, which can prematurely commit to suboptimal actions when solving high...
1406.0173
Ljubisa Stankovic
Ljubisa Stankovic
On the ISAR Image Analysis and Recovery with Unavailable or Heavily Corrupted Data
9 pages, 6 figures, submitted to the IEEE Transactions on Aerospace and Electronic Systems
null
10.1109/TAES.2015.140413
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Common ISAR radar images and signals can be reconstructed from much fewer samples than the sampling theorem requires since they are usually sparse. Unavailable randomly positioned samples can result from heavily corrupted parts of the signal. Since these samples can be omitted and declared as unavailable, the applica...
[ { "created": "Sun, 1 Jun 2014 15:46:35 GMT", "version": "v1" } ]
2016-11-17
[ [ "Stankovic", "Ljubisa", "" ] ]
Common ISAR radar images and signals can be reconstructed from much fewer samples than the sampling theorem requires since they are usually sparse. Unavailable randomly positioned samples can result from heavily corrupted parts of the signal. Since these samples can be omitted and declared as unavailable, the applicati...
1112.2336
Nasrin Mazaheri
Nasrin Mazaheri Soudani and Ahmad Baraani-Dastgerdi
The Spatial Nearest Neighbor Skyline Queries
15 pages, 14 figures, Journal:International Journal of Database Management Systems (IJDMS)
International Journal of Database Management Systems (IJDMS), Vol.3, No.4, November 2011, 65-79
null
null
cs.DB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
User preference queries are very important in spatial databases. With the help of these queries, one can found best location among points saved in database. In many situation users evaluate quality of a location with its distance from its nearest neighbor among a special set of points. There has been less attention a...
[ { "created": "Sun, 11 Dec 2011 08:43:54 GMT", "version": "v1" } ]
2011-12-13
[ [ "Soudani", "Nasrin Mazaheri", "" ], [ "Baraani-Dastgerdi", "Ahmad", "" ] ]
User preference queries are very important in spatial databases. With the help of these queries, one can found best location among points saved in database. In many situation users evaluate quality of a location with its distance from its nearest neighbor among a special set of points. There has been less attention abo...
2308.12111
Chao Tian
Chao Tian, Zikun Zhou, Yuqing Huang, Gaojun Li, and Zhenyu He
Cross-Modality Proposal-guided Feature Mining for Unregistered RGB-Thermal Pedestrian Detection
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
RGB-Thermal (RGB-T) pedestrian detection aims to locate the pedestrians in RGB-T image pairs to exploit the complementation between the two modalities for improving detection robustness in extreme conditions. Most existing algorithms assume that the RGB-T image pairs are well registered, while in the real world they ...
[ { "created": "Wed, 23 Aug 2023 12:58:51 GMT", "version": "v1" } ]
2023-08-24
[ [ "Tian", "Chao", "" ], [ "Zhou", "Zikun", "" ], [ "Huang", "Yuqing", "" ], [ "Li", "Gaojun", "" ], [ "He", "Zhenyu", "" ] ]
RGB-Thermal (RGB-T) pedestrian detection aims to locate the pedestrians in RGB-T image pairs to exploit the complementation between the two modalities for improving detection robustness in extreme conditions. Most existing algorithms assume that the RGB-T image pairs are well registered, while in the real world they ar...
2202.10313
Alexander Breuer
Alexander Breuer, Alexander Heinecke
Next-Generation Local Time Stepping for the ADER-DG Finite Element Method
null
null
null
null
cs.DC cs.CE
http://creativecommons.org/licenses/by/4.0/
High-frequency ground motion simulations pose a grand challenge in computational seismology. Two main factors drive this challenge. First, to account for higher frequencies, we have to extend our numerical models, e.g., by considering anelasticity, or by including mountain topography. Second, even if we were able to ...
[ { "created": "Mon, 21 Feb 2022 15:36:05 GMT", "version": "v1" } ]
2022-02-22
[ [ "Breuer", "Alexander", "" ], [ "Heinecke", "Alexander", "" ] ]
High-frequency ground motion simulations pose a grand challenge in computational seismology. Two main factors drive this challenge. First, to account for higher frequencies, we have to extend our numerical models, e.g., by considering anelasticity, or by including mountain topography. Second, even if we were able to ke...
2402.08171
David Widder
David Gray Widder
Epistemic Power in AI Ethics Labor: Legitimizing Located Complaints
Accepted to ACM FAccT 2024
null
10.1145/3630106.3658973
null
cs.CY
http://creativecommons.org/licenses/by-nc-sa/4.0/
What counts as legitimate AI ethics labor, and consequently, what are the epistemic terms on which AI ethics claims are rendered legitimate? Based on 75 interviews with technologists including researchers, developers, open source contributors, and activists, this paper explores the various epistemic bases from which ...
[ { "created": "Tue, 13 Feb 2024 02:07:03 GMT", "version": "v1" }, { "created": "Wed, 10 Apr 2024 01:27:21 GMT", "version": "v2" }, { "created": "Thu, 11 Apr 2024 01:19:03 GMT", "version": "v3" }, { "created": "Wed, 17 Apr 2024 18:34:09 GMT", "version": "v4" } ]
2024-04-19
[ [ "Widder", "David Gray", "" ] ]
What counts as legitimate AI ethics labor, and consequently, what are the epistemic terms on which AI ethics claims are rendered legitimate? Based on 75 interviews with technologists including researchers, developers, open source contributors, and activists, this paper explores the various epistemic bases from which AI...
1909.11851
Christian Szegedy
Dennis Lee, Christian Szegedy, Markus N. Rabe, Sarah M. Loos and Kshitij Bansal
Mathematical Reasoning in Latent Space
null
null
null
null
cs.LG cs.AI stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We design and conduct a simple experiment to study whether neural networks can perform several steps of approximate reasoning in a fixed dimensional latent space. The set of rewrites (i.e. transformations) that can be successfully performed on a statement represents essential semantic features of the statement. We ca...
[ { "created": "Thu, 26 Sep 2019 02:33:07 GMT", "version": "v1" } ]
2019-09-27
[ [ "Lee", "Dennis", "" ], [ "Szegedy", "Christian", "" ], [ "Rabe", "Markus N.", "" ], [ "Loos", "Sarah M.", "" ], [ "Bansal", "Kshitij", "" ] ]
We design and conduct a simple experiment to study whether neural networks can perform several steps of approximate reasoning in a fixed dimensional latent space. The set of rewrites (i.e. transformations) that can be successfully performed on a statement represents essential semantic features of the statement. We can ...
2312.05557
Wenbo Zhu
W. Zhu, H. D. Tuan, E. Dutkiewicz, Y. Fang, H. V. Poor, L. Hanzo
Long-Term Rate-Fairness-Aware Beamforming Based Massive MIMO Systems
null
null
null
null
cs.IT eess.SP math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This is the first treatise on multi-user (MU) beamforming designed for achieving long-term rate-fairness in fulldimensional MU massive multi-input multi-output (m-MIMO) systems. Explicitly, based on the channel covariances, which can be assumed to be known beforehand, we address this problem by optimizing the followi...
[ { "created": "Sat, 9 Dec 2023 12:10:18 GMT", "version": "v1" } ]
2023-12-12
[ [ "Zhu", "W.", "" ], [ "Tuan", "H. D.", "" ], [ "Dutkiewicz", "E.", "" ], [ "Fang", "Y.", "" ], [ "Poor", "H. V.", "" ], [ "Hanzo", "L.", "" ] ]
This is the first treatise on multi-user (MU) beamforming designed for achieving long-term rate-fairness in fulldimensional MU massive multi-input multi-output (m-MIMO) systems. Explicitly, based on the channel covariances, which can be assumed to be known beforehand, we address this problem by optimizing the following...
2402.13823
Andreas Vogelsang
Andreas Vogelsang, Jannik Fischbach
Using Large Language Models for Natural Language Processing Tasks in Requirements Engineering: A Systematic Guideline
null
null
null
null
cs.SE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Large Language Models (LLMs) are the cornerstone in automating Requirements Engineering (RE) tasks, underpinning recent advancements in the field. Their pre-trained comprehension of natural language is pivotal for effectively tailoring them to specific RE tasks. However, selecting an appropriate LLM from a myriad of ...
[ { "created": "Wed, 21 Feb 2024 14:00:52 GMT", "version": "v1" }, { "created": "Thu, 22 Feb 2024 12:23:06 GMT", "version": "v2" }, { "created": "Wed, 15 May 2024 12:57:58 GMT", "version": "v3" } ]
2024-05-16
[ [ "Vogelsang", "Andreas", "" ], [ "Fischbach", "Jannik", "" ] ]
Large Language Models (LLMs) are the cornerstone in automating Requirements Engineering (RE) tasks, underpinning recent advancements in the field. Their pre-trained comprehension of natural language is pivotal for effectively tailoring them to specific RE tasks. However, selecting an appropriate LLM from a myriad of ex...
1302.4549
Nir Ailon
Nir Ailon and Yudong Chen and Xu Huan
Breaking the Small Cluster Barrier of Graph Clustering
null
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper investigates graph clustering in the planted cluster model in the presence of {\em small clusters}. Traditional results dictate that for an algorithm to provably correctly recover the clusters, {\em all} clusters must be sufficiently large (in particular, $\tilde{\Omega}(\sqrt{n})$ where $n$ is the number ...
[ { "created": "Tue, 19 Feb 2013 09:21:09 GMT", "version": "v1" }, { "created": "Wed, 20 Feb 2013 08:35:39 GMT", "version": "v2" } ]
2013-02-21
[ [ "Ailon", "Nir", "" ], [ "Chen", "Yudong", "" ], [ "Huan", "Xu", "" ] ]
This paper investigates graph clustering in the planted cluster model in the presence of {\em small clusters}. Traditional results dictate that for an algorithm to provably correctly recover the clusters, {\em all} clusters must be sufficiently large (in particular, $\tilde{\Omega}(\sqrt{n})$ where $n$ is the number of...
1303.1264
Radim Belohlavek
Radim Belohlavek and Vilem Vychodil
Discovery of factors in matrices with grades
null
null
null
null
cs.LG cs.NA
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present an approach to decomposition and factor analysis of matrices with ordinal data. The matrix entries are grades to which objects represented by rows satisfy attributes represented by columns, e.g. grades to which an image is red, a product has a given feature, or a person performs well in a test. We assume t...
[ { "created": "Wed, 6 Mar 2013 07:58:14 GMT", "version": "v1" } ]
2013-03-07
[ [ "Belohlavek", "Radim", "" ], [ "Vychodil", "Vilem", "" ] ]
We present an approach to decomposition and factor analysis of matrices with ordinal data. The matrix entries are grades to which objects represented by rows satisfy attributes represented by columns, e.g. grades to which an image is red, a product has a given feature, or a person performs well in a test. We assume tha...
1806.02023
Jia-Hong Lee
Jia-Hong Lee, Yi-Ming Chan, Ting-Yen Chen, and Chu-Song Chen
Joint Estimation of Age and Gender from Unconstrained Face Images using Lightweight Multi-task CNN for Mobile Applications
To publish in the IEEE first International Conference on Multimedia Information Processing and Retrieval, 2018. (IEEE MIPR 2018)
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Automatic age and gender classification based on unconstrained images has become essential techniques on mobile devices. With limited computing power, how to develop a robust system becomes a challenging task. In this paper, we present an efficient convolutional neural network (CNN) called lightweight multi-task CNN ...
[ { "created": "Wed, 6 Jun 2018 06:22:16 GMT", "version": "v1" } ]
2018-06-07
[ [ "Lee", "Jia-Hong", "" ], [ "Chan", "Yi-Ming", "" ], [ "Chen", "Ting-Yen", "" ], [ "Chen", "Chu-Song", "" ] ]
Automatic age and gender classification based on unconstrained images has become essential techniques on mobile devices. With limited computing power, how to develop a robust system becomes a challenging task. In this paper, we present an efficient convolutional neural network (CNN) called lightweight multi-task CNN fo...
1708.01341
Rui Han
Rui Han, Fan Zhang, Zhentao Wang
AccurateML: Information-aggregation-based Approximate Processing for Fast and Accurate Machine Learning on MapReduce
9 pages, 9 figures
null
null
838-846
cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The growing demands of processing massive datasets have promoted irresistible trends of running machine learning applications on MapReduce. When processing large input data, it is often of greater values to produce fast and accurate enough approximate results than slow exact results. Existing techniques produce appro...
[ { "created": "Fri, 4 Aug 2017 00:57:57 GMT", "version": "v1" } ]
2017-08-07
[ [ "Han", "Rui", "" ], [ "Zhang", "Fan", "" ], [ "Wang", "Zhentao", "" ] ]
The growing demands of processing massive datasets have promoted irresistible trends of running machine learning applications on MapReduce. When processing large input data, it is often of greater values to produce fast and accurate enough approximate results than slow exact results. Existing techniques produce approxi...
1908.01478
Yi-Hsiang Chang
Yi-Hsiang Chang, Kuan-Yu Chang, Henry Kuo, Chun-Yi Lee
Reusability and Transferability of Macro Actions for Reinforcement Learning
null
null
10.1145/3514260
null
cs.NE cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Conventional reinforcement learning (RL) typically determines an appropriate primitive action at each timestep. However, by using a proper macro action, defined as a sequence of primitive actions, an agent is able to bypass intermediate states to a farther state and facilitate its learning procedure. The problem we w...
[ { "created": "Mon, 5 Aug 2019 05:59:40 GMT", "version": "v1" }, { "created": "Sat, 7 Nov 2020 06:04:26 GMT", "version": "v2" }, { "created": "Thu, 28 Apr 2022 12:43:25 GMT", "version": "v3" } ]
2022-04-29
[ [ "Chang", "Yi-Hsiang", "" ], [ "Chang", "Kuan-Yu", "" ], [ "Kuo", "Henry", "" ], [ "Lee", "Chun-Yi", "" ] ]
Conventional reinforcement learning (RL) typically determines an appropriate primitive action at each timestep. However, by using a proper macro action, defined as a sequence of primitive actions, an agent is able to bypass intermediate states to a farther state and facilitate its learning procedure. The problem we wou...
2203.07656
Yuqian Fu
Yuqian Fu, Yu Xie, Yanwei Fu, Jingjing Chen, Yu-Gang Jiang
Wave-SAN: Wavelet based Style Augmentation Network for Cross-Domain Few-Shot Learning
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Previous few-shot learning (FSL) works mostly are limited to natural images of general concepts and categories. These works assume very high visual similarity between the source and target classes. In contrast, the recently proposed cross-domain few-shot learning (CD-FSL) aims at transferring knowledge from general n...
[ { "created": "Tue, 15 Mar 2022 05:36:41 GMT", "version": "v1" } ]
2022-03-16
[ [ "Fu", "Yuqian", "" ], [ "Xie", "Yu", "" ], [ "Fu", "Yanwei", "" ], [ "Chen", "Jingjing", "" ], [ "Jiang", "Yu-Gang", "" ] ]
Previous few-shot learning (FSL) works mostly are limited to natural images of general concepts and categories. These works assume very high visual similarity between the source and target classes. In contrast, the recently proposed cross-domain few-shot learning (CD-FSL) aims at transferring knowledge from general nat...
2006.09040
Christopher Brix
Christopher Brix, Thomas Noll
Debona: Decoupled Boundary Network Analysis for Tighter Bounds and Faster Adversarial Robustness Proofs
null
null
null
null
cs.LG cs.AI stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Neural networks are commonly used in safety-critical real-world applications. Unfortunately, the predicted output is often highly sensitive to small, and possibly imperceptible, changes to the input data. Proving that either no such adversarial examples exist, or providing a concrete instance, is therefore crucial to...
[ { "created": "Tue, 16 Jun 2020 10:00:33 GMT", "version": "v1" }, { "created": "Tue, 2 Feb 2021 16:53:29 GMT", "version": "v2" } ]
2021-02-03
[ [ "Brix", "Christopher", "" ], [ "Noll", "Thomas", "" ] ]
Neural networks are commonly used in safety-critical real-world applications. Unfortunately, the predicted output is often highly sensitive to small, and possibly imperceptible, changes to the input data. Proving that either no such adversarial examples exist, or providing a concrete instance, is therefore crucial to e...
2011.03290
Delei Kong
Delei Kong, Zheng Fang, Haojia Li, Kuanxu Hou, Sonya Coleman and Dermot Kerr
Event-VPR: End-to-End Weakly Supervised Network Architecture for Event-based Visual Place Recognition
null
null
null
null
cs.CV cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Traditional visual place recognition (VPR) methods generally use frame-based cameras, which is easy to fail due to dramatic illumination changes or fast motions. In this paper, we propose an end-to-end visual place recognition network for event cameras, which can achieve good place recognition performance in challeng...
[ { "created": "Fri, 6 Nov 2020 11:32:04 GMT", "version": "v1" } ]
2020-11-09
[ [ "Kong", "Delei", "" ], [ "Fang", "Zheng", "" ], [ "Li", "Haojia", "" ], [ "Hou", "Kuanxu", "" ], [ "Coleman", "Sonya", "" ], [ "Kerr", "Dermot", "" ] ]
Traditional visual place recognition (VPR) methods generally use frame-based cameras, which is easy to fail due to dramatic illumination changes or fast motions. In this paper, we propose an end-to-end visual place recognition network for event cameras, which can achieve good place recognition performance in challengin...
2203.01543
Andy T. Liu
Andy T. Liu, Wei Xiao, Henghui Zhu, Dejiao Zhang, Shang-Wen Li, Andrew Arnold
QaNER: Prompting Question Answering Models for Few-shot Named Entity Recognition
8 pages, 6 figures
null
null
null
cs.CL cs.AI cs.LG
http://creativecommons.org/licenses/by-nc-sa/4.0/
Recently, prompt-based learning for pre-trained language models has succeeded in few-shot Named Entity Recognition (NER) by exploiting prompts as task guidance to increase label efficiency. However, previous prompt-based methods for few-shot NER have limitations such as a higher computational complexity, poor zero-sh...
[ { "created": "Thu, 3 Mar 2022 06:56:01 GMT", "version": "v1" }, { "created": "Fri, 4 Mar 2022 07:58:08 GMT", "version": "v2" } ]
2022-03-07
[ [ "Liu", "Andy T.", "" ], [ "Xiao", "Wei", "" ], [ "Zhu", "Henghui", "" ], [ "Zhang", "Dejiao", "" ], [ "Li", "Shang-Wen", "" ], [ "Arnold", "Andrew", "" ] ]
Recently, prompt-based learning for pre-trained language models has succeeded in few-shot Named Entity Recognition (NER) by exploiting prompts as task guidance to increase label efficiency. However, previous prompt-based methods for few-shot NER have limitations such as a higher computational complexity, poor zero-shot...
1312.2218
EPTCS
Nobuko Yoshida (Imperial College London, UK), Wim Vanderbauwhede (University of Glasgow, UK)
Proceedings 5th Workshop on Programming Language Approaches to Concurrency and Communication-cEntric Software
null
EPTCS 137, 2013
10.4204/EPTCS.137
null
cs.PL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
PLACES 2013 (full title: Programming Language Approaches to Concurrency- and Communication-cEntric Software) was the sixth edition of the PLACES workshop series. After the first PLACES, which was affiliated to DisCoTec in 2008, the workshop has been part of ETAPS every year since 2009 and is now an established part o...
[ { "created": "Sun, 8 Dec 2013 14:19:11 GMT", "version": "v1" } ]
2013-12-10
[ [ "Yoshida", "Nobuko", "", "Imperial College London, UK" ], [ "Vanderbauwhede", "Wim", "", "University of Glasgow, UK" ] ]
PLACES 2013 (full title: Programming Language Approaches to Concurrency- and Communication-cEntric Software) was the sixth edition of the PLACES workshop series. After the first PLACES, which was affiliated to DisCoTec in 2008, the workshop has been part of ETAPS every year since 2009 and is now an established part of ...
1909.06146
Qiao Jin
Qiao Jin, Bhuwan Dhingra, Zhengping Liu, William W. Cohen, Xinghua Lu
PubMedQA: A Dataset for Biomedical Research Question Answering
EMNLP 2019
null
null
null
cs.CL cs.LG q-bio.QM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We introduce PubMedQA, a novel biomedical question answering (QA) dataset collected from PubMed abstracts. The task of PubMedQA is to answer research questions with yes/no/maybe (e.g.: Do preoperative statins reduce atrial fibrillation after coronary artery bypass grafting?) using the corresponding abstracts. PubMedQ...
[ { "created": "Fri, 13 Sep 2019 11:18:20 GMT", "version": "v1" } ]
2019-09-16
[ [ "Jin", "Qiao", "" ], [ "Dhingra", "Bhuwan", "" ], [ "Liu", "Zhengping", "" ], [ "Cohen", "William W.", "" ], [ "Lu", "Xinghua", "" ] ]
We introduce PubMedQA, a novel biomedical question answering (QA) dataset collected from PubMed abstracts. The task of PubMedQA is to answer research questions with yes/no/maybe (e.g.: Do preoperative statins reduce atrial fibrillation after coronary artery bypass grafting?) using the corresponding abstracts. PubMedQA ...
2104.13818
Ali Ramezani-Kebrya
Ali Ramezani-Kebrya, Fartash Faghri, Ilya Markov, Vitalii Aksenov, Dan Alistarh, Daniel M. Roy
NUQSGD: Provably Communication-efficient Data-parallel SGD via Nonuniform Quantization
This entry is redundant and was created in error. See arXiv:1908.06077 for the latest version
null
null
null
cs.LG math.OC stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
As the size and complexity of models and datasets grow, so does the need for communication-efficient variants of stochastic gradient descent that can be deployed to perform parallel model training. One popular communication-compression method for data-parallel SGD is QSGD (Alistarh et al., 2017), which quantizes and ...
[ { "created": "Wed, 28 Apr 2021 15:07:03 GMT", "version": "v1" }, { "created": "Sat, 1 May 2021 20:34:38 GMT", "version": "v2" } ]
2021-05-05
[ [ "Ramezani-Kebrya", "Ali", "" ], [ "Faghri", "Fartash", "" ], [ "Markov", "Ilya", "" ], [ "Aksenov", "Vitalii", "" ], [ "Alistarh", "Dan", "" ], [ "Roy", "Daniel M.", "" ] ]
As the size and complexity of models and datasets grow, so does the need for communication-efficient variants of stochastic gradient descent that can be deployed to perform parallel model training. One popular communication-compression method for data-parallel SGD is QSGD (Alistarh et al., 2017), which quantizes and en...
1607.06757
Konrad Dabrowski
Alexandre Blanch\'e and Konrad K. Dabrowski and Matthew Johnson and Dani\"el Paulusma
Hereditary Graph Classes: When the Complexities of Colouring and Clique Cover Coincide
19 Pages, 5 Figures
null
null
null
cs.DS cs.CC cs.DM math.CO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A graph is $(H_1,H_2)$-free for a pair of graphs $H_1,H_2$ if it contains no induced subgraph isomorphic to $H_1$ or $H_2$. In 2001, Kr\'al', Kratochv\'{\i}l, Tuza, and Woeginger initiated a study into the complexity of Colouring for $(H_1,H_2)$-free graphs. Since then, others have tried to complete their study, but ...
[ { "created": "Fri, 22 Jul 2016 17:32:39 GMT", "version": "v1" }, { "created": "Mon, 12 Dec 2016 20:29:41 GMT", "version": "v2" }, { "created": "Wed, 7 Jun 2017 11:10:25 GMT", "version": "v3" } ]
2017-06-08
[ [ "Blanché", "Alexandre", "" ], [ "Dabrowski", "Konrad K.", "" ], [ "Johnson", "Matthew", "" ], [ "Paulusma", "Daniël", "" ] ]
A graph is $(H_1,H_2)$-free for a pair of graphs $H_1,H_2$ if it contains no induced subgraph isomorphic to $H_1$ or $H_2$. In 2001, Kr\'al', Kratochv\'{\i}l, Tuza, and Woeginger initiated a study into the complexity of Colouring for $(H_1,H_2)$-free graphs. Since then, others have tried to complete their study, but ma...
2205.10629
Phillip Swazinna
Phillip Swazinna, Steffen Udluft, Thomas Runkler
User-Interactive Offline Reinforcement Learning
Accepted at ICLR 2023 - 11th International Conference on Learning Representations
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Offline reinforcement learning algorithms still lack trust in practice due to the risk that the learned policy performs worse than the original policy that generated the dataset or behaves in an unexpected way that is unfamiliar to the user. At the same time, offline RL algorithms are not able to tune their most impo...
[ { "created": "Sat, 21 May 2022 15:50:23 GMT", "version": "v1" }, { "created": "Wed, 25 Jan 2023 12:37:46 GMT", "version": "v2" } ]
2023-01-26
[ [ "Swazinna", "Phillip", "" ], [ "Udluft", "Steffen", "" ], [ "Runkler", "Thomas", "" ] ]
Offline reinforcement learning algorithms still lack trust in practice due to the risk that the learned policy performs worse than the original policy that generated the dataset or behaves in an unexpected way that is unfamiliar to the user. At the same time, offline RL algorithms are not able to tune their most import...
2202.09338
Bennet Meyers
Bennet E. Meyers and Stephen P. Boyd
Signal Decomposition Using Masked Proximal Operators
The manuscript has 61 pages, 22 figures and 2 tables. Also hosted at https://web.stanford.edu/~boyd/papers/sig_decomp_mprox.html. For code, see https://github.com/cvxgrp/signal-decomposition
null
null
null
cs.LG eess.SP
http://creativecommons.org/licenses/by-sa/4.0/
We consider the well-studied problem of decomposing a vector time series signal into components with different characteristics, such as smooth, periodic, nonnegative, or sparse. We describe a simple and general framework in which the components are defined by loss functions (which include constraints), and the signal...
[ { "created": "Fri, 18 Feb 2022 18:05:33 GMT", "version": "v1" }, { "created": "Wed, 2 Mar 2022 16:46:36 GMT", "version": "v2" }, { "created": "Tue, 3 May 2022 00:02:53 GMT", "version": "v3" }, { "created": "Wed, 4 May 2022 16:05:04 GMT", "version": "v4" }, { "crea...
2022-09-21
[ [ "Meyers", "Bennet E.", "" ], [ "Boyd", "Stephen P.", "" ] ]
We consider the well-studied problem of decomposing a vector time series signal into components with different characteristics, such as smooth, periodic, nonnegative, or sparse. We describe a simple and general framework in which the components are defined by loss functions (which include constraints), and the signal d...
1711.00354
Shinnosuke Takamichi
Ryosuke Sonobe, Shinnosuke Takamichi, Hiroshi Saruwatari
JSUT corpus: free large-scale Japanese speech corpus for end-to-end speech synthesis
Submitted to ICASSP2018
null
null
null
cs.CL
http://creativecommons.org/licenses/by-sa/4.0/
Thanks to improvements in machine learning techniques including deep learning, a free large-scale speech corpus that can be shared between academic institutions and commercial companies has an important role. However, such a corpus for Japanese speech synthesis does not exist. In this paper, we designed a novel Japan...
[ { "created": "Sat, 28 Oct 2017 05:28:01 GMT", "version": "v1" } ]
2017-11-02
[ [ "Sonobe", "Ryosuke", "" ], [ "Takamichi", "Shinnosuke", "" ], [ "Saruwatari", "Hiroshi", "" ] ]
Thanks to improvements in machine learning techniques including deep learning, a free large-scale speech corpus that can be shared between academic institutions and commercial companies has an important role. However, such a corpus for Japanese speech synthesis does not exist. In this paper, we designed a novel Japanes...
1909.04942
Peiliang Li
Peiliang Li, Siqi Liu and Shaojie Shen
Multi-Sensor 3D Object Box Refinement for Autonomous Driving
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We propose a 3D object detection system with multi-sensor refinement in the context of autonomous driving. In our framework, the monocular camera serves as the fundamental sensor for 2D object proposal and initial 3D bounding box prediction. While the stereo cameras and LiDAR are treated as adaptive plug-in sensors t...
[ { "created": "Wed, 11 Sep 2019 09:38:56 GMT", "version": "v1" }, { "created": "Tue, 19 Nov 2019 05:36:55 GMT", "version": "v2" } ]
2019-11-20
[ [ "Li", "Peiliang", "" ], [ "Liu", "Siqi", "" ], [ "Shen", "Shaojie", "" ] ]
We propose a 3D object detection system with multi-sensor refinement in the context of autonomous driving. In our framework, the monocular camera serves as the fundamental sensor for 2D object proposal and initial 3D bounding box prediction. While the stereo cameras and LiDAR are treated as adaptive plug-in sensors to ...
2402.10323
Melissa Greeff
Babak Akbari and Melissa Greeff
A Computationally Efficient Learning-Based Model Predictive Control for Multirotors under Aerodynamic Disturbances
null
null
null
null
cs.RO cs.SY eess.SY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Neglecting complex aerodynamic effects hinders high-speed yet high-precision multirotor autonomy. In this paper, we present a computationally efficient learning-based model predictive controller that simultaneously optimizes a trajectory that can be tracked within the physical limits (on thrust and orientation) of th...
[ { "created": "Thu, 15 Feb 2024 20:54:05 GMT", "version": "v1" } ]
2024-02-19
[ [ "Akbari", "Babak", "" ], [ "Greeff", "Melissa", "" ] ]
Neglecting complex aerodynamic effects hinders high-speed yet high-precision multirotor autonomy. In this paper, we present a computationally efficient learning-based model predictive controller that simultaneously optimizes a trajectory that can be tracked within the physical limits (on thrust and orientation) of the ...
2004.13477
Pavel Surynek
Pavel Surynek
Pushing the Envelope: From Discrete to Continuous Movements in Multi-Agent Path Finding via Lazy Encodings
arXiv admin note: text overlap with arXiv:1903.09820
null
null
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Multi-agent path finding in continuous space and time with geometric agents MAPF$^\mathcal{R}$ is addressed in this paper. The task is to navigate agents that move smoothly between predefined positions to their individual goals so that they do not collide. We introduce a novel solving approach for obtaining makespan ...
[ { "created": "Sat, 25 Apr 2020 13:21:32 GMT", "version": "v1" } ]
2020-04-29
[ [ "Surynek", "Pavel", "" ] ]
Multi-agent path finding in continuous space and time with geometric agents MAPF$^\mathcal{R}$ is addressed in this paper. The task is to navigate agents that move smoothly between predefined positions to their individual goals so that they do not collide. We introduce a novel solving approach for obtaining makespan op...
1609.09430
Shawn Hershey
Shawn Hershey, Sourish Chaudhuri, Daniel P. W. Ellis, Jort F. Gemmeke, Aren Jansen, R. Channing Moore, Manoj Plakal, Devin Platt, Rif A. Saurous, Bryan Seybold, Malcolm Slaney, Ron J. Weiss, Kevin Wilson
CNN Architectures for Large-Scale Audio Classification
Accepted for publication at ICASSP 2017 Changes: Added definitions of mAP, AUC, and d-prime. Updated mAP/AUC/d-prime numbers for Audio Set based on changes of latest Audio Set revision. Changed wording to fit 4 page limit with new additions
null
null
null
cs.SD cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Convolutional Neural Networks (CNNs) have proven very effective in image classification and show promise for audio. We use various CNN architectures to classify the soundtracks of a dataset of 70M training videos (5.24 million hours) with 30,871 video-level labels. We examine fully connected Deep Neural Networks (DNN...
[ { "created": "Thu, 29 Sep 2016 17:04:50 GMT", "version": "v1" }, { "created": "Tue, 10 Jan 2017 18:06:51 GMT", "version": "v2" } ]
2017-01-11
[ [ "Hershey", "Shawn", "" ], [ "Chaudhuri", "Sourish", "" ], [ "Ellis", "Daniel P. W.", "" ], [ "Gemmeke", "Jort F.", "" ], [ "Jansen", "Aren", "" ], [ "Moore", "R. Channing", "" ], [ "Plakal", "Manoj", "" ]...
Convolutional Neural Networks (CNNs) have proven very effective in image classification and show promise for audio. We use various CNN architectures to classify the soundtracks of a dataset of 70M training videos (5.24 million hours) with 30,871 video-level labels. We examine fully connected Deep Neural Networks (DNNs)...
2005.05385
Murat Yildirim
Suleyman Yildirim, Alper Ekrem Murat, Murat Yildirim, Suzan Arslanturk
Process Knowledge Driven Change Point Detection for Automated Calibration of Discrete Event Simulation Models Using Machine Learning
This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible
null
null
null
cs.LG cs.SY eess.SY stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Initial development and subsequent calibration of discrete event simulation models for complex systems require accurate identification of dynamically changing process characteristics. Existing data driven change point methods (DD-CPD) assume changes are extraneous to the system, thus cannot utilize available process ...
[ { "created": "Mon, 11 May 2020 19:07:26 GMT", "version": "v1" }, { "created": "Mon, 21 Sep 2020 04:24:27 GMT", "version": "v2" } ]
2020-09-22
[ [ "Yildirim", "Suleyman", "" ], [ "Murat", "Alper Ekrem", "" ], [ "Yildirim", "Murat", "" ], [ "Arslanturk", "Suzan", "" ] ]
Initial development and subsequent calibration of discrete event simulation models for complex systems require accurate identification of dynamically changing process characteristics. Existing data driven change point methods (DD-CPD) assume changes are extraneous to the system, thus cannot utilize available process kn...
1912.10398
L.A. Prashanth
Ajay Kumar Pandey, Prashanth L.A. and Sanjay P. Bhat
Estimation of Spectral Risk Measures
null
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We consider the problem of estimating a spectral risk measure (SRM) from i.i.d. samples, and propose a novel method that is based on numerical integration. We show that our SRM estimate concentrates exponentially, when the underlying distribution has bounded support. Further, we also consider the case when the underl...
[ { "created": "Sun, 22 Dec 2019 08:11:42 GMT", "version": "v1" } ]
2019-12-24
[ [ "Pandey", "Ajay Kumar", "" ], [ "A.", "Prashanth L.", "" ], [ "Bhat", "Sanjay P.", "" ] ]
We consider the problem of estimating a spectral risk measure (SRM) from i.i.d. samples, and propose a novel method that is based on numerical integration. We show that our SRM estimate concentrates exponentially, when the underlying distribution has bounded support. Further, we also consider the case when the underlyi...
1905.11445
Ke Wang
Ke Wang, Mihai Christodorescu
COSET: A Benchmark for Evaluating Neural Program Embeddings
8 Pages
null
null
null
cs.LG cs.PL stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Neural program embedding can be helpful in analyzing large software, a task that is challenging for traditional logic-based program analyses due to their limited scalability. A key focus of recent machine-learning advances in this area is on modeling program semantics instead of just syntax. Unfortunately evaluating ...
[ { "created": "Mon, 27 May 2019 18:44:54 GMT", "version": "v1" } ]
2019-05-29
[ [ "Wang", "Ke", "" ], [ "Christodorescu", "Mihai", "" ] ]
Neural program embedding can be helpful in analyzing large software, a task that is challenging for traditional logic-based program analyses due to their limited scalability. A key focus of recent machine-learning advances in this area is on modeling program semantics instead of just syntax. Unfortunately evaluating su...
2004.11475
Aayush Rana
Mamshad Nayeem Rizve, Ugur Demir, Praveen Tirupattur, Aayush Jung Rana, Kevin Duarte, Ishan Dave, Yogesh Singh Rawat, Mubarak Shah
Gabriella: An Online System for Real-Time Activity Detection in Untrimmed Security Videos
9 pages
null
null
null
cs.CV eess.IV
http://creativecommons.org/licenses/by-nc-sa/4.0/
Activity detection in security videos is a difficult problem due to multiple factors such as large field of view, presence of multiple activities, varying scales and viewpoints, and its untrimmed nature. The existing research in activity detection is mainly focused on datasets, such as UCF-101, JHMDB, THUMOS, and AVA...
[ { "created": "Thu, 23 Apr 2020 22:20:10 GMT", "version": "v1" }, { "created": "Tue, 19 May 2020 17:45:25 GMT", "version": "v2" } ]
2020-05-20
[ [ "Rizve", "Mamshad Nayeem", "" ], [ "Demir", "Ugur", "" ], [ "Tirupattur", "Praveen", "" ], [ "Rana", "Aayush Jung", "" ], [ "Duarte", "Kevin", "" ], [ "Dave", "Ishan", "" ], [ "Rawat", "Yogesh Singh", "" ...
Activity detection in security videos is a difficult problem due to multiple factors such as large field of view, presence of multiple activities, varying scales and viewpoints, and its untrimmed nature. The existing research in activity detection is mainly focused on datasets, such as UCF-101, JHMDB, THUMOS, and AVA, ...
2301.07696
Robert Beinert
Robert Beinert, Saghar Rezaei
Prony-Based Super-Resolution Phase Retrieval of Sparse, Multivariate Signals
null
null
null
null
cs.IT cs.NA math.IT math.NA
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Phase retrieval consists in the recovery of an unknown signal from phaseless measurements of its usually complex-valued Fourier transform. Without further assumptions, this problem is notorious to be severe ill posed such that the recovery of the true signal is nearly impossible. In certain applications like crystall...
[ { "created": "Wed, 18 Jan 2023 18:36:16 GMT", "version": "v1" } ]
2023-01-19
[ [ "Beinert", "Robert", "" ], [ "Rezaei", "Saghar", "" ] ]
Phase retrieval consists in the recovery of an unknown signal from phaseless measurements of its usually complex-valued Fourier transform. Without further assumptions, this problem is notorious to be severe ill posed such that the recovery of the true signal is nearly impossible. In certain applications like crystallog...
2302.09703
Jihao Long
Jihao Long and Jiequn Han
Reinforcement Learning with Function Approximation: From Linear to Nonlinear
null
J. Mach. Learn. , 2 (2023), pp. 161-193
10.4208/jml.230105
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Function approximation has been an indispensable component in modern reinforcement learning algorithms designed to tackle problems with large state spaces in high dimensions. This paper reviews recent results on error analysis for these reinforcement learning algorithms in linear or nonlinear approximation settings, ...
[ { "created": "Mon, 20 Feb 2023 00:31:18 GMT", "version": "v1" }, { "created": "Fri, 19 May 2023 01:01:39 GMT", "version": "v2" } ]
2024-02-27
[ [ "Long", "Jihao", "" ], [ "Han", "Jiequn", "" ] ]
Function approximation has been an indispensable component in modern reinforcement learning algorithms designed to tackle problems with large state spaces in high dimensions. This paper reviews recent results on error analysis for these reinforcement learning algorithms in linear or nonlinear approximation settings, em...
1806.08810
Nima Roohi
Nima Roohi, Ramneet Kaur, James Weimer, Oleg Sokolsky, Insup Lee
Self-Driving Vehicle Verification Towards a Benchmark
7 pages
null
null
null
cs.LO cs.RO cs.SY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Industrial cyber-physical systems are hybrid systems with strict safety requirements. Despite not having a formal semantics, most of these systems are modeled using Stateflow/Simulink for mainly two reasons: (1) it is easier to model, test, and simulate using these tools, and (2) dynamics of these systems are not sup...
[ { "created": "Wed, 20 Jun 2018 12:23:35 GMT", "version": "v1" } ]
2018-06-26
[ [ "Roohi", "Nima", "" ], [ "Kaur", "Ramneet", "" ], [ "Weimer", "James", "" ], [ "Sokolsky", "Oleg", "" ], [ "Lee", "Insup", "" ] ]
Industrial cyber-physical systems are hybrid systems with strict safety requirements. Despite not having a formal semantics, most of these systems are modeled using Stateflow/Simulink for mainly two reasons: (1) it is easier to model, test, and simulate using these tools, and (2) dynamics of these systems are not suppo...
1301.3527
Vamsi Potluru
Vamsi K. Potluru, Sergey M. Plis, Jonathan Le Roux, Barak A. Pearlmutter, Vince D. Calhoun, Thomas P. Hayes
Block Coordinate Descent for Sparse NMF
null
null
null
null
cs.LG cs.NA
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Nonnegative matrix factorization (NMF) has become a ubiquitous tool for data analysis. An important variant is the sparse NMF problem which arises when we explicitly require the learnt features to be sparse. A natural measure of sparsity is the L$_0$ norm, however its optimization is NP-hard. Mixed norms, such as L$_...
[ { "created": "Tue, 15 Jan 2013 23:11:05 GMT", "version": "v1" }, { "created": "Mon, 18 Mar 2013 22:42:11 GMT", "version": "v2" } ]
2013-03-20
[ [ "Potluru", "Vamsi K.", "" ], [ "Plis", "Sergey M.", "" ], [ "Roux", "Jonathan Le", "" ], [ "Pearlmutter", "Barak A.", "" ], [ "Calhoun", "Vince D.", "" ], [ "Hayes", "Thomas P.", "" ] ]
Nonnegative matrix factorization (NMF) has become a ubiquitous tool for data analysis. An important variant is the sparse NMF problem which arises when we explicitly require the learnt features to be sparse. A natural measure of sparsity is the L$_0$ norm, however its optimization is NP-hard. Mixed norms, such as L$_1$...
1410.1006
Fabrizio Frati
Giuseppe Di Battista and Fabrizio Frati
A Survey on Small-Area Planar Graph Drawing
Preliminary version appeared in "Thirty Essays on Geometric Graph Theory", J. Pach (ed.), 2012
null
null
null
cs.CG cs.DM cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We survey algorithms and bounds for constructing planar drawings of graphs in small area.
[ { "created": "Sat, 4 Oct 2014 01:44:39 GMT", "version": "v1" } ]
2014-10-07
[ [ "Di Battista", "Giuseppe", "" ], [ "Frati", "Fabrizio", "" ] ]
We survey algorithms and bounds for constructing planar drawings of graphs in small area.
2209.13750
Andrey Kutuzov
Anna Aksenova, Ekaterina Gavrishina, Elisey Rykov, Andrey Kutuzov
RuDSI: graph-based word sense induction dataset for Russian
TextGraphs-16 workshop at the CoLING-2022 conference
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
We present RuDSI, a new benchmark for word sense induction (WSI) in Russian. The dataset was created using manual annotation and semi-automatic clustering of Word Usage Graphs (WUGs). Unlike prior WSI datasets for Russian, RuDSI is completely data-driven (based on texts from Russian National Corpus), with no external...
[ { "created": "Wed, 28 Sep 2022 00:08:24 GMT", "version": "v1" } ]
2022-09-29
[ [ "Aksenova", "Anna", "" ], [ "Gavrishina", "Ekaterina", "" ], [ "Rykov", "Elisey", "" ], [ "Kutuzov", "Andrey", "" ] ]
We present RuDSI, a new benchmark for word sense induction (WSI) in Russian. The dataset was created using manual annotation and semi-automatic clustering of Word Usage Graphs (WUGs). Unlike prior WSI datasets for Russian, RuDSI is completely data-driven (based on texts from Russian National Corpus), with no external w...
2007.14964
David Gotz
David Borland, Jonathan Zhang, Smiti Kaul, David Gotz
Selection-Bias-Corrected Visualization via Dynamic Reweighting
This article will be published in IEEE Transactions on Visualization and Computer Graphics (TVCG) in January 2021. The work will also be presented at IEEE VIS 2020. Video figure available here: https://vimeo.com/442775090
null
10.1109/TVCG.2020.3030455
null
cs.HC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The collection and visual analysis of large-scale data from complex systems, such as electronic health records or clickstream data, has become increasingly common across a wide range of industries. This type of retrospective visual analysis, however, is prone to a variety of selection bias effects, especially for hig...
[ { "created": "Wed, 29 Jul 2020 17:15:36 GMT", "version": "v1" }, { "created": "Mon, 24 Aug 2020 21:02:54 GMT", "version": "v2" } ]
2020-12-07
[ [ "Borland", "David", "" ], [ "Zhang", "Jonathan", "" ], [ "Kaul", "Smiti", "" ], [ "Gotz", "David", "" ] ]
The collection and visual analysis of large-scale data from complex systems, such as electronic health records or clickstream data, has become increasingly common across a wide range of industries. This type of retrospective visual analysis, however, is prone to a variety of selection bias effects, especially for high-...
2204.08103
Ariel Rosenfeld
Ariel Rosenfeld and Oleg Maksimov
Should Young Computer Scientists Stop Collaborating with their Doctoral Advisors?
Communications of the ACM (to appear)
null
10.1145/3529089
null
cs.CY cs.DL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
One of the first steps in an academic career, and perhaps the pillar thereof, is completing a PhD under the supervision of a doctoral advisor. While prior work has examined the advisor-advisee relationship and its potential effects on the prospective academic success of the advisee, very little is known on the possib...
[ { "created": "Thu, 7 Apr 2022 18:49:39 GMT", "version": "v1" } ]
2022-04-19
[ [ "Rosenfeld", "Ariel", "" ], [ "Maksimov", "Oleg", "" ] ]
One of the first steps in an academic career, and perhaps the pillar thereof, is completing a PhD under the supervision of a doctoral advisor. While prior work has examined the advisor-advisee relationship and its potential effects on the prospective academic success of the advisee, very little is known on the possibly...
1512.03131
Li Wang
Li Wang and Dennis Sng
Deep Learning Algorithms with Applications to Video Analytics for A Smart City: A Survey
8 pages, 18 figures
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Deep learning has recently achieved very promising results in a wide range of areas such as computer vision, speech recognition and natural language processing. It aims to learn hierarchical representations of data by using deep architecture models. In a smart city, a lot of data (e.g. videos captured from many distr...
[ { "created": "Thu, 10 Dec 2015 03:23:54 GMT", "version": "v1" } ]
2015-12-11
[ [ "Wang", "Li", "" ], [ "Sng", "Dennis", "" ] ]
Deep learning has recently achieved very promising results in a wide range of areas such as computer vision, speech recognition and natural language processing. It aims to learn hierarchical representations of data by using deep architecture models. In a smart city, a lot of data (e.g. videos captured from many distrib...
2212.13647
Miguel Pardal
Duarte M. Nascimento and Miguel Ferreira and Miguel L. Pardal
Does Big Data Require Complex Systems? A Performance Comparison Between Spark and Unicage Shell Scripts
10 pages, 14 figures
null
null
null
cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The paradigm of big data is characterized by the need to collect and process data sets of great volume, arriving at the systems with great velocity, in a variety of formats. Spark is a widely used big data processing system that can be integrated with Hadoop to provide powerful abstractions to developers, such as dis...
[ { "created": "Wed, 28 Dec 2022 00:04:13 GMT", "version": "v1" } ]
2022-12-29
[ [ "Nascimento", "Duarte M.", "" ], [ "Ferreira", "Miguel", "" ], [ "Pardal", "Miguel L.", "" ] ]
The paradigm of big data is characterized by the need to collect and process data sets of great volume, arriving at the systems with great velocity, in a variety of formats. Spark is a widely used big data processing system that can be integrated with Hadoop to provide powerful abstractions to developers, such as distr...
1005.5065
Manar Mohaisen
Manar Mohaisen, KyungHi Chang
Upper-lower bounded-complexity QRD-M for spatial multiplexing MIMO-OFDM systems
Springer, Wireless Personal Communications Journal (WPC'2010), 13 pages, 6 figures, 2 tables, 1 algorithm
null
10.1007/s11277-010-0014-8
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Multiple-input multiple-output (MIMO) technology applied with orthogonal frequency division multiplexing (OFDM) is considered as the ultimate solution to increase channel capacity without any additional spectral resources. At the receiver side, the challenge resides in designing low complexity detection algorithms ca...
[ { "created": "Thu, 27 May 2010 13:26:03 GMT", "version": "v1" } ]
2010-05-28
[ [ "Mohaisen", "Manar", "" ], [ "Chang", "KyungHi", "" ] ]
Multiple-input multiple-output (MIMO) technology applied with orthogonal frequency division multiplexing (OFDM) is considered as the ultimate solution to increase channel capacity without any additional spectral resources. At the receiver side, the challenge resides in designing low complexity detection algorithms capa...
2303.15892
Yuhao Cheng
Yuhao Cheng and Yichao Yan and Wenhan Zhu and Ye Pan and Bowen Pan and Xiaokang Yang
Head3D: Complete 3D Head Generation via Tri-plane Feature Distillation
null
null
null
null
cs.CV
http://creativecommons.org/licenses/by-nc-sa/4.0/
Head generation with diverse identities is an important task in computer vision and computer graphics, widely used in multimedia applications. However, current full head generation methods require a large number of 3D scans or multi-view images to train the model, resulting in expensive data acquisition cost. To addr...
[ { "created": "Tue, 28 Mar 2023 11:12:26 GMT", "version": "v1" } ]
2023-03-29
[ [ "Cheng", "Yuhao", "" ], [ "Yan", "Yichao", "" ], [ "Zhu", "Wenhan", "" ], [ "Pan", "Ye", "" ], [ "Pan", "Bowen", "" ], [ "Yang", "Xiaokang", "" ] ]
Head generation with diverse identities is an important task in computer vision and computer graphics, widely used in multimedia applications. However, current full head generation methods require a large number of 3D scans or multi-view images to train the model, resulting in expensive data acquisition cost. To addres...
2306.00757
Zou Zhou
Qing Huang, Zhou Zou, Zhenchang Xing, Zhenkang Zuo, Xiwei Xu, Qinghua Lu
AI Chain on Large Language Model for Unsupervised Control Flow Graph Generation for Statically-Typed Partial Code
null
null
null
null
cs.SE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Control Flow Graphs (CFGs) are essential for visualizing, understanding and analyzing program behavior. For statically-typed programming language like Java, developers obtain CFGs by using bytecode-based methods for compilable code and Abstract Syntax Tree (AST)-based methods for partially uncompilable code. However,...
[ { "created": "Thu, 1 Jun 2023 14:52:59 GMT", "version": "v1" } ]
2023-06-02
[ [ "Huang", "Qing", "" ], [ "Zou", "Zhou", "" ], [ "Xing", "Zhenchang", "" ], [ "Zuo", "Zhenkang", "" ], [ "Xu", "Xiwei", "" ], [ "Lu", "Qinghua", "" ] ]
Control Flow Graphs (CFGs) are essential for visualizing, understanding and analyzing program behavior. For statically-typed programming language like Java, developers obtain CFGs by using bytecode-based methods for compilable code and Abstract Syntax Tree (AST)-based methods for partially uncompilable code. However, e...
2204.08575
Basheer Joudeh
Basheer Joudeh and Boris \v{S}kori\'c
Collusion-resistant fingerprinting of parallel content channels
15 pages. 1 figure. Submitted to IHMMSEC'22
null
null
null
cs.IT cs.CR math.IT
http://creativecommons.org/licenses/by/4.0/
The fingerprinting game is analysed when the coalition size $k$ is known to the tracer, but the colluders can distribute themselves across $L$ TV channels. The collusion channel is introduced and the extra degrees of freedom for the coalition are made manifest in our formulation. We introduce a payoff functional that...
[ { "created": "Mon, 18 Apr 2022 22:06:23 GMT", "version": "v1" } ]
2022-04-20
[ [ "Joudeh", "Basheer", "" ], [ "Škorić", "Boris", "" ] ]
The fingerprinting game is analysed when the coalition size $k$ is known to the tracer, but the colluders can distribute themselves across $L$ TV channels. The collusion channel is introduced and the extra degrees of freedom for the coalition are made manifest in our formulation. We introduce a payoff functional that i...
2105.14565
JingKai Siow
Yaqin Zhou, Jing Kai Siow, Chenyu Wang, Shangqing Liu, Yang Liu
SPI: Automated Identification of Security Patches via Commits
Accepted By ACM Transactions on Software Engineering and Methodology (TOSEM), Continuous Special Section: AI and SE
null
null
null
cs.CR cs.SE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Security patches in open-source software, providing security fixes to identified vulnerabilities, are crucial in protecting against cyberattacks. Despite the National Vulnerability Database (NVD) publishes identified vulnerabilities, a vast majority of vulnerabilities and their corresponding security patches remain b...
[ { "created": "Sun, 30 May 2021 15:09:40 GMT", "version": "v1" }, { "created": "Sun, 6 Jun 2021 14:00:38 GMT", "version": "v2" } ]
2021-06-08
[ [ "Zhou", "Yaqin", "" ], [ "Siow", "Jing Kai", "" ], [ "Wang", "Chenyu", "" ], [ "Liu", "Shangqing", "" ], [ "Liu", "Yang", "" ] ]
Security patches in open-source software, providing security fixes to identified vulnerabilities, are crucial in protecting against cyberattacks. Despite the National Vulnerability Database (NVD) publishes identified vulnerabilities, a vast majority of vulnerabilities and their corresponding security patches remain bey...
2211.01496
Yu Zhang
Yu Zhang, Mitchell Bucklew
Max Markov Chain
null
null
null
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we introduce Max Markov Chain (MMC), a novel representation for a useful subset of High-order Markov Chains (HMCs) with sparse correlations among the states. MMC is parsimony while retaining the expressiveness of HMCs. Even though parameter optimization is generally intractable as with HMC approximate ...
[ { "created": "Wed, 2 Nov 2022 21:50:54 GMT", "version": "v1" } ]
2022-11-04
[ [ "Zhang", "Yu", "" ], [ "Bucklew", "Mitchell", "" ] ]
In this paper, we introduce Max Markov Chain (MMC), a novel representation for a useful subset of High-order Markov Chains (HMCs) with sparse correlations among the states. MMC is parsimony while retaining the expressiveness of HMCs. Even though parameter optimization is generally intractable as with HMC approximate mo...
2403.14183
Jong Chul Ye
Kwanyoung Kim, Yujin Oh, Jong Chul Ye
OTSeg: Multi-prompt Sinkhorn Attention for Zero-Shot Semantic Segmentation
ECCV 2024; 23 pages, 8 tables, 8 figures; Project Page: https://cubeyoung.github.io/OTSeg_project/
null
null
null
cs.CV cs.AI cs.LG stat.ML
http://creativecommons.org/licenses/by/4.0/
The recent success of CLIP has demonstrated promising results in zero-shot semantic segmentation by transferring muiltimodal knowledge to pixel-level classification. However, leveraging pre-trained CLIP knowledge to closely align text embeddings with pixel embeddings still has limitations in existing approaches. To a...
[ { "created": "Thu, 21 Mar 2024 07:15:37 GMT", "version": "v1" }, { "created": "Thu, 11 Jul 2024 18:09:48 GMT", "version": "v2" } ]
2024-07-15
[ [ "Kim", "Kwanyoung", "" ], [ "Oh", "Yujin", "" ], [ "Ye", "Jong Chul", "" ] ]
The recent success of CLIP has demonstrated promising results in zero-shot semantic segmentation by transferring muiltimodal knowledge to pixel-level classification. However, leveraging pre-trained CLIP knowledge to closely align text embeddings with pixel embeddings still has limitations in existing approaches. To add...
2108.04897
Bijit Hore
Bijit Hore, Ravi Jammalamadaka, Sharad Mehrotra, Amedeo D'Ascanio
Contrained Generalization For Data Anonymization - A Systematic Search Based Approach
45 pages
null
null
null
cs.DB cs.DS
http://creativecommons.org/licenses/by/4.0/
Data generalization is a powerful technique for sanitizing multi-attribute data for publication. In a multidimensional model, a subset of attributes called the quasi-identifiers (QI) are used to define the space and a generalization scheme corresponds to a partitioning of the data space. The process of sanitization c...
[ { "created": "Tue, 10 Aug 2021 19:45:27 GMT", "version": "v1" } ]
2021-08-12
[ [ "Hore", "Bijit", "" ], [ "Jammalamadaka", "Ravi", "" ], [ "Mehrotra", "Sharad", "" ], [ "D'Ascanio", "Amedeo", "" ] ]
Data generalization is a powerful technique for sanitizing multi-attribute data for publication. In a multidimensional model, a subset of attributes called the quasi-identifiers (QI) are used to define the space and a generalization scheme corresponds to a partitioning of the data space. The process of sanitization can...
2107.09133
Daniel Kunin
Daniel Kunin, Javier Sagastuy-Brena, Lauren Gillespie, Eshed Margalit, Hidenori Tanaka, Surya Ganguli, Daniel L. K. Yamins
The Limiting Dynamics of SGD: Modified Loss, Phase Space Oscillations, and Anomalous Diffusion
78 pages, 9 figures, Neural Computation 2024
Neural Computation (2024) 36 (1) 151-174
10.1162/neco_a_01626
null
cs.LG cond-mat.stat-mech q-bio.NC stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this work we explore the limiting dynamics of deep neural networks trained with stochastic gradient descent (SGD). As observed previously, long after performance has converged, networks continue to move through parameter space by a process of anomalous diffusion in which distance travelled grows as a power law in ...
[ { "created": "Mon, 19 Jul 2021 20:18:57 GMT", "version": "v1" }, { "created": "Tue, 5 Oct 2021 23:45:27 GMT", "version": "v2" }, { "created": "Thu, 2 Dec 2021 17:30:08 GMT", "version": "v3" }, { "created": "Thu, 28 Dec 2023 17:48:28 GMT", "version": "v4" } ]
2023-12-29
[ [ "Kunin", "Daniel", "" ], [ "Sagastuy-Brena", "Javier", "" ], [ "Gillespie", "Lauren", "" ], [ "Margalit", "Eshed", "" ], [ "Tanaka", "Hidenori", "" ], [ "Ganguli", "Surya", "" ], [ "Yamins", "Daniel L. K.", ...
In this work we explore the limiting dynamics of deep neural networks trained with stochastic gradient descent (SGD). As observed previously, long after performance has converged, networks continue to move through parameter space by a process of anomalous diffusion in which distance travelled grows as a power law in th...
2305.03572
Enzo Tartaglione
Marta Milovanovi\'c, Enzo Tartaglione, Marco Cagnazzo, F\'elix Henry
Learn how to Prune Pixels for Multi-view Neural Image-based Synthesis
null
null
10.1109/ICMEW59549.2023.00034
null
cs.MM cs.AI cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Image-based rendering techniques stand at the core of an immersive experience for the user, as they generate novel views given a set of multiple input images. Since they have shown good performance in terms of objective and subjective quality, the research community devotes great effort to their improvement. However,...
[ { "created": "Fri, 5 May 2023 14:29:24 GMT", "version": "v1" } ]
2023-09-13
[ [ "Milovanović", "Marta", "" ], [ "Tartaglione", "Enzo", "" ], [ "Cagnazzo", "Marco", "" ], [ "Henry", "Félix", "" ] ]
Image-based rendering techniques stand at the core of an immersive experience for the user, as they generate novel views given a set of multiple input images. Since they have shown good performance in terms of objective and subjective quality, the research community devotes great effort to their improvement. However, t...
2109.04650
Sang-Woo Lee
Boseop Kim, HyoungSeok Kim, Sang-Woo Lee, Gichang Lee, Donghyun Kwak, Dong Hyeon Jeon, Sunghyun Park, Sungju Kim, Seonhoon Kim, Dongpil Seo, Heungsub Lee, Minyoung Jeong, Sungjae Lee, Minsub Kim, Suk Hyun Ko, Seokhun Kim, Taeyong Park, Jinuk Kim, Soyoung Kang, Na-Hyeon Ryu, Kang Min Yoo, Minsuk Chang, Soobin Su...
What Changes Can Large-scale Language Models Bring? Intensive Study on HyperCLOVA: Billions-scale Korean Generative Pretrained Transformers
Accepted to EMNLP2021 as a long paper. Fixed some typos
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
GPT-3 shows remarkable in-context learning ability of large-scale language models (LMs) trained on hundreds of billion scale data. Here we address some remaining issues less reported by the GPT-3 paper, such as a non-English LM, the performances of different sized models, and the effect of recently introduced prompt ...
[ { "created": "Fri, 10 Sep 2021 03:32:19 GMT", "version": "v1" }, { "created": "Sun, 28 Nov 2021 10:56:27 GMT", "version": "v2" } ]
2021-11-30
[ [ "Kim", "Boseop", "" ], [ "Kim", "HyoungSeok", "" ], [ "Lee", "Sang-Woo", "" ], [ "Lee", "Gichang", "" ], [ "Kwak", "Donghyun", "" ], [ "Jeon", "Dong Hyeon", "" ], [ "Park", "Sunghyun", "" ], [ "Kim"...
GPT-3 shows remarkable in-context learning ability of large-scale language models (LMs) trained on hundreds of billion scale data. Here we address some remaining issues less reported by the GPT-3 paper, such as a non-English LM, the performances of different sized models, and the effect of recently introduced prompt op...
2305.18718
Augustinos Saravanos
Augustinos D. Saravanos, Yihui Li, Evangelos A. Theodorou
Distributed Hierarchical Distribution Control for Very-Large-Scale Clustered Multi-Agent Systems
Accepted at Robotics: Science and Systems 2023
null
null
null
cs.RO cs.MA cs.SY eess.SY
http://creativecommons.org/licenses/by-nc-sa/4.0/
As the scale and complexity of multi-agent robotic systems are subject to a continuous increase, this paper considers a class of systems labeled as Very-Large-Scale Multi-Agent Systems (VLMAS) with dimensionality that can scale up to the order of millions of agents. In particular, we consider the problem of steering ...
[ { "created": "Tue, 30 May 2023 03:49:29 GMT", "version": "v1" } ]
2023-05-31
[ [ "Saravanos", "Augustinos D.", "" ], [ "Li", "Yihui", "" ], [ "Theodorou", "Evangelos A.", "" ] ]
As the scale and complexity of multi-agent robotic systems are subject to a continuous increase, this paper considers a class of systems labeled as Very-Large-Scale Multi-Agent Systems (VLMAS) with dimensionality that can scale up to the order of millions of agents. In particular, we consider the problem of steering th...
2005.12444
Yuchuan Gou
Yuchuan Gou, Qiancheng Wu, Minghao Li, Bo Gong, Mei Han
SegAttnGAN: Text to Image Generation with Segmentation Attention
Accepted to the AI for Content Creation Workshop at CVPR 2020
null
null
null
cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we propose a novel generative network (SegAttnGAN) that utilizes additional segmentation information for the text-to-image synthesis task. As the segmentation data introduced to the model provides useful guidance on the generator training, the proposed model can generate images with better realism qual...
[ { "created": "Mon, 25 May 2020 23:56:41 GMT", "version": "v1" } ]
2020-05-27
[ [ "Gou", "Yuchuan", "" ], [ "Wu", "Qiancheng", "" ], [ "Li", "Minghao", "" ], [ "Gong", "Bo", "" ], [ "Han", "Mei", "" ] ]
In this paper, we propose a novel generative network (SegAttnGAN) that utilizes additional segmentation information for the text-to-image synthesis task. As the segmentation data introduced to the model provides useful guidance on the generator training, the proposed model can generate images with better realism qualit...
1107.4414
Annapurna Sharma Ms
Annapurna Sharma, Amit Purwar, Young-Dong Lee Young-Sook Lee Wan-Young Chung
Frequency based Classification of Activities using Accelerometer Data
IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, 2008. MFI 2008
null
10.1109/MFI.2008.4648056
null
cs.NE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This work presents, the classification of user activities such as Rest, Walk and Run, on the basis of frequency component present in the acceleration data in a wireless sensor network environment. As the frequencies of the above mentioned activities differ slightly for different person, so it gives a more accurate re...
[ { "created": "Fri, 22 Jul 2011 04:41:13 GMT", "version": "v1" } ]
2011-07-25
[ [ "Sharma", "Annapurna", "" ], [ "Purwar", "Amit", "" ], [ "Chung", "Young-Dong Lee Young-Sook Lee Wan-Young", "" ] ]
This work presents, the classification of user activities such as Rest, Walk and Run, on the basis of frequency component present in the acceleration data in a wireless sensor network environment. As the frequencies of the above mentioned activities differ slightly for different person, so it gives a more accurate resu...
2303.16245
Xingfu Wu
Xingfu Wu, Prasanna Balaprakash, Michael Kruse, Jaehoon Koo, Brice Videau, Paul Hovland, Valerie Taylor, Brad Geltz, Siddhartha Jana, and Mary Hall
ytopt: Autotuning Scientific Applications for Energy Efficiency at Large Scales
null
to be pushilshed in CUG2023
null
null
cs.DC cs.LG cs.PF
http://creativecommons.org/licenses/by-nc-sa/4.0/
As we enter the exascale computing era, efficiently utilizing power and optimizing the performance of scientific applications under power and energy constraints has become critical and challenging. We propose a low-overhead autotuning framework to autotune performance and energy for various hybrid MPI/OpenMP scientif...
[ { "created": "Tue, 28 Mar 2023 18:50:55 GMT", "version": "v1" } ]
2023-03-30
[ [ "Wu", "Xingfu", "" ], [ "Balaprakash", "Prasanna", "" ], [ "Kruse", "Michael", "" ], [ "Koo", "Jaehoon", "" ], [ "Videau", "Brice", "" ], [ "Hovland", "Paul", "" ], [ "Taylor", "Valerie", "" ], [ "G...
As we enter the exascale computing era, efficiently utilizing power and optimizing the performance of scientific applications under power and energy constraints has become critical and challenging. We propose a low-overhead autotuning framework to autotune performance and energy for various hybrid MPI/OpenMP scientific...
2108.09671
Jiefeng Peng
Jiefeng Peng, Jiqi Zhang, Changlin Li, Guangrun Wang, Xiaodan Liang, Liang Lin
Pi-NAS: Improving Neural Architecture Search by Reducing Supernet Training Consistency Shift
Accepted to ICCV 2021
null
null
null
cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recently proposed neural architecture search (NAS) methods co-train billions of architectures in a supernet and estimate their potential accuracy using the network weights detached from the supernet. However, the ranking correlation between the architectures' predicted accuracy and their actual capability is incorrec...
[ { "created": "Sun, 22 Aug 2021 09:08:48 GMT", "version": "v1" } ]
2021-08-24
[ [ "Peng", "Jiefeng", "" ], [ "Zhang", "Jiqi", "" ], [ "Li", "Changlin", "" ], [ "Wang", "Guangrun", "" ], [ "Liang", "Xiaodan", "" ], [ "Lin", "Liang", "" ] ]
Recently proposed neural architecture search (NAS) methods co-train billions of architectures in a supernet and estimate their potential accuracy using the network weights detached from the supernet. However, the ranking correlation between the architectures' predicted accuracy and their actual capability is incorrect,...
1803.06539
Claudio Qureshi
Claudio Qureshi and Daniel Panario
The Graph Structure of Chebyshev Polynomials over Finite Fields and Applications
null
null
null
null
cs.DM math.CO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We completely describe the functional graph associated to iterations of Chebyshev polynomials over finite fields. Then, we use our structural results to obtain estimates for the average rho length, average number of connected components and the expected value for the period and preperiod of iterating Chebyshev polyno...
[ { "created": "Sat, 17 Mar 2018 16:59:58 GMT", "version": "v1" } ]
2018-03-20
[ [ "Qureshi", "Claudio", "" ], [ "Panario", "Daniel", "" ] ]
We completely describe the functional graph associated to iterations of Chebyshev polynomials over finite fields. Then, we use our structural results to obtain estimates for the average rho length, average number of connected components and the expected value for the period and preperiod of iterating Chebyshev polynomi...
2307.16171
Sang-Hoon Lee
Sang-Hoon Lee, Ha-Yeong Choi, Hyung-Seok Oh, Seong-Whan Lee
HierVST: Hierarchical Adaptive Zero-shot Voice Style Transfer
INTERSPEECH 2023 (Oral)
null
null
null
cs.SD cs.AI cs.MM eess.AS
http://creativecommons.org/licenses/by-nc-sa/4.0/
Despite rapid progress in the voice style transfer (VST) field, recent zero-shot VST systems still lack the ability to transfer the voice style of a novel speaker. In this paper, we present HierVST, a hierarchical adaptive end-to-end zero-shot VST model. Without any text transcripts, we only use the speech dataset to...
[ { "created": "Sun, 30 Jul 2023 08:49:55 GMT", "version": "v1" } ]
2023-08-01
[ [ "Lee", "Sang-Hoon", "" ], [ "Choi", "Ha-Yeong", "" ], [ "Oh", "Hyung-Seok", "" ], [ "Lee", "Seong-Whan", "" ] ]
Despite rapid progress in the voice style transfer (VST) field, recent zero-shot VST systems still lack the ability to transfer the voice style of a novel speaker. In this paper, we present HierVST, a hierarchical adaptive end-to-end zero-shot VST model. Without any text transcripts, we only use the speech dataset to t...
0707.2293
Maziar Nekovee
Maziar Nekovee
Worm Epidemics in Wireless Adhoc Networks
null
Published in New J. Phys. 9 189, 2007
10.1088/1367-2630/9/6/189
null
cs.NI cond-mat.stat-mech cs.CR physics.soc-ph
null
A dramatic increase in the number of computing devices with wireless communication capability has resulted in the emergence of a new class of computer worms which specifically target such devices. The most striking feature of these worms is that they do not require Internet connectivity for their propagation but can ...
[ { "created": "Mon, 16 Jul 2007 09:58:18 GMT", "version": "v1" } ]
2008-07-10
[ [ "Nekovee", "Maziar", "" ] ]
A dramatic increase in the number of computing devices with wireless communication capability has resulted in the emergence of a new class of computer worms which specifically target such devices. The most striking feature of these worms is that they do not require Internet connectivity for their propagation but can sp...
2310.18338
Subhabrata Dutta
Gurusha Juneja, Subhabrata Dutta, Soumen Chakrabarti, Sunny Manchanda, Tanmoy Chakraborty
Small Language Models Fine-tuned to Coordinate Larger Language Models improve Complex Reasoning
EMNLP 2023 (Typos corrected)
null
null
null
cs.CL cs.AI
http://creativecommons.org/licenses/by/4.0/
Large Language Models (LLMs) prompted to generate chain-of-thought (CoT) exhibit impressive reasoning capabilities. Recent attempts at prompt decomposition toward solving complex, multi-step reasoning problems depend on the ability of the LLM to simultaneously decompose and solve the problem. A significant disadvanta...
[ { "created": "Sat, 21 Oct 2023 15:23:20 GMT", "version": "v1" }, { "created": "Tue, 27 Feb 2024 13:24:06 GMT", "version": "v2" } ]
2024-02-28
[ [ "Juneja", "Gurusha", "" ], [ "Dutta", "Subhabrata", "" ], [ "Chakrabarti", "Soumen", "" ], [ "Manchanda", "Sunny", "" ], [ "Chakraborty", "Tanmoy", "" ] ]
Large Language Models (LLMs) prompted to generate chain-of-thought (CoT) exhibit impressive reasoning capabilities. Recent attempts at prompt decomposition toward solving complex, multi-step reasoning problems depend on the ability of the LLM to simultaneously decompose and solve the problem. A significant disadvantage...
2210.00145
Andrea Araldo
Rosario Patan\`e, Andrea Araldo, Tijani Chahed, Diego Kiedanski, Daniel Kofman
Coalitional Game-Theoretical Approach to Coinvestment with Application to Edge Computing
null
IEEE CCNC 2023
null
null
cs.GT cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We propose in this paper a coinvestment plan between several stakeholders of different types, namely a physical network owner, operating network nodes, e.g. a network operator or a tower company, and a set of service providers willing to use these resources to provide services as video streaming, augmented reality, a...
[ { "created": "Fri, 30 Sep 2022 23:58:19 GMT", "version": "v1" } ]
2022-10-04
[ [ "Patanè", "Rosario", "" ], [ "Araldo", "Andrea", "" ], [ "Chahed", "Tijani", "" ], [ "Kiedanski", "Diego", "" ], [ "Kofman", "Daniel", "" ] ]
We propose in this paper a coinvestment plan between several stakeholders of different types, namely a physical network owner, operating network nodes, e.g. a network operator or a tower company, and a set of service providers willing to use these resources to provide services as video streaming, augmented reality, aut...
2302.10184
Zhongzhan Huang
Zhongzhan Huang, Mingfu Liang and Liang Lin
On Robust Numerical Solver for ODE via Self-Attention Mechanism
Work in progress. Technical report
null
null
null
cs.LG cs.AI cs.NA math.NA
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
With the development of deep learning techniques, AI-enhanced numerical solvers are expected to become a new paradigm for solving differential equations due to their versatility and effectiveness in alleviating the accuracy-speed trade-off in traditional numerical solvers. However, this paradigm still inevitably requ...
[ { "created": "Sun, 5 Feb 2023 01:39:21 GMT", "version": "v1" } ]
2023-02-22
[ [ "Huang", "Zhongzhan", "" ], [ "Liang", "Mingfu", "" ], [ "Lin", "Liang", "" ] ]
With the development of deep learning techniques, AI-enhanced numerical solvers are expected to become a new paradigm for solving differential equations due to their versatility and effectiveness in alleviating the accuracy-speed trade-off in traditional numerical solvers. However, this paradigm still inevitably requir...
1811.10201
AnChieh Cheng
An-Chieh Cheng, Chieh Hubert Lin, Da-Cheng Juan, Wei Wei, Min Sun
InstaNAS: Instance-aware Neural Architecture Search
null
null
null
null
cs.LG cs.CV stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Conventional Neural Architecture Search (NAS) aims at finding a single architecture that achieves the best performance, which usually optimizes task related learning objectives such as accuracy. However, a single architecture may not be representative enough for the whole dataset with high diversity and variety. Intu...
[ { "created": "Mon, 26 Nov 2018 06:29:39 GMT", "version": "v1" }, { "created": "Wed, 9 Jan 2019 14:12:40 GMT", "version": "v2" }, { "created": "Thu, 23 May 2019 09:25:04 GMT", "version": "v3" } ]
2019-05-24
[ [ "Cheng", "An-Chieh", "" ], [ "Lin", "Chieh Hubert", "" ], [ "Juan", "Da-Cheng", "" ], [ "Wei", "Wei", "" ], [ "Sun", "Min", "" ] ]
Conventional Neural Architecture Search (NAS) aims at finding a single architecture that achieves the best performance, which usually optimizes task related learning objectives such as accuracy. However, a single architecture may not be representative enough for the whole dataset with high diversity and variety. Intuit...
2405.07666
Andr\'e Chailloux
Andr\'e Chailloux and Thomas Debris-Alazard
New Solutions to Delsarte's Dual Linear Programs
null
null
null
null
cs.IT cs.DM math.IT
http://creativecommons.org/licenses/by-nc-sa/4.0/
Understanding the maximum size of a code with a given minimum distance is a major question in computer science and discrete mathematics. The most fruitful approach for finding asymptotic bounds on such codes is by using Delsarte's theory of association schemes. With this approach, Delsarte constructs a linear program...
[ { "created": "Mon, 13 May 2024 11:48:16 GMT", "version": "v1" }, { "created": "Mon, 27 May 2024 13:45:05 GMT", "version": "v2" } ]
2024-05-28
[ [ "Chailloux", "André", "" ], [ "Debris-Alazard", "Thomas", "" ] ]
Understanding the maximum size of a code with a given minimum distance is a major question in computer science and discrete mathematics. The most fruitful approach for finding asymptotic bounds on such codes is by using Delsarte's theory of association schemes. With this approach, Delsarte constructs a linear program s...
2205.06770
Otavio Carpinteiro
Alfredo J. P. Barbosa, Edmilson M. Moreira, Carlos H. V. Moraes, Ot\'avio A. S. Carpinteiro
A heuristic to determine the initial gravitational constant of the GSA
27 pages, 2 figures, 8 tables
null
null
null
cs.NE cs.AI
http://creativecommons.org/licenses/by/4.0/
The Gravitational Search Algorithm (GSA) is an optimization algorithm based on Newton's laws of gravity and dynamics. Introduced in 2009, the GSA already has several versions and applications. However, its performance depends on the values of its parameters, which are determined empirically. Hence, its generality is ...
[ { "created": "Thu, 21 Apr 2022 21:38:13 GMT", "version": "v1" } ]
2022-05-16
[ [ "Barbosa", "Alfredo J. P.", "" ], [ "Moreira", "Edmilson M.", "" ], [ "Moraes", "Carlos H. V.", "" ], [ "Carpinteiro", "Otávio A. S.", "" ] ]
The Gravitational Search Algorithm (GSA) is an optimization algorithm based on Newton's laws of gravity and dynamics. Introduced in 2009, the GSA already has several versions and applications. However, its performance depends on the values of its parameters, which are determined empirically. Hence, its generality is co...
2103.13020
Yue Yu
Chen Zeng, Yue Yu, Shanshan Li, Xin Xia, Zhiming Wang, Mingyang Geng, Bailin Xiao, Wei Dong, Xiangke Liao
deGraphCS: Embedding Variable-based Flow Graph for Neural Code Search
32 pages
null
null
null
cs.SE cs.AI
http://creativecommons.org/licenses/by/4.0/
With the rapid increase in the amount of public code repositories, developers maintain a great desire to retrieve precise code snippets by using natural language. Despite existing deep learning based approaches(e.g., DeepCS and MMAN) have provided the end-to-end solutions (i.e., accepts natural language as queries an...
[ { "created": "Wed, 24 Mar 2021 06:57:44 GMT", "version": "v1" }, { "created": "Tue, 28 Sep 2021 15:12:49 GMT", "version": "v2" }, { "created": "Sat, 16 Oct 2021 01:49:18 GMT", "version": "v3" } ]
2021-10-19
[ [ "Zeng", "Chen", "" ], [ "Yu", "Yue", "" ], [ "Li", "Shanshan", "" ], [ "Xia", "Xin", "" ], [ "Wang", "Zhiming", "" ], [ "Geng", "Mingyang", "" ], [ "Xiao", "Bailin", "" ], [ "Dong", "Wei", "...
With the rapid increase in the amount of public code repositories, developers maintain a great desire to retrieve precise code snippets by using natural language. Despite existing deep learning based approaches(e.g., DeepCS and MMAN) have provided the end-to-end solutions (i.e., accepts natural language as queries and ...
2005.06070
Ali H\"urriyeto\u{g}lu
Ali H\"urriyeto\u{g}lu, Vanni Zavarella, Hristo Tanev, Erdem Y\"or\"uk, Ali Safaya, Osman Mutlu
Automated Extraction of Socio-political Events from News (AESPEN): Workshop and Shared Task Report
null
null
null
null
cs.CL cs.CY cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We describe our effort on automated extraction of socio-political events from news in the scope of a workshop and a shared task we organized at Language Resources and Evaluation Conference (LREC 2020). We believe the event extraction studies in computational linguistics and social and political sciences should furthe...
[ { "created": "Tue, 12 May 2020 22:07:14 GMT", "version": "v1" } ]
2020-05-14
[ [ "Hürriyetoğlu", "Ali", "" ], [ "Zavarella", "Vanni", "" ], [ "Tanev", "Hristo", "" ], [ "Yörük", "Erdem", "" ], [ "Safaya", "Ali", "" ], [ "Mutlu", "Osman", "" ] ]
We describe our effort on automated extraction of socio-political events from news in the scope of a workshop and a shared task we organized at Language Resources and Evaluation Conference (LREC 2020). We believe the event extraction studies in computational linguistics and social and political sciences should further ...
2103.03206
Andrew Jaegle
Andrew Jaegle and Felix Gimeno and Andrew Brock and Andrew Zisserman and Oriol Vinyals and Joao Carreira
Perceiver: General Perception with Iterative Attention
ICML 2021
null
null
null
cs.CV cs.AI cs.LG cs.SD eess.AS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Biological systems perceive the world by simultaneously processing high-dimensional inputs from modalities as diverse as vision, audition, touch, proprioception, etc. The perception models used in deep learning on the other hand are designed for individual modalities, often relying on domain-specific assumptions such...
[ { "created": "Thu, 4 Mar 2021 18:20:50 GMT", "version": "v1" }, { "created": "Wed, 23 Jun 2021 00:25:31 GMT", "version": "v2" } ]
2021-06-24
[ [ "Jaegle", "Andrew", "" ], [ "Gimeno", "Felix", "" ], [ "Brock", "Andrew", "" ], [ "Zisserman", "Andrew", "" ], [ "Vinyals", "Oriol", "" ], [ "Carreira", "Joao", "" ] ]
Biological systems perceive the world by simultaneously processing high-dimensional inputs from modalities as diverse as vision, audition, touch, proprioception, etc. The perception models used in deep learning on the other hand are designed for individual modalities, often relying on domain-specific assumptions such a...
2111.07765
Jobst Landgrebe
Jobst Landgrebe, Barry Smith
An argument for the impossibility of machine intelligence
null
null
null
null
cs.AI
http://creativecommons.org/licenses/by-nc-nd/4.0/
Since the noun phrase `artificial intelligence' (AI) was coined, it has been debated whether humans are able to create intelligence using technology. We shed new light on this question from the point of view of themodynamics and mathematics. First, we define what it is to be an agent (device) that could be the bearer...
[ { "created": "Wed, 20 Oct 2021 08:54:48 GMT", "version": "v1" } ]
2021-11-16
[ [ "Landgrebe", "Jobst", "" ], [ "Smith", "Barry", "" ] ]
Since the noun phrase `artificial intelligence' (AI) was coined, it has been debated whether humans are able to create intelligence using technology. We shed new light on this question from the point of view of themodynamics and mathematics. First, we define what it is to be an agent (device) that could be the bearer o...
1903.00922
Benedikt Ahrens
Benedikt Ahrens, Andr\'e Hirschowitz, Ambroise Lafont, Marco Maggesi
Modular specification of monads through higher-order presentations
17 pages
Formal Structures for Computation and Deduction (FSCD) 2019, LIPIcs Vol. 131, pp. 6:1-6:19
10.4230/LIPIcs.FSCD.2019.6
null
cs.LO math.LO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In their work on second-order equational logic, Fiore and Hur have studied presentations of simply typed languages by generating binding constructions and equations among them. To each pair consisting of a binding signature and a set of equations, they associate a category of `models', and they give a monadicity resu...
[ { "created": "Sun, 3 Mar 2019 15:00:36 GMT", "version": "v1" } ]
2019-07-16
[ [ "Ahrens", "Benedikt", "" ], [ "Hirschowitz", "André", "" ], [ "Lafont", "Ambroise", "" ], [ "Maggesi", "Marco", "" ] ]
In their work on second-order equational logic, Fiore and Hur have studied presentations of simply typed languages by generating binding constructions and equations among them. To each pair consisting of a binding signature and a set of equations, they associate a category of `models', and they give a monadicity result...
2310.17193
Ryota Tanaka
Ryota Tanaka, Tomohiro Suzuki, Kazuya Takeda, Keisuke Fujii
Automatic Edge Error Judgment in Figure Skating Using 3D Pose Estimation from a Monocular Camera and IMUs
null
null
null
null
cs.MM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Automatic evaluating systems are fundamental issues in sports technologies. In many sports, such as figure skating, automated evaluating methods based on pose estimation have been proposed. However, previous studies have evaluated skaters' skills in 2D analysis. In this paper, we propose an automatic edge error judgm...
[ { "created": "Thu, 26 Oct 2023 07:15:40 GMT", "version": "v1" } ]
2023-10-27
[ [ "Tanaka", "Ryota", "" ], [ "Suzuki", "Tomohiro", "" ], [ "Takeda", "Kazuya", "" ], [ "Fujii", "Keisuke", "" ] ]
Automatic evaluating systems are fundamental issues in sports technologies. In many sports, such as figure skating, automated evaluating methods based on pose estimation have been proposed. However, previous studies have evaluated skaters' skills in 2D analysis. In this paper, we propose an automatic edge error judgmen...
1607.02133
Fan Yang
Fan Yang and Andrew A. Chien
Extreme Scaling of Supercomputing with Stranded Power: Costs and Capabilities
12 pages, 22 figures
null
null
null
cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Power consumption (supply, heat, cost) and associated carbon emissions (environmental impact) are increasingly critical challenges in scaling supercomputing to Exascale and beyond. We proposes to exploit stranded power, renewable energy that has no value to the power grid, for scaling supercomputers, Zero-Carbon Clou...
[ { "created": "Thu, 7 Jul 2016 19:31:37 GMT", "version": "v1" } ]
2016-07-08
[ [ "Yang", "Fan", "" ], [ "Chien", "Andrew A.", "" ] ]
Power consumption (supply, heat, cost) and associated carbon emissions (environmental impact) are increasingly critical challenges in scaling supercomputing to Exascale and beyond. We proposes to exploit stranded power, renewable energy that has no value to the power grid, for scaling supercomputers, Zero-Carbon Cloud ...
1001.3497
William Jackson
Shahid Hussain, Sheikh Muhammad Saqib, Bashir Ahmad, Shakeel Ahmad
Mapping of SOA and RUP: DOA as Case Study
Journal of Computing, Vol. 2, Issue 1, January 2010, https://sites.google.com/site/journalofcomputing/
Journal of Computing, Vol. 2, Issue 1, January 2010, https://sites.google.com/site/journalofcomputing/
null
null
cs.SE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
SOA (Service Oriented Architecture) is a new trend towards increasing the profit margins in an organization due to incorporating business services to business practices. Rational Unified Process (RUP) is a unified method planning form for large business applications that provides a language for describing method cont...
[ { "created": "Wed, 20 Jan 2010 08:11:10 GMT", "version": "v1" }, { "created": "Mon, 29 Mar 2010 07:37:16 GMT", "version": "v2" } ]
2010-03-30
[ [ "Hussain", "Shahid", "" ], [ "Saqib", "Sheikh Muhammad", "" ], [ "Ahmad", "Bashir", "" ], [ "Ahmad", "Shakeel", "" ] ]
SOA (Service Oriented Architecture) is a new trend towards increasing the profit margins in an organization due to incorporating business services to business practices. Rational Unified Process (RUP) is a unified method planning form for large business applications that provides a language for describing method conten...
2111.04746
Max Hopkins
Max Hopkins, Daniel M. Kane, Shachar Lovett, Gaurav Mahajan
Realizable Learning is All You Need
null
TheoretiCS, Volume 3 (February 6, 2024) theoretics:10093
10.46298/theoretics.24.2
null
cs.LG stat.ML
http://creativecommons.org/licenses/by/4.0/
The equivalence of realizable and agnostic learnability is a fundamental phenomenon in learning theory. With variants ranging from classical settings like PAC learning and regression to recent trends such as adversarially robust learning, it's surprising that we still lack a unified theory; traditional proofs of the ...
[ { "created": "Mon, 8 Nov 2021 19:00:00 GMT", "version": "v1" }, { "created": "Sun, 25 Sep 2022 08:34:25 GMT", "version": "v2" }, { "created": "Fri, 3 Feb 2023 12:06:15 GMT", "version": "v3" }, { "created": "Sat, 3 Feb 2024 00:55:16 GMT", "version": "v4" } ]
2024-08-07
[ [ "Hopkins", "Max", "" ], [ "Kane", "Daniel M.", "" ], [ "Lovett", "Shachar", "" ], [ "Mahajan", "Gaurav", "" ] ]
The equivalence of realizable and agnostic learnability is a fundamental phenomenon in learning theory. With variants ranging from classical settings like PAC learning and regression to recent trends such as adversarially robust learning, it's surprising that we still lack a unified theory; traditional proofs of the eq...
2108.01753
Andrew Reed
Andrew C. Reed, Michael K. Reiter
Optimally Hiding Object Sizes with Constrained Padding
null
null
null
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Among the most challenging traffic-analysis attacks to confound are those leveraging the sizes of objects downloaded over the network. In this paper we systematically analyze this problem under realistic constraints regarding the padding overhead that the object store is willing to incur. We give algorithms to comput...
[ { "created": "Tue, 3 Aug 2021 21:14:13 GMT", "version": "v1" } ]
2021-08-05
[ [ "Reed", "Andrew C.", "" ], [ "Reiter", "Michael K.", "" ] ]
Among the most challenging traffic-analysis attacks to confound are those leveraging the sizes of objects downloaded over the network. In this paper we systematically analyze this problem under realistic constraints regarding the padding overhead that the object store is willing to incur. We give algorithms to compute ...
2304.03985
Anoop S. K. M.
Anoop S. K. M., Jayalal Sarma
On Rotation Distance of Rank Bounded Trees
28 pages, 2 figures, Abstract shortened to meet arxiv requirements, accepted journal version
Fundamenta Informaticae, Volume 191, Issue 2 (July 8, 2024) fi:11200
null
null
cs.DS
http://creativecommons.org/licenses/by/4.0/
Computing the rotation distance between two binary trees with $n$ internal nodes efficiently (in $poly(n)$ time) is a long standing open question in the study of height balancing in tree data structures. In this paper, we initiate the study of this problem bounding the rank of the trees given at the input (defined by...
[ { "created": "Sat, 8 Apr 2023 11:02:35 GMT", "version": "v1" }, { "created": "Thu, 21 Mar 2024 15:42:46 GMT", "version": "v2" }, { "created": "Fri, 10 May 2024 18:18:05 GMT", "version": "v3" } ]
2024-08-07
[ [ "M.", "Anoop S. K.", "" ], [ "Sarma", "Jayalal", "" ] ]
Computing the rotation distance between two binary trees with $n$ internal nodes efficiently (in $poly(n)$ time) is a long standing open question in the study of height balancing in tree data structures. In this paper, we initiate the study of this problem bounding the rank of the trees given at the input (defined by E...
1811.10855
Chen Yang
Chen Yang, Xiaofeng Meng, Zhihui Du, Zhiqiang Duan and Yongjie Du
Data Management in Time-Domain Astronomy: Requirements and Challenges
null
null
null
null
cs.DB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In time-domain astronomy, we need to use the relational database to manage star catalog data. With the development of sky survey technology, the size of star catalog data is larger, and the speed of data generation is faster. So, in this paper, we make a systematic and comprehensive introduction to process the data i...
[ { "created": "Tue, 27 Nov 2018 07:54:43 GMT", "version": "v1" } ]
2018-11-28
[ [ "Yang", "Chen", "" ], [ "Meng", "Xiaofeng", "" ], [ "Du", "Zhihui", "" ], [ "Duan", "Zhiqiang", "" ], [ "Du", "Yongjie", "" ] ]
In time-domain astronomy, we need to use the relational database to manage star catalog data. With the development of sky survey technology, the size of star catalog data is larger, and the speed of data generation is faster. So, in this paper, we make a systematic and comprehensive introduction to process the data in ...
2406.13793
Minghao Cai
Minghao Cai, and Carrie Demmans Epp
Exploring the Optimal Time Window for Predicting Cognitive Load Using Physiological Sensor Data
Presented at PhysioCHI: Towards Best Practices for Integrating Physiological Signals in HCI, May 11, 2024, Honolulu, HI, USA
null
null
null
cs.HC
http://creativecommons.org/licenses/by/4.0/
Learning analytics has begun to use physiological signals because these have been linked with learners' cognitive and affective states. These signals, when interpreted through machine learning techniques, offer a nuanced understanding of the temporal dynamics of student learning experiences and processes. However, th...
[ { "created": "Wed, 19 Jun 2024 19:39:14 GMT", "version": "v1" } ]
2024-06-21
[ [ "Cai", "Minghao", "" ], [ "Epp", "Carrie Demmans", "" ] ]
Learning analytics has begun to use physiological signals because these have been linked with learners' cognitive and affective states. These signals, when interpreted through machine learning techniques, offer a nuanced understanding of the temporal dynamics of student learning experiences and processes. However, ther...
2405.11708
Shao-Yuan Lo
Shao-Yuan Lo, Vishal M. Patel
Adaptive Batch Normalization Networks for Adversarial Robustness
Accepted at IEEE International Conference on Advanced Video and Signal-based Surveillance (AVSS) 2024
null
null
null
cs.LG cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Deep networks are vulnerable to adversarial examples. Adversarial Training (AT) has been a standard foundation of modern adversarial defense approaches due to its remarkable effectiveness. However, AT is extremely time-consuming, refraining it from wide deployment in practical applications. In this paper, we aim at a...
[ { "created": "Mon, 20 May 2024 00:58:53 GMT", "version": "v1" }, { "created": "Mon, 27 May 2024 00:38:08 GMT", "version": "v2" } ]
2024-05-28
[ [ "Lo", "Shao-Yuan", "" ], [ "Patel", "Vishal M.", "" ] ]
Deep networks are vulnerable to adversarial examples. Adversarial Training (AT) has been a standard foundation of modern adversarial defense approaches due to its remarkable effectiveness. However, AT is extremely time-consuming, refraining it from wide deployment in practical applications. In this paper, we aim at a n...
1403.2294
Sergey Nikolaev
Sergei Nikolaev
Non-linear mass-spring system for large soft tissue deformations modeling
9 pages, 2 figures, 4 charts
Scientific and Technical Journal of Information Technologies, Mechanics and Optics 5(87) (2013) 88-94
null
null
cs.NA physics.comp-ph
http://creativecommons.org/licenses/by-nc-sa/3.0/
Implant placement under soft tissues operation is described. In this operation tissues can reach such deformations that nonlinear properties are appeared. A mass-spring model modification for modeling nonlinear tissue operation is developed. A method for creating elasticity module using splines is described. For Pois...
[ { "created": "Mon, 10 Mar 2014 16:34:40 GMT", "version": "v1" } ]
2014-03-11
[ [ "Nikolaev", "Sergei", "" ] ]
Implant placement under soft tissues operation is described. In this operation tissues can reach such deformations that nonlinear properties are appeared. A mass-spring model modification for modeling nonlinear tissue operation is developed. A method for creating elasticity module using splines is described. For Poisso...
1802.08249
Maziar Sanjabi
Maziar Sanjabi, Jimmy Ba, Meisam Razaviyayn, Jason D. Lee
On the Convergence and Robustness of Training GANs with Regularized Optimal Transport
null
null
null
null
cs.LG math.OC stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Generative Adversarial Networks (GANs) are one of the most practical methods for learning data distributions. A popular GAN formulation is based on the use of Wasserstein distance as a metric between probability distributions. Unfortunately, minimizing the Wasserstein distance between the data distribution and the ge...
[ { "created": "Thu, 22 Feb 2018 04:11:58 GMT", "version": "v1" }, { "created": "Tue, 22 May 2018 05:11:47 GMT", "version": "v2" } ]
2018-05-23
[ [ "Sanjabi", "Maziar", "" ], [ "Ba", "Jimmy", "" ], [ "Razaviyayn", "Meisam", "" ], [ "Lee", "Jason D.", "" ] ]
Generative Adversarial Networks (GANs) are one of the most practical methods for learning data distributions. A popular GAN formulation is based on the use of Wasserstein distance as a metric between probability distributions. Unfortunately, minimizing the Wasserstein distance between the data distribution and the gene...
2112.06921
Letitia Sabburg
Letitia Sabburg, Alan Woodley and Kerrie Mengersen
A Data- and Task- Oriented Design Framework for Bivariate Communication of Uncertainty
null
null
null
null
cs.HC
http://creativecommons.org/licenses/by-sa/4.0/
The communication of uncertainty estimates, predictions and insights based on spatio-temporal models is important for decision-making as it impacts the utilisation and interpretation of information. Bivariate mapping is commonly used for communication of estimates and associated uncertainty; however, it is known that...
[ { "created": "Mon, 13 Dec 2021 05:37:16 GMT", "version": "v1" } ]
2021-12-15
[ [ "Sabburg", "Letitia", "" ], [ "Woodley", "Alan", "" ], [ "Mengersen", "Kerrie", "" ] ]
The communication of uncertainty estimates, predictions and insights based on spatio-temporal models is important for decision-making as it impacts the utilisation and interpretation of information. Bivariate mapping is commonly used for communication of estimates and associated uncertainty; however, it is known that d...