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2303.09092
Ian Porada
Ian Porada, Alexandra Olteanu, Kaheer Suleman, Adam Trischler, Jackie Chi Kit Cheung
Challenges to Evaluating the Generalization of Coreference Resolution Models: A Measurement Modeling Perspective
ACL Findings 2024
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
It is increasingly common to evaluate the same coreference resolution (CR) model on multiple datasets. Do these multi-dataset evaluations allow us to draw meaningful conclusions about model generalization? Or, do they rather reflect the idiosyncrasies of a particular experimental setup (e.g., the specific datasets us...
[ { "created": "Thu, 16 Mar 2023 05:32:02 GMT", "version": "v1" }, { "created": "Tue, 18 Jun 2024 16:19:36 GMT", "version": "v2" } ]
2024-06-19
[ [ "Porada", "Ian", "" ], [ "Olteanu", "Alexandra", "" ], [ "Suleman", "Kaheer", "" ], [ "Trischler", "Adam", "" ], [ "Cheung", "Jackie Chi Kit", "" ] ]
It is increasingly common to evaluate the same coreference resolution (CR) model on multiple datasets. Do these multi-dataset evaluations allow us to draw meaningful conclusions about model generalization? Or, do they rather reflect the idiosyncrasies of a particular experimental setup (e.g., the specific datasets used...
2207.01498
Heinrich S\"obke
Sebastian Damek, Heinrich S\"obke, Franziska Weise and Maria Reichelt
(Meta) Competences for Digital Practice: Educational Scenarios for the Workplace of the Future Exemplified by Building Information Modeling Work Processes
14 pages, 6 figures, 3 tables
null
10.3390/knowledge2030027
null
cs.CY
http://creativecommons.org/licenses/by/4.0/
Workplaces of the future require advanced competence profiles from employees, not least due to new options for teleworking and new complex digital tools. The acquisition of advanced competence profiles is to be addressed by formal education. For example, the method of Building Information Modeling (BIM) aims at digit...
[ { "created": "Thu, 9 Jun 2022 18:33:14 GMT", "version": "v1" } ]
2022-09-05
[ [ "Damek", "Sebastian", "" ], [ "Söbke", "Heinrich", "" ], [ "Weise", "Franziska", "" ], [ "Reichelt", "Maria", "" ] ]
Workplaces of the future require advanced competence profiles from employees, not least due to new options for teleworking and new complex digital tools. The acquisition of advanced competence profiles is to be addressed by formal education. For example, the method of Building Information Modeling (BIM) aims at digitiz...
1702.05192
Mohammad-Parsa Hosseini
Mohammad-Parsa Hosseini, Hamid Soltanian-Zadeh, Kost Elisevich, and Dario Pompili
Cloud-based Deep Learning of Big EEG Data for Epileptic Seizure Prediction
IEEE Global Conference on Signal and Information Processing (GlobalSIP), Greater Washington, DC, Dec 7-9, 2016
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Developing a Brain-Computer Interface~(BCI) for seizure prediction can help epileptic patients have a better quality of life. However, there are many difficulties and challenges in developing such a system as a real-life support for patients. Because of the nonstationary nature of EEG signals, normal and seizure patt...
[ { "created": "Fri, 17 Feb 2017 00:00:38 GMT", "version": "v1" } ]
2017-02-20
[ [ "Hosseini", "Mohammad-Parsa", "" ], [ "Soltanian-Zadeh", "Hamid", "" ], [ "Elisevich", "Kost", "" ], [ "Pompili", "Dario", "" ] ]
Developing a Brain-Computer Interface~(BCI) for seizure prediction can help epileptic patients have a better quality of life. However, there are many difficulties and challenges in developing such a system as a real-life support for patients. Because of the nonstationary nature of EEG signals, normal and seizure patter...
2107.12193
Muhammad Bilal
Muhammad Basit Umair, Zeshan Iqbal, Muhammad Bilal, Tarik Adnan Almohamad, Jamel Nebhen, Raja Majid Mehmood
An Efficient Internet Traffic Classification System Using Deep Learning for IoT
14 pages, 4 figures, 11 tables, Accepted for publication in CMC-Computers, Materials & Continua
CMC-Computers, Materials and Continua, 71(1), 407-422, 2022
10.32604/cmc.2022.020727
null
cs.NI
http://creativecommons.org/licenses/by/4.0/
Internet of Things (IoT) defines a network of devices connected to the internet and sharing a massive amount of data between each other and a central location. These IoT devices are connected to a network therefore prone to attacks. Various management tasks and network operations such as security, intrusion detection...
[ { "created": "Mon, 26 Jul 2021 12:58:15 GMT", "version": "v1" } ]
2021-11-16
[ [ "Umair", "Muhammad Basit", "" ], [ "Iqbal", "Zeshan", "" ], [ "Bilal", "Muhammad", "" ], [ "Almohamad", "Tarik Adnan", "" ], [ "Nebhen", "Jamel", "" ], [ "Mehmood", "Raja Majid", "" ] ]
Internet of Things (IoT) defines a network of devices connected to the internet and sharing a massive amount of data between each other and a central location. These IoT devices are connected to a network therefore prone to attacks. Various management tasks and network operations such as security, intrusion detection, ...
1808.08622
James Ferguson
James Ferguson, Colin Lockard, Daniel S. Weld, Hannaneh Hajishirzi
Semi-Supervised Event Extraction with Paraphrase Clusters
NAACL 2018
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Supervised event extraction systems are limited in their accuracy due to the lack of available training data. We present a method for self-training event extraction systems by bootstrapping additional training data. This is done by taking advantage of the occurrence of multiple mentions of the same event instances ac...
[ { "created": "Sun, 26 Aug 2018 21:12:43 GMT", "version": "v1" } ]
2018-08-28
[ [ "Ferguson", "James", "" ], [ "Lockard", "Colin", "" ], [ "Weld", "Daniel S.", "" ], [ "Hajishirzi", "Hannaneh", "" ] ]
Supervised event extraction systems are limited in their accuracy due to the lack of available training data. We present a method for self-training event extraction systems by bootstrapping additional training data. This is done by taking advantage of the occurrence of multiple mentions of the same event instances acro...
2009.07834
Andriy Miranskyy
William Pourmajidi and Lei Zhang and John Steinbacher and Tony Erwin and Andriy Miranskyy
Immutable Log Storage as a Service on Private and Public Blockchains
Accepted for publication in IEEE Transactions on Services Computing
null
10.1109/TSC.2021.3120690
null
cs.SE cs.CR cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Service Level Agreements (SLA) are employed to ensure the performance of Cloud solutions. When a component fails, the importance of logs increases significantly. All departments may turn to logs to determine the cause of the issue and find the party at fault. The party at fault may be motivated to tamper with the log...
[ { "created": "Wed, 16 Sep 2020 17:51:48 GMT", "version": "v1" }, { "created": "Wed, 6 Oct 2021 14:16:37 GMT", "version": "v2" } ]
2021-11-03
[ [ "Pourmajidi", "William", "" ], [ "Zhang", "Lei", "" ], [ "Steinbacher", "John", "" ], [ "Erwin", "Tony", "" ], [ "Miranskyy", "Andriy", "" ] ]
Service Level Agreements (SLA) are employed to ensure the performance of Cloud solutions. When a component fails, the importance of logs increases significantly. All departments may turn to logs to determine the cause of the issue and find the party at fault. The party at fault may be motivated to tamper with the logs ...
2003.11650
Asia Biega
Asia J. Biega, Fernando Diaz, Michael D. Ekstrand, Sebastian Kohlmeier
Overview of the TREC 2019 Fair Ranking Track
Published in The Twenty-Eighth Text REtrieval Conference Proceedings (TREC 2019)
null
null
null
cs.IR cs.DL cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The goal of the TREC Fair Ranking track was to develop a benchmark for evaluating retrieval systems in terms of fairness to different content providers in addition to classic notions of relevance. As part of the benchmark, we defined standardized fairness metrics with evaluation protocols and released a dataset for t...
[ { "created": "Wed, 25 Mar 2020 21:34:58 GMT", "version": "v1" } ]
2020-03-27
[ [ "Biega", "Asia J.", "" ], [ "Diaz", "Fernando", "" ], [ "Ekstrand", "Michael D.", "" ], [ "Kohlmeier", "Sebastian", "" ] ]
The goal of the TREC Fair Ranking track was to develop a benchmark for evaluating retrieval systems in terms of fairness to different content providers in addition to classic notions of relevance. As part of the benchmark, we defined standardized fairness metrics with evaluation protocols and released a dataset for the...
1712.07195
Wei Shen
Wei Shen, Yilu Guo, Yan Wang, Kai Zhao, Bo Wang, Alan Yuille
Deep Regression Forests for Age Estimation
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Age estimation from facial images is typically cast as a nonlinear regression problem. The main challenge of this problem is the facial feature space w.r.t. ages is heterogeneous, due to the large variation in facial appearance across different persons of the same age and the non-stationary property of aging patterns...
[ { "created": "Tue, 19 Dec 2017 20:42:15 GMT", "version": "v1" } ]
2017-12-21
[ [ "Shen", "Wei", "" ], [ "Guo", "Yilu", "" ], [ "Wang", "Yan", "" ], [ "Zhao", "Kai", "" ], [ "Wang", "Bo", "" ], [ "Yuille", "Alan", "" ] ]
Age estimation from facial images is typically cast as a nonlinear regression problem. The main challenge of this problem is the facial feature space w.r.t. ages is heterogeneous, due to the large variation in facial appearance across different persons of the same age and the non-stationary property of aging patterns. ...
1902.01437
Junhao Li
Junhao Li, Hang Zhang
Blaze: Simplified High Performance Cluster Computing
null
null
null
null
cs.DC cs.AI cs.LG cs.PF
http://creativecommons.org/licenses/by-nc-sa/4.0/
MapReduce and its variants have significantly simplified and accelerated the process of developing parallel programs. However, most MapReduce implementations focus on data-intensive tasks while many real-world tasks are compute intensive and their data can fit distributedly into the memory. For these tasks, the speed...
[ { "created": "Mon, 4 Feb 2019 19:28:15 GMT", "version": "v1" }, { "created": "Wed, 6 Feb 2019 02:59:19 GMT", "version": "v2" } ]
2019-02-07
[ [ "Li", "Junhao", "" ], [ "Zhang", "Hang", "" ] ]
MapReduce and its variants have significantly simplified and accelerated the process of developing parallel programs. However, most MapReduce implementations focus on data-intensive tasks while many real-world tasks are compute intensive and their data can fit distributedly into the memory. For these tasks, the speed o...
1612.01655
Xin Yang
Xin Yang, Lequan Yu, Lingyun Wu, Yi Wang, Dong Ni, Jing Qin, Pheng-Ann Heng
Fine-grained Recurrent Neural Networks for Automatic Prostate Segmentation in Ultrasound Images
To appear in AAAI Conference 2017
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Boundary incompleteness raises great challenges to automatic prostate segmentation in ultrasound images. Shape prior can provide strong guidance in estimating the missing boundary, but traditional shape models often suffer from hand-crafted descriptors and local information loss in the fitting procedure. In this pape...
[ { "created": "Tue, 6 Dec 2016 03:56:07 GMT", "version": "v1" } ]
2016-12-07
[ [ "Yang", "Xin", "" ], [ "Yu", "Lequan", "" ], [ "Wu", "Lingyun", "" ], [ "Wang", "Yi", "" ], [ "Ni", "Dong", "" ], [ "Qin", "Jing", "" ], [ "Heng", "Pheng-Ann", "" ] ]
Boundary incompleteness raises great challenges to automatic prostate segmentation in ultrasound images. Shape prior can provide strong guidance in estimating the missing boundary, but traditional shape models often suffer from hand-crafted descriptors and local information loss in the fitting procedure. In this paper,...
1306.5726
Kuldeep Meel
Supratik Chakraborty and Kuldeep S. Meel and Moshe Y. Vardi
A Scalable Approximate Model Counter
Conference version will appear in CP 2013
null
null
null
cs.LO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Propositional model counting} (#SAT), i.e., counting the number of satisfying assignments of a propositional formula, is a problem of significant theoretical and practical interest. Due to the inherent complexity of the problem, approximate model counting, which counts the number of satisfying assignments to within g...
[ { "created": "Mon, 24 Jun 2013 19:51:33 GMT", "version": "v1" }, { "created": "Tue, 25 Jun 2013 18:41:58 GMT", "version": "v2" }, { "created": "Sun, 7 Jul 2013 05:40:29 GMT", "version": "v3" } ]
2013-07-09
[ [ "Chakraborty", "Supratik", "" ], [ "Meel", "Kuldeep S.", "" ], [ "Vardi", "Moshe Y.", "" ] ]
Propositional model counting} (#SAT), i.e., counting the number of satisfying assignments of a propositional formula, is a problem of significant theoretical and practical interest. Due to the inherent complexity of the problem, approximate model counting, which counts the number of satisfying assignments to within giv...
2010.01657
Wei-Jen Ko
Wei-Jen Ko and Te-Yuan Chen and Yiyan Huang and Greg Durrett and Junyi Jessy Li
Inquisitive Question Generation for High Level Text Comprehension
EMNLP 2020
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Inquisitive probing questions come naturally to humans in a variety of settings, but is a challenging task for automatic systems. One natural type of question to ask tries to fill a gap in knowledge during text comprehension, like reading a news article: we might ask about background information, deeper reasons behin...
[ { "created": "Sun, 4 Oct 2020 19:03:39 GMT", "version": "v1" } ]
2020-10-06
[ [ "Ko", "Wei-Jen", "" ], [ "Chen", "Te-Yuan", "" ], [ "Huang", "Yiyan", "" ], [ "Durrett", "Greg", "" ], [ "Li", "Junyi Jessy", "" ] ]
Inquisitive probing questions come naturally to humans in a variety of settings, but is a challenging task for automatic systems. One natural type of question to ask tries to fill a gap in knowledge during text comprehension, like reading a news article: we might ask about background information, deeper reasons behind ...
1401.1913
J\"urgen M\"unch
Adam Trendowicz, Michael Kl\"as, Constanza Lampasona, J\"urgen M\"unch, Christian K\"orner, Matthias Saft
Model-based Product Quality Evaluation with Multi-Criteria Decision Analysis
18 pages. The final publication is available at http://www.shaker.de/de/content/catalogue/index.asp? lang=de&ID=8&ISBN=978-3-8322-9618-6
Proceedings of the International Conference on Software Process and Product Measurement (IWSM/MetriKon/Mensura 2010), pages 3-20, Stuttgart, Germany, November 10-12 2010
null
null
cs.SE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The ability to develop or evolve software or software-based systems/services with defined and guaranteed quality in a predictable way is becoming increasingly important. Essential - though not exclusive - prerequisites for this are the ability to model the relevant quality properties appropriately and the capability ...
[ { "created": "Thu, 9 Jan 2014 07:47:58 GMT", "version": "v1" } ]
2014-01-10
[ [ "Trendowicz", "Adam", "" ], [ "Kläs", "Michael", "" ], [ "Lampasona", "Constanza", "" ], [ "Münch", "Jürgen", "" ], [ "Körner", "Christian", "" ], [ "Saft", "Matthias", "" ] ]
The ability to develop or evolve software or software-based systems/services with defined and guaranteed quality in a predictable way is becoming increasingly important. Essential - though not exclusive - prerequisites for this are the ability to model the relevant quality properties appropriately and the capability to...
2012.13976
Raghavendra Addanki
Raghavendra Addanki, Andrew McGregor, Cameron Musco
Intervention Efficient Algorithms for Approximate Learning of Causal Graphs
To appear, International Conference on Algorithmic Learning Theory(ALT) 2021
null
null
null
cs.DS cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We study the problem of learning the causal relationships between a set of observed variables in the presence of latents, while minimizing the cost of interventions on the observed variables. We assume access to an undirected graph $G$ on the observed variables whose edges represent either all direct causal relations...
[ { "created": "Sun, 27 Dec 2020 17:08:46 GMT", "version": "v1" } ]
2020-12-29
[ [ "Addanki", "Raghavendra", "" ], [ "McGregor", "Andrew", "" ], [ "Musco", "Cameron", "" ] ]
We study the problem of learning the causal relationships between a set of observed variables in the presence of latents, while minimizing the cost of interventions on the observed variables. We assume access to an undirected graph $G$ on the observed variables whose edges represent either all direct causal relationshi...
1707.02647
Mohammad Motamedi
Mohammad Motamedi, Daniel Fong, and Soheil Ghiasi
Cappuccino: Efficient Inference Software Synthesis for Mobile System-on-Chips
4 pages, 7 figures
null
null
null
cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Convolutional Neural Networks (CNNs) exhibit remarkable performance in various machine learning tasks. As sensor-equipped Internet of Things (IoT) devices permeate into every aspect of modern life, the ability to execute CNN inference, a computationally intensive application, on resource constrained devices has becom...
[ { "created": "Sun, 9 Jul 2017 22:03:05 GMT", "version": "v1" } ]
2017-07-11
[ [ "Motamedi", "Mohammad", "" ], [ "Fong", "Daniel", "" ], [ "Ghiasi", "Soheil", "" ] ]
Convolutional Neural Networks (CNNs) exhibit remarkable performance in various machine learning tasks. As sensor-equipped Internet of Things (IoT) devices permeate into every aspect of modern life, the ability to execute CNN inference, a computationally intensive application, on resource constrained devices has become ...
2407.21762
Mei Aoran
Aoran Mei, Guo-Niu Zhu, Huaxiang Zhang, and Zhongxue Gan
ReplanVLM: Replanning Robotic Tasks with Visual Language Models
null
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Large language models (LLMs) have gained increasing popularity in robotic task planning due to their exceptional abilities in text analytics and generation, as well as their broad knowledge of the world. However, they fall short in decoding visual cues. LLMs have limited direct perception of the world, which leads to...
[ { "created": "Wed, 31 Jul 2024 17:31:01 GMT", "version": "v1" } ]
2024-08-01
[ [ "Mei", "Aoran", "" ], [ "Zhu", "Guo-Niu", "" ], [ "Zhang", "Huaxiang", "" ], [ "Gan", "Zhongxue", "" ] ]
Large language models (LLMs) have gained increasing popularity in robotic task planning due to their exceptional abilities in text analytics and generation, as well as their broad knowledge of the world. However, they fall short in decoding visual cues. LLMs have limited direct perception of the world, which leads to a...
2407.21374
Eran Bamani
Eran Bamani Beeri, Eden Nissinman, Avishai Sintov
Dynamic Gesture Recognition in Ultra-Range Distance for Effective Human-Robot Interaction
null
null
null
null
cs.RO cs.CV cs.LG
http://creativecommons.org/licenses/by/4.0/
This paper presents a novel approach for ultra-range gesture recognition, addressing Human-Robot Interaction (HRI) challenges over extended distances. By leveraging human gestures in video data, we propose the Temporal-Spatiotemporal Fusion Network (TSFN) model that surpasses the limitations of current methods, enabl...
[ { "created": "Wed, 31 Jul 2024 06:56:46 GMT", "version": "v1" } ]
2024-08-01
[ [ "Beeri", "Eran Bamani", "" ], [ "Nissinman", "Eden", "" ], [ "Sintov", "Avishai", "" ] ]
This paper presents a novel approach for ultra-range gesture recognition, addressing Human-Robot Interaction (HRI) challenges over extended distances. By leveraging human gestures in video data, we propose the Temporal-Spatiotemporal Fusion Network (TSFN) model that surpasses the limitations of current methods, enablin...
2109.14376
Erez Shmueli Dr.
Dana Pessach, Tamir Tassa, Erez Shmueli
Fairness-Driven Private Collaborative Machine Learning
null
null
null
null
cs.LG cs.CR cs.CY
http://creativecommons.org/licenses/by/4.0/
The performance of machine learning algorithms can be considerably improved when trained over larger datasets. In many domains, such as medicine and finance, larger datasets can be obtained if several parties, each having access to limited amounts of data, collaborate and share their data. However, such data sharing ...
[ { "created": "Wed, 29 Sep 2021 12:22:00 GMT", "version": "v1" } ]
2021-09-30
[ [ "Pessach", "Dana", "" ], [ "Tassa", "Tamir", "" ], [ "Shmueli", "Erez", "" ] ]
The performance of machine learning algorithms can be considerably improved when trained over larger datasets. In many domains, such as medicine and finance, larger datasets can be obtained if several parties, each having access to limited amounts of data, collaborate and share their data. However, such data sharing in...
2407.16539
Yehonatan Zion
Yehonatan Zion, Porat Aharon, Ran Dubin, Amit Dvir, Chen Hajaj
Enhancing Encrypted Internet Traffic Classification Through Advanced Data Augmentation Techniques
null
null
null
null
cs.LG
http://creativecommons.org/licenses/by-nc-nd/4.0/
The increasing popularity of online services has made Internet Traffic Classification a critical field of study. However, the rapid development of internet protocols and encryption limits usable data availability. This paper addresses the challenges of classifying encrypted internet traffic, focusing on the scarcity ...
[ { "created": "Tue, 23 Jul 2024 14:49:17 GMT", "version": "v1" } ]
2024-07-24
[ [ "Zion", "Yehonatan", "" ], [ "Aharon", "Porat", "" ], [ "Dubin", "Ran", "" ], [ "Dvir", "Amit", "" ], [ "Hajaj", "Chen", "" ] ]
The increasing popularity of online services has made Internet Traffic Classification a critical field of study. However, the rapid development of internet protocols and encryption limits usable data availability. This paper addresses the challenges of classifying encrypted internet traffic, focusing on the scarcity of...
2310.14605
Fei Zhao
Fei Zhao, Chunhui Li, Zhen Wu, Yawen Ouyang, Jianbing Zhang, Xinyu Dai
M2DF: Multi-grained Multi-curriculum Denoising Framework for Multimodal Aspect-based Sentiment Analysis
Accepted by EMNLP 2023
null
null
null
cs.CL cs.MM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Multimodal Aspect-based Sentiment Analysis (MABSA) is a fine-grained Sentiment Analysis task, which has attracted growing research interests recently. Existing work mainly utilizes image information to improve the performance of MABSA task. However, most of the studies overestimate the importance of images since ther...
[ { "created": "Mon, 23 Oct 2023 06:22:39 GMT", "version": "v1" } ]
2023-10-24
[ [ "Zhao", "Fei", "" ], [ "Li", "Chunhui", "" ], [ "Wu", "Zhen", "" ], [ "Ouyang", "Yawen", "" ], [ "Zhang", "Jianbing", "" ], [ "Dai", "Xinyu", "" ] ]
Multimodal Aspect-based Sentiment Analysis (MABSA) is a fine-grained Sentiment Analysis task, which has attracted growing research interests recently. Existing work mainly utilizes image information to improve the performance of MABSA task. However, most of the studies overestimate the importance of images since there ...
2110.04616
Rogelio Andrade Mancisidor
Rogelio A. Mancisidor, Michael Kampffmeyer, Kjersti Aas, Robert Jenssen
Discriminative Multimodal Learning via Conditional Priors in Generative Models
null
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Deep generative models with latent variables have been used lately to learn joint representations and generative processes from multi-modal data. These two learning mechanisms can, however, conflict with each other and representations can fail to embed information on the data modalities. This research studies the rea...
[ { "created": "Sat, 9 Oct 2021 17:22:24 GMT", "version": "v1" }, { "created": "Tue, 26 Jul 2022 13:07:34 GMT", "version": "v2" }, { "created": "Sat, 21 Jan 2023 21:49:58 GMT", "version": "v3" } ]
2023-01-24
[ [ "Mancisidor", "Rogelio A.", "" ], [ "Kampffmeyer", "Michael", "" ], [ "Aas", "Kjersti", "" ], [ "Jenssen", "Robert", "" ] ]
Deep generative models with latent variables have been used lately to learn joint representations and generative processes from multi-modal data. These two learning mechanisms can, however, conflict with each other and representations can fail to embed information on the data modalities. This research studies the reali...
1912.07712
Marco Ciccone
Andrea Celli, Marco Ciccone, Raffaele Bongo, Nicola Gatti
Coordination in Adversarial Sequential Team Games via Multi-Agent Deep Reinforcement Learning
Preliminary version
null
null
null
cs.AI cs.NE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Many real-world applications involve teams of agents that have to coordinate their actions to reach a common goal against potential adversaries. This paper focuses on zero-sum games where a team of players faces an opponent, as is the case, for example, in Bridge, collusion in poker, and collusion in bidding. The pos...
[ { "created": "Mon, 16 Dec 2019 21:30:04 GMT", "version": "v1" } ]
2019-12-18
[ [ "Celli", "Andrea", "" ], [ "Ciccone", "Marco", "" ], [ "Bongo", "Raffaele", "" ], [ "Gatti", "Nicola", "" ] ]
Many real-world applications involve teams of agents that have to coordinate their actions to reach a common goal against potential adversaries. This paper focuses on zero-sum games where a team of players faces an opponent, as is the case, for example, in Bridge, collusion in poker, and collusion in bidding. The possi...
1306.2550
Georg B\"ocherer
Georg B\"ocherer and Rana Ali Amjad
Fixed-to-Variable Length Resolution Coding for Target Distributions
Essentially the ITW 2013 final version. Compared to v1, minor typos were corrected and Fig. 1 with an example variable length encoder was added
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The number of random bits required to approximate a target distribution in terms of un-normalized informational divergence is considered. It is shown that for a variable-to-variable length encoder, this number is lower bounded by the entropy of the target distribution. A fixed-to-variable length encoder is constructe...
[ { "created": "Tue, 11 Jun 2013 15:18:13 GMT", "version": "v1" }, { "created": "Thu, 1 Aug 2013 14:01:29 GMT", "version": "v2" } ]
2013-08-02
[ [ "Böcherer", "Georg", "" ], [ "Amjad", "Rana Ali", "" ] ]
The number of random bits required to approximate a target distribution in terms of un-normalized informational divergence is considered. It is shown that for a variable-to-variable length encoder, this number is lower bounded by the entropy of the target distribution. A fixed-to-variable length encoder is constructed ...
2301.01100
Zhisheng Zhong
Zhisheng Zhong, Jiequan Cui, Yibo Yang, Xiaoyang Wu, Xiaojuan Qi, Xiangyu Zhang, Jiaya Jia
Understanding Imbalanced Semantic Segmentation Through Neural Collapse
Technical Report
null
null
null
cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A recent study has shown a phenomenon called neural collapse in that the within-class means of features and the classifier weight vectors converge to the vertices of a simplex equiangular tight frame at the terminal phase of training for classification. In this paper, we explore the corresponding structures of the la...
[ { "created": "Tue, 3 Jan 2023 13:51:51 GMT", "version": "v1" } ]
2023-01-04
[ [ "Zhong", "Zhisheng", "" ], [ "Cui", "Jiequan", "" ], [ "Yang", "Yibo", "" ], [ "Wu", "Xiaoyang", "" ], [ "Qi", "Xiaojuan", "" ], [ "Zhang", "Xiangyu", "" ], [ "Jia", "Jiaya", "" ] ]
A recent study has shown a phenomenon called neural collapse in that the within-class means of features and the classifier weight vectors converge to the vertices of a simplex equiangular tight frame at the terminal phase of training for classification. In this paper, we explore the corresponding structures of the last...
2403.17327
Jeong-Yoon Kim
Jeong-Yoon Kim, Seung-Ho Lee
Accuracy enhancement method for speech emotion recognition from spectrogram using temporal frequency correlation and positional information learning through knowledge transfer
null
null
null
null
cs.SD cs.CV eess.AS
http://creativecommons.org/licenses/by/4.0/
In this paper, we propose a method to improve the accuracy of speech emotion recognition (SER) by using vision transformer (ViT) to attend to the correlation of frequency (y-axis) with time (x-axis) in spectrogram and transferring positional information between ViT through knowledge transfer. The proposed method has ...
[ { "created": "Tue, 26 Mar 2024 02:21:36 GMT", "version": "v1" } ]
2024-03-27
[ [ "Kim", "Jeong-Yoon", "" ], [ "Lee", "Seung-Ho", "" ] ]
In this paper, we propose a method to improve the accuracy of speech emotion recognition (SER) by using vision transformer (ViT) to attend to the correlation of frequency (y-axis) with time (x-axis) in spectrogram and transferring positional information between ViT through knowledge transfer. The proposed method has th...
2406.04485
Dongfu Jiang
Dongfu Jiang, Max Ku, Tianle Li, Yuansheng Ni, Shizhuo Sun, Rongqi Fan, Wenhu Chen
GenAI Arena: An Open Evaluation Platform for Generative Models
9 pages,7 figures
null
null
null
cs.AI cs.CV
http://creativecommons.org/licenses/by/4.0/
Generative AI has made remarkable strides to revolutionize fields such as image and video generation. These advancements are driven by innovative algorithms, architecture, and data. However, the rapid proliferation of generative models has highlighted a critical gap: the absence of trustworthy evaluation metrics. Cur...
[ { "created": "Thu, 6 Jun 2024 20:15:42 GMT", "version": "v1" }, { "created": "Mon, 5 Aug 2024 07:18:25 GMT", "version": "v2" }, { "created": "Tue, 6 Aug 2024 16:35:50 GMT", "version": "v3" } ]
2024-08-07
[ [ "Jiang", "Dongfu", "" ], [ "Ku", "Max", "" ], [ "Li", "Tianle", "" ], [ "Ni", "Yuansheng", "" ], [ "Sun", "Shizhuo", "" ], [ "Fan", "Rongqi", "" ], [ "Chen", "Wenhu", "" ] ]
Generative AI has made remarkable strides to revolutionize fields such as image and video generation. These advancements are driven by innovative algorithms, architecture, and data. However, the rapid proliferation of generative models has highlighted a critical gap: the absence of trustworthy evaluation metrics. Curre...
2106.15433
Bla\v{z} \v{S}krlj
Timen Stepi\v{s}nik Perdih, Nada Lavra\v{c}, Bla\v{z} \v{S}krlj
Semantic Reasoning from Model-Agnostic Explanations
null
null
10.1109/SAMI50585.2021.9378668
null
cs.AI
http://creativecommons.org/publicdomain/zero/1.0/
With the wide adoption of black-box models, instance-based \emph{post hoc} explanation tools, such as LIME and SHAP became increasingly popular. These tools produce explanations, pinpointing contributions of key features associated with a given prediction. However, the obtained explanations remain at the raw feature ...
[ { "created": "Tue, 29 Jun 2021 14:03:47 GMT", "version": "v1" } ]
2021-06-30
[ [ "Perdih", "Timen Stepišnik", "" ], [ "Lavrač", "Nada", "" ], [ "Škrlj", "Blaž", "" ] ]
With the wide adoption of black-box models, instance-based \emph{post hoc} explanation tools, such as LIME and SHAP became increasingly popular. These tools produce explanations, pinpointing contributions of key features associated with a given prediction. However, the obtained explanations remain at the raw feature le...
1503.08345
Pravendra Singh
Pravendra Singh
Implementing an intelligent version of the classical sliding-puzzle game for unix terminals using Golang's concurrency primitives
8 pages
null
null
null
cs.AI
http://creativecommons.org/licenses/by/4.0/
An intelligent version of the sliding-puzzle game is developed using the new Go programming language, which uses a concurrent version of the A* Informed Search Algorithm to power solver-bot that runs in the background. The game runs in computer system's terminals. Mainly, it was developed for UNIX-type systems but it...
[ { "created": "Sat, 28 Mar 2015 20:35:02 GMT", "version": "v1" }, { "created": "Sat, 22 Aug 2015 17:07:32 GMT", "version": "v2" } ]
2015-08-25
[ [ "Singh", "Pravendra", "" ] ]
An intelligent version of the sliding-puzzle game is developed using the new Go programming language, which uses a concurrent version of the A* Informed Search Algorithm to power solver-bot that runs in the background. The game runs in computer system's terminals. Mainly, it was developed for UNIX-type systems but it w...
2201.09656
Alessandro Benfenati
Alessandro Benfenati and Alessio Marta
A singular Riemannian geometry approach to Deep Neural Networks I. Theoretical foundations
null
null
null
null
cs.LG cs.NE math.MG
http://creativecommons.org/licenses/by/4.0/
Deep Neural Networks are widely used for solving complex problems in several scientific areas, such as speech recognition, machine translation, image analysis. The strategies employed to investigate their theoretical properties mainly rely on Euclidean geometry, but in the last years new approaches based on Riemannia...
[ { "created": "Fri, 17 Dec 2021 11:43:30 GMT", "version": "v1" }, { "created": "Fri, 23 Sep 2022 10:19:09 GMT", "version": "v2" } ]
2022-09-26
[ [ "Benfenati", "Alessandro", "" ], [ "Marta", "Alessio", "" ] ]
Deep Neural Networks are widely used for solving complex problems in several scientific areas, such as speech recognition, machine translation, image analysis. The strategies employed to investigate their theoretical properties mainly rely on Euclidean geometry, but in the last years new approaches based on Riemannian ...
2310.01164
Lei Li
Lei Li
Segment Any Building
CGI 2023
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The task of identifying and segmenting buildings within remote sensing imagery has perennially stood at the forefront of scholarly investigations. This manuscript accentuates the potency of harnessing diversified datasets in tandem with cutting-edge representation learning paradigms for building segmentation in such ...
[ { "created": "Mon, 2 Oct 2023 12:49:20 GMT", "version": "v1" }, { "created": "Mon, 16 Oct 2023 17:53:55 GMT", "version": "v2" }, { "created": "Wed, 25 Oct 2023 11:28:35 GMT", "version": "v3" }, { "created": "Thu, 26 Oct 2023 17:08:34 GMT", "version": "v4" } ]
2023-10-27
[ [ "Li", "Lei", "" ] ]
The task of identifying and segmenting buildings within remote sensing imagery has perennially stood at the forefront of scholarly investigations. This manuscript accentuates the potency of harnessing diversified datasets in tandem with cutting-edge representation learning paradigms for building segmentation in such im...
2005.04308
Jian Xu
Jian Xu, Sunkyu Kim, Min Song, Minbyul Jeong, Donghyeon Kim, Jaewoo Kang, Justin F. Rousseau, Xin Li, Weijia Xu, Vetle I. Torvik, Yi Bu, Chongyan Chen, Islam Akef Ebeid, Daifeng Li, Ying Ding
Building a PubMed knowledge graph
19 pages, 5 figures, 14 tables
null
null
null
cs.DL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
PubMed is an essential resource for the medical domain, but useful concepts are either difficult to extract or are ambiguated, which has significantly hindered knowledge discovery. To address this issue, we constructed a PubMed knowledge graph (PKG) by extracting bio-entities from 29 million PubMed abstracts, disambi...
[ { "created": "Fri, 8 May 2020 22:36:49 GMT", "version": "v1" }, { "created": "Fri, 15 May 2020 06:50:39 GMT", "version": "v2" } ]
2020-05-18
[ [ "Xu", "Jian", "" ], [ "Kim", "Sunkyu", "" ], [ "Song", "Min", "" ], [ "Jeong", "Minbyul", "" ], [ "Kim", "Donghyeon", "" ], [ "Kang", "Jaewoo", "" ], [ "Rousseau", "Justin F.", "" ], [ "Li", "Xi...
PubMed is an essential resource for the medical domain, but useful concepts are either difficult to extract or are ambiguated, which has significantly hindered knowledge discovery. To address this issue, we constructed a PubMed knowledge graph (PKG) by extracting bio-entities from 29 million PubMed abstracts, disambigu...
1411.4568
Yannick Verdie
Yannick Verdie, Kwang Moo Yi, Pascal Fua, Vincent Lepetit
TILDE: A Temporally Invariant Learned DEtector
null
null
10.1109/CVPR.2015.7299165
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We introduce a learning-based approach to detect repeatable keypoints under drastic imaging changes of weather and lighting conditions to which state-of-the-art keypoint detectors are surprisingly sensitive. We first identify good keypoint candidates in multiple training images taken from the same viewpoint. We then ...
[ { "created": "Mon, 17 Nov 2014 17:44:21 GMT", "version": "v1" }, { "created": "Wed, 11 Feb 2015 14:22:39 GMT", "version": "v2" }, { "created": "Thu, 12 Mar 2015 20:07:01 GMT", "version": "v3" } ]
2015-11-16
[ [ "Verdie", "Yannick", "" ], [ "Yi", "Kwang Moo", "" ], [ "Fua", "Pascal", "" ], [ "Lepetit", "Vincent", "" ] ]
We introduce a learning-based approach to detect repeatable keypoints under drastic imaging changes of weather and lighting conditions to which state-of-the-art keypoint detectors are surprisingly sensitive. We first identify good keypoint candidates in multiple training images taken from the same viewpoint. We then tr...
1903.06017
Hancheng Min
Hancheng Min and Enrique Mallada
Dynamics Concentration of Large-Scale Tightly-Connected Networks
null
null
null
null
cs.SY cs.MA
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The ability to achieve coordinated behavior --engineered or emergent-- on networked systems has attracted widespread interest over several fields. This has led to remarkable advances on the development of a theoretical understanding of the conditions under which agents within a network can reach agreement (consensus)...
[ { "created": "Thu, 14 Mar 2019 14:16:37 GMT", "version": "v1" }, { "created": "Fri, 15 Mar 2019 18:07:03 GMT", "version": "v2" }, { "created": "Tue, 2 Apr 2019 12:29:28 GMT", "version": "v3" }, { "created": "Fri, 12 Apr 2019 16:29:14 GMT", "version": "v4" }, { "cr...
2019-09-16
[ [ "Min", "Hancheng", "" ], [ "Mallada", "Enrique", "" ] ]
The ability to achieve coordinated behavior --engineered or emergent-- on networked systems has attracted widespread interest over several fields. This has led to remarkable advances on the development of a theoretical understanding of the conditions under which agents within a network can reach agreement (consensus) o...
1704.06185
Huacheng Yu
Josh Alman, Joshua R. Wang, Huacheng Yu
Cell-Probe Lower Bounds from Online Communication Complexity
null
null
null
null
cs.DS cs.CC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this work, we introduce an online model for communication complexity. Analogous to how online algorithms receive their input piece-by-piece, our model presents one of the players, Bob, his input piece-by-piece, and has the players Alice and Bob cooperate to compute a result each time before the next piece is revea...
[ { "created": "Thu, 20 Apr 2017 15:27:26 GMT", "version": "v1" }, { "created": "Wed, 15 Nov 2017 18:05:06 GMT", "version": "v2" } ]
2017-11-16
[ [ "Alman", "Josh", "" ], [ "Wang", "Joshua R.", "" ], [ "Yu", "Huacheng", "" ] ]
In this work, we introduce an online model for communication complexity. Analogous to how online algorithms receive their input piece-by-piece, our model presents one of the players, Bob, his input piece-by-piece, and has the players Alice and Bob cooperate to compute a result each time before the next piece is reveale...
2305.10960
Eric Rosen
Eric Rosen, Devesh K. Jha
A Virtual Reality Teleoperation Interface for Industrial Robot Manipulators
7 pages, 6 figures
null
null
null
cs.RO cs.AI
http://creativecommons.org/licenses/by/4.0/
We address the problem of teleoperating an industrial robot manipulator via a commercially available Virtual Reality (VR) interface. Previous works on VR teleoperation for robot manipulators focus primarily on collaborative or research robot platforms (whose dynamics and constraints differ from industrial robot arms)...
[ { "created": "Thu, 18 May 2023 13:26:23 GMT", "version": "v1" } ]
2023-05-19
[ [ "Rosen", "Eric", "" ], [ "Jha", "Devesh K.", "" ] ]
We address the problem of teleoperating an industrial robot manipulator via a commercially available Virtual Reality (VR) interface. Previous works on VR teleoperation for robot manipulators focus primarily on collaborative or research robot platforms (whose dynamics and constraints differ from industrial robot arms), ...
1412.7059
Huibo Bi
Huibo Bi and Erol Gelenbe
Cloud Enabled Emergency Navigation Using Faster-than-real-time Simulation
Submitted to PerNEM'15 for review
null
null
null
cs.OH
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
State-of-the-art emergency navigation approaches are designed to evacuate civilians during a disaster based on real-time decisions using a pre-defined algorithm and live sensory data. Hence, casualties caused by the poor decisions and guidance are only apparent at the end of the evacuation process and cannot then be ...
[ { "created": "Mon, 22 Dec 2014 17:08:59 GMT", "version": "v1" }, { "created": "Sat, 3 Jan 2015 15:41:35 GMT", "version": "v2" } ]
2015-01-06
[ [ "Bi", "Huibo", "" ], [ "Gelenbe", "Erol", "" ] ]
State-of-the-art emergency navigation approaches are designed to evacuate civilians during a disaster based on real-time decisions using a pre-defined algorithm and live sensory data. Hence, casualties caused by the poor decisions and guidance are only apparent at the end of the evacuation process and cannot then be re...
1910.05645
Doron Mu
Shiri Chechik and Doron Mukhtar
Reachability and Shortest Paths in the Broadcast CONGEST Model
null
null
null
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper we study the time complexity of the single-source reachability problem and the single-source shortest path problem for directed unweighted graphs in the Broadcast CONGEST model. We focus on the case where the diameter $D$ of the underlying network is constant. We show that for the case where $D = 1$ the...
[ { "created": "Sat, 12 Oct 2019 21:11:52 GMT", "version": "v1" } ]
2019-10-15
[ [ "Chechik", "Shiri", "" ], [ "Mukhtar", "Doron", "" ] ]
In this paper we study the time complexity of the single-source reachability problem and the single-source shortest path problem for directed unweighted graphs in the Broadcast CONGEST model. We focus on the case where the diameter $D$ of the underlying network is constant. We show that for the case where $D = 1$ there...
2004.06496
Michael Everett
Michael Everett, Bjorn Lutjens, Jonathan P. How
Certifiable Robustness to Adversarial State Uncertainty in Deep Reinforcement Learning
arXiv admin note: text overlap with arXiv:1910.12908
null
10.1109/TNNLS.2021.3056046
null
cs.LG cs.CR stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Deep Neural Network-based systems are now the state-of-the-art in many robotics tasks, but their application in safety-critical domains remains dangerous without formal guarantees on network robustness. Small perturbations to sensor inputs (from noise or adversarial examples) are often enough to change network-based ...
[ { "created": "Sat, 11 Apr 2020 21:36:13 GMT", "version": "v1" }, { "created": "Mon, 22 Jun 2020 22:02:21 GMT", "version": "v2" }, { "created": "Fri, 21 Aug 2020 16:57:54 GMT", "version": "v3" }, { "created": "Mon, 25 Jan 2021 17:15:40 GMT", "version": "v4" }, { "c...
2022-02-03
[ [ "Everett", "Michael", "" ], [ "Lutjens", "Bjorn", "" ], [ "How", "Jonathan P.", "" ] ]
Deep Neural Network-based systems are now the state-of-the-art in many robotics tasks, but their application in safety-critical domains remains dangerous without formal guarantees on network robustness. Small perturbations to sensor inputs (from noise or adversarial examples) are often enough to change network-based de...
2108.12313
Wei Xiang
Fanxin Xu, Xiangkui Li, Hang Yang, Yali Wang, Wei Xiang
TE-YOLOF: Tiny and efficient YOLOF for blood cell detection
null
null
null
null
cs.CV cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Blood cell detection in microscopic images is an essential branch of medical image processing research. Since disease detection based on manual checking of blood cells is time-consuming and full of errors, testing of blood cells using object detectors with Deep Convolutional Neural Network can be regarded as a feasib...
[ { "created": "Fri, 27 Aug 2021 14:45:27 GMT", "version": "v1" } ]
2021-08-30
[ [ "Xu", "Fanxin", "" ], [ "Li", "Xiangkui", "" ], [ "Yang", "Hang", "" ], [ "Wang", "Yali", "" ], [ "Xiang", "Wei", "" ] ]
Blood cell detection in microscopic images is an essential branch of medical image processing research. Since disease detection based on manual checking of blood cells is time-consuming and full of errors, testing of blood cells using object detectors with Deep Convolutional Neural Network can be regarded as a feasible...
1907.02140
Tadahiro Taniguchi
Akira Kinose and Tadahiro Taniguchi
Integration of Imitation Learning using GAIL and Reinforcement Learning using Task-achievement Rewards via Probabilistic Graphical Model
Submitted to Advanced Robotics
Advanced Robotics, 2020, 34:16, 1055-1067
10.1080/01691864.2020.1778521
null
cs.LG cs.AI stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Integration of reinforcement learning and imitation learning is an important problem that has been studied for a long time in the field of intelligent robotics. Reinforcement learning optimizes policies to maximize the cumulative reward, whereas imitation learning attempts to extract general knowledge about the traje...
[ { "created": "Wed, 3 Jul 2019 21:38:48 GMT", "version": "v1" }, { "created": "Wed, 16 Oct 2019 08:24:58 GMT", "version": "v2" } ]
2023-01-18
[ [ "Kinose", "Akira", "" ], [ "Taniguchi", "Tadahiro", "" ] ]
Integration of reinforcement learning and imitation learning is an important problem that has been studied for a long time in the field of intelligent robotics. Reinforcement learning optimizes policies to maximize the cumulative reward, whereas imitation learning attempts to extract general knowledge about the traject...
2203.13965
Filip Ilievski
Jiang Wang, Filip Ilievski, Pedro Szekely, Ke-Thia Yao
Augmenting Knowledge Graphs for Better Link Prediction
null
null
null
null
cs.AI
http://creativecommons.org/licenses/by-nc-sa/4.0/
Embedding methods have demonstrated robust performance on the task of link prediction in knowledge graphs, by mostly encoding entity relationships. Recent methods propose to enhance the loss function with a literal-aware term. In this paper, we propose KGA: a knowledge graph augmentation method that incorporates lite...
[ { "created": "Sat, 26 Mar 2022 02:06:17 GMT", "version": "v1" }, { "created": "Mon, 25 Apr 2022 03:43:30 GMT", "version": "v2" } ]
2022-04-26
[ [ "Wang", "Jiang", "" ], [ "Ilievski", "Filip", "" ], [ "Szekely", "Pedro", "" ], [ "Yao", "Ke-Thia", "" ] ]
Embedding methods have demonstrated robust performance on the task of link prediction in knowledge graphs, by mostly encoding entity relationships. Recent methods propose to enhance the loss function with a literal-aware term. In this paper, we propose KGA: a knowledge graph augmentation method that incorporates litera...
2308.00519
Andrea Avogaro
Andrea Avogaro, Federico Cunico, Bodo Rosenhahn and Francesco Setti
Markerless human pose estimation for biomedical applications: a survey
null
Frontiers in Computer Science 5, (2023): 1153160
10.3389/fcomp.2023.1153160
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Markerless Human Pose Estimation (HPE) proved its potential to support decision making and assessment in many fields of application. HPE is often preferred to traditional marker-based Motion Capture systems due to the ease of setup, portability, and affordable cost of the technology. However, the exploitation of HPE ...
[ { "created": "Tue, 1 Aug 2023 12:59:07 GMT", "version": "v1" } ]
2023-08-02
[ [ "Avogaro", "Andrea", "" ], [ "Cunico", "Federico", "" ], [ "Rosenhahn", "Bodo", "" ], [ "Setti", "Francesco", "" ] ]
Markerless Human Pose Estimation (HPE) proved its potential to support decision making and assessment in many fields of application. HPE is often preferred to traditional marker-based Motion Capture systems due to the ease of setup, portability, and affordable cost of the technology. However, the exploitation of HPE in...
1809.01633
Jan Siebert
Nina Hristozova, Piotr Ozimek, and Jan Paul Siebert
Efficient Egocentric Visual Perception Combining Eye-tracking, a Software Retina and Deep Learning
Accepted for: EPIC Workshop at the European Conference on Computer Vision, ECCV2018
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present ongoing work to harness biological approaches to achieving highly efficient egocentric perception by combining the space-variant imaging architecture of the mammalian retina with Deep Learning methods. By pre-processing images collected by means of eye-tracking glasses to control the fixation locations of ...
[ { "created": "Wed, 5 Sep 2018 17:19:07 GMT", "version": "v1" } ]
2018-09-06
[ [ "Hristozova", "Nina", "" ], [ "Ozimek", "Piotr", "" ], [ "Siebert", "Jan Paul", "" ] ]
We present ongoing work to harness biological approaches to achieving highly efficient egocentric perception by combining the space-variant imaging architecture of the mammalian retina with Deep Learning methods. By pre-processing images collected by means of eye-tracking glasses to control the fixation locations of a ...
1906.06498
Alberto Bemporad Prof.
Alberto Bemporad
Global optimization via inverse distance weighting and radial basis functions
null
null
null
null
cs.LG math.OC stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Global optimization problems whose objective function is expensive to evaluate can be solved effectively by recursively fitting a surrogate function to function samples and minimizing an acquisition function to generate new samples. The acquisition step trades off between seeking for a new optimization vector where t...
[ { "created": "Sat, 15 Jun 2019 08:45:47 GMT", "version": "v1" }, { "created": "Thu, 9 Jan 2020 07:32:43 GMT", "version": "v2" } ]
2020-01-10
[ [ "Bemporad", "Alberto", "" ] ]
Global optimization problems whose objective function is expensive to evaluate can be solved effectively by recursively fitting a surrogate function to function samples and minimizing an acquisition function to generate new samples. The acquisition step trades off between seeking for a new optimization vector where the...
1208.3845
Jing-Yan Wang
Jing-Yan Wang and Mustafa AbdulJabbar
Adaptive Graph via Multiple Kernel Learning for Nonnegative Matrix Factorization
This paper has been withdrawn by the author due to the terrible writing
null
null
null
cs.LG cs.CV stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Nonnegative Matrix Factorization (NMF) has been continuously evolving in several areas like pattern recognition and information retrieval methods. It factorizes a matrix into a product of 2 low-rank non-negative matrices that will define parts-based, and linear representation of nonnegative data. Recently, Graph regu...
[ { "created": "Sun, 19 Aug 2012 15:21:09 GMT", "version": "v1" }, { "created": "Sun, 26 Aug 2012 07:24:22 GMT", "version": "v2" }, { "created": "Wed, 3 Apr 2013 14:21:50 GMT", "version": "v3" } ]
2013-04-04
[ [ "Wang", "Jing-Yan", "" ], [ "AbdulJabbar", "Mustafa", "" ] ]
Nonnegative Matrix Factorization (NMF) has been continuously evolving in several areas like pattern recognition and information retrieval methods. It factorizes a matrix into a product of 2 low-rank non-negative matrices that will define parts-based, and linear representation of nonnegative data. Recently, Graph regula...
1806.06977
Akhilesh Gotmare
Akhilesh Gotmare, Nitish Shirish Keskar, Caiming Xiong, Richard Socher
Using Mode Connectivity for Loss Landscape Analysis
Accepted as a workshop paper at ICML's Workshop on Modern Trends in Nonconvex Optimization for Machine Learning, 2018
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Mode connectivity is a recently introduced frame- work that empirically establishes the connected- ness of minima by finding a high accuracy curve between two independently trained models. To investigate the limits of this setup, we examine the efficacy of this technique in extreme cases where the input models are tr...
[ { "created": "Mon, 18 Jun 2018 23:00:26 GMT", "version": "v1" } ]
2018-06-20
[ [ "Gotmare", "Akhilesh", "" ], [ "Keskar", "Nitish Shirish", "" ], [ "Xiong", "Caiming", "" ], [ "Socher", "Richard", "" ] ]
Mode connectivity is a recently introduced frame- work that empirically establishes the connected- ness of minima by finding a high accuracy curve between two independently trained models. To investigate the limits of this setup, we examine the efficacy of this technique in extreme cases where the input models are trai...
1603.04574
Tamoor-Ul-Hassan Syed
Syed Tamoor-ul-Hassan, Mehdi Bennis, Pedro H. J. Nardelli, Matti Latva-Aho
Caching in Wireless Small Cell Networks: A Storage-Bandwidth Tradeoff
accepted for publication, IEEE Comm Letters 2016
null
10.1109/LCOMM.2016.2543698
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Caching contents at the network edge is an efficient mean for offloading traffic, reducing latency and improving users' quality-of-experience. In this letter, we focus on aspects of storage-bandwidth tradeoffs in which small cell base stations are distributed according to a homogeneous Poisson point process and cache...
[ { "created": "Tue, 15 Mar 2016 07:19:06 GMT", "version": "v1" }, { "created": "Wed, 16 Mar 2016 09:07:27 GMT", "version": "v2" }, { "created": "Thu, 17 Mar 2016 13:11:18 GMT", "version": "v3" } ]
2016-11-18
[ [ "Tamoor-ul-Hassan", "Syed", "" ], [ "Bennis", "Mehdi", "" ], [ "Nardelli", "Pedro H. J.", "" ], [ "Latva-Aho", "Matti", "" ] ]
Caching contents at the network edge is an efficient mean for offloading traffic, reducing latency and improving users' quality-of-experience. In this letter, we focus on aspects of storage-bandwidth tradeoffs in which small cell base stations are distributed according to a homogeneous Poisson point process and cache c...
2009.04091
Binh Nguyen Xuan
Binh X. Nguyen, Binh D. Nguyen, Gustavo Carneiro, Erman Tjiputra, Quang D. Tran, Thanh-Toan Do
Deep Metric Learning Meets Deep Clustering: An Novel Unsupervised Approach for Feature Embedding
Accepted in BMVC 2020
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Unsupervised Deep Distance Metric Learning (UDML) aims to learn sample similarities in the embedding space from an unlabeled dataset. Traditional UDML methods usually use the triplet loss or pairwise loss which requires the mining of positive and negative samples w.r.t. anchor data points. This is, however, challengi...
[ { "created": "Wed, 9 Sep 2020 04:02:04 GMT", "version": "v1" } ]
2020-09-10
[ [ "Nguyen", "Binh X.", "" ], [ "Nguyen", "Binh D.", "" ], [ "Carneiro", "Gustavo", "" ], [ "Tjiputra", "Erman", "" ], [ "Tran", "Quang D.", "" ], [ "Do", "Thanh-Toan", "" ] ]
Unsupervised Deep Distance Metric Learning (UDML) aims to learn sample similarities in the embedding space from an unlabeled dataset. Traditional UDML methods usually use the triplet loss or pairwise loss which requires the mining of positive and negative samples w.r.t. anchor data points. This is, however, challenging...
2404.08163
Adrian Lehmann
Bhakti Shah, William Spencer, Laura Zielinski, Ben Caldwell, Adrian Lehmann, Robert Rand
ViCAR: Visualizing Categories with Automated Rewriting in Coq
13 pages, 10 figures
null
null
null
cs.PL math.CT
http://creativecommons.org/licenses/by/4.0/
We present ViCAR, a library for working with monoidal categories in the Coq proof assistant. ViCAR provides definitions for categorical structures that users can instantiate with their own verification projects. Upon verifying relevant coherence conditions, ViCAR gives a set of lemmas and tactics for manipulating cat...
[ { "created": "Thu, 11 Apr 2024 23:59:14 GMT", "version": "v1" } ]
2024-04-15
[ [ "Shah", "Bhakti", "" ], [ "Spencer", "William", "" ], [ "Zielinski", "Laura", "" ], [ "Caldwell", "Ben", "" ], [ "Lehmann", "Adrian", "" ], [ "Rand", "Robert", "" ] ]
We present ViCAR, a library for working with monoidal categories in the Coq proof assistant. ViCAR provides definitions for categorical structures that users can instantiate with their own verification projects. Upon verifying relevant coherence conditions, ViCAR gives a set of lemmas and tactics for manipulating categ...
2308.03172
Shuang Ao
Shuang Ao, Stefan Rueger, Advaith Siddharthan
Two Sides of Miscalibration: Identifying Over and Under-Confidence Prediction for Network Calibration
9 pages
2023
null
null
cs.LG cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Proper confidence calibration of deep neural networks is essential for reliable predictions in safety-critical tasks. Miscalibration can lead to model over-confidence and/or under-confidence; i.e., the model's confidence in its prediction can be greater or less than the model's accuracy. Recent studies have highlight...
[ { "created": "Sun, 6 Aug 2023 17:59:14 GMT", "version": "v1" } ]
2023-08-08
[ [ "Ao", "Shuang", "" ], [ "Rueger", "Stefan", "" ], [ "Siddharthan", "Advaith", "" ] ]
Proper confidence calibration of deep neural networks is essential for reliable predictions in safety-critical tasks. Miscalibration can lead to model over-confidence and/or under-confidence; i.e., the model's confidence in its prediction can be greater or less than the model's accuracy. Recent studies have highlighted...
2405.20824
Stephen Pasteris
Stephen Pasteris, Chris Hicks, Vasilios Mavroudis, Mark Herbster
Online Convex Optimisation: The Optimal Switching Regret for all Segmentations Simultaneously
null
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We consider the classic problem of online convex optimisation. Whereas the notion of static regret is relevant for stationary problems, the notion of switching regret is more appropriate for non-stationary problems. A switching regret is defined relative to any segmentation of the trial sequence, and is equal to the ...
[ { "created": "Fri, 31 May 2024 14:16:52 GMT", "version": "v1" } ]
2024-06-03
[ [ "Pasteris", "Stephen", "" ], [ "Hicks", "Chris", "" ], [ "Mavroudis", "Vasilios", "" ], [ "Herbster", "Mark", "" ] ]
We consider the classic problem of online convex optimisation. Whereas the notion of static regret is relevant for stationary problems, the notion of switching regret is more appropriate for non-stationary problems. A switching regret is defined relative to any segmentation of the trial sequence, and is equal to the su...
1403.2628
Ozan Kahramanogullari
Ozan Kahramanogullari (The Microsoft Research - University of Trento Centre for Computational and Syste)
Interaction and Depth against Nondeterminism in Proof Search
null
Logical Methods in Computer Science, Volume 10, Issue 2 (May 30, 2014) lmcs:1089
10.2168/LMCS-10(2:5)2014
null
cs.LO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Deep inference is a proof theoretic methodology that generalizes the standard notion of inference of the sequent calculus, whereby inference rules become applicable at any depth inside logical expressions. Deep inference provides more freedom in the design of deductive systems for different logics and a rich combinat...
[ { "created": "Tue, 11 Mar 2014 16:22:34 GMT", "version": "v1" }, { "created": "Wed, 28 May 2014 16:36:47 GMT", "version": "v2" } ]
2015-07-01
[ [ "Kahramanogullari", "Ozan", "", "The Microsoft Research - University of Trento\n Centre for Computational and Syste" ] ]
Deep inference is a proof theoretic methodology that generalizes the standard notion of inference of the sequent calculus, whereby inference rules become applicable at any depth inside logical expressions. Deep inference provides more freedom in the design of deductive systems for different logics and a rich combinator...
2201.06056
Mengyue Yang
Mengyue Yang, Guohao Cai, Furui Liu, Zhenhua Dong, Xiuqiang He, Jianye Hao, Jun Wang, Xu Chen
Debiased Recommendation with User Feature Balancing
null
null
null
null
cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Debiased recommendation has recently attracted increasing attention from both industry and academic communities. Traditional models mostly rely on the inverse propensity score (IPS), which can be hard to estimate and may suffer from the high variance issue. To alleviate these problems, in this paper, we propose a nov...
[ { "created": "Sun, 16 Jan 2022 14:26:28 GMT", "version": "v1" } ]
2022-01-19
[ [ "Yang", "Mengyue", "" ], [ "Cai", "Guohao", "" ], [ "Liu", "Furui", "" ], [ "Dong", "Zhenhua", "" ], [ "He", "Xiuqiang", "" ], [ "Hao", "Jianye", "" ], [ "Wang", "Jun", "" ], [ "Chen", "Xu", ...
Debiased recommendation has recently attracted increasing attention from both industry and academic communities. Traditional models mostly rely on the inverse propensity score (IPS), which can be hard to estimate and may suffer from the high variance issue. To alleviate these problems, in this paper, we propose a novel...
1803.10623
Hazer Inaltekin
Y. Sarikaya, H. Inaltekin, T. Alpcan and J. S. Evans
Stability and Dynamic Control of Underlay Mobile Edge Networks
arXiv admin note: substantial text overlap with arXiv:1606.00534
null
null
null
cs.IT cs.NI math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper studies the stability and dynamic control of underlay mobile edge networks. First, the stability region for a multiuser edge network is obtained under the assumption of full channel state information. This result provides a benchmark figure for comparing performance of the proposed algorithms. Second, a ce...
[ { "created": "Mon, 26 Mar 2018 00:33:00 GMT", "version": "v1" } ]
2018-03-29
[ [ "Sarikaya", "Y.", "" ], [ "Inaltekin", "H.", "" ], [ "Alpcan", "T.", "" ], [ "Evans", "J. S.", "" ] ]
This paper studies the stability and dynamic control of underlay mobile edge networks. First, the stability region for a multiuser edge network is obtained under the assumption of full channel state information. This result provides a benchmark figure for comparing performance of the proposed algorithms. Second, a cent...
2302.02121
Hanjing Ye
Hanjing Ye, Jieting Zhao, Yaling Pan, Weinan Chen, Li He and Hong Zhang
Robot Person Following Under Partial Occlusion
Accepted by ICRA 2023
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Robot person following (RPF) is a capability that supports many useful human-robot-interaction (HRI) applications. However, existing solutions to person following often assume full observation of the tracked person. As a consequence, they cannot track the person reliably under partial occlusion where the assumption o...
[ { "created": "Sat, 4 Feb 2023 07:34:05 GMT", "version": "v1" }, { "created": "Mon, 27 Feb 2023 08:57:54 GMT", "version": "v2" } ]
2023-02-28
[ [ "Ye", "Hanjing", "" ], [ "Zhao", "Jieting", "" ], [ "Pan", "Yaling", "" ], [ "Chen", "Weinan", "" ], [ "He", "Li", "" ], [ "Zhang", "Hong", "" ] ]
Robot person following (RPF) is a capability that supports many useful human-robot-interaction (HRI) applications. However, existing solutions to person following often assume full observation of the tracked person. As a consequence, they cannot track the person reliably under partial occlusion where the assumption of ...
2107.04231
Vinod K Kurmi
Vinod K Kurmi and Venkatesh K Subramanian and Vinay P. Namboodiri
Exploring Dropout Discriminator for Domain Adaptation
This work is an extension of our BMVC-2019 paper (arXiv:1907.10628)
null
null
null
cs.LG cs.AI cs.CV
http://creativecommons.org/licenses/by-nc-sa/4.0/
Adaptation of a classifier to new domains is one of the challenging problems in machine learning. This has been addressed using many deep and non-deep learning based methods. Among the methodologies used, that of adversarial learning is widely applied to solve many deep learning problems along with domain adaptation....
[ { "created": "Fri, 9 Jul 2021 06:11:34 GMT", "version": "v1" } ]
2021-07-12
[ [ "Kurmi", "Vinod K", "" ], [ "Subramanian", "Venkatesh K", "" ], [ "Namboodiri", "Vinay P.", "" ] ]
Adaptation of a classifier to new domains is one of the challenging problems in machine learning. This has been addressed using many deep and non-deep learning based methods. Among the methodologies used, that of adversarial learning is widely applied to solve many deep learning problems along with domain adaptation. T...
2102.03933
Thomas Hardjono
Thomas Hardjono
Blockchain Gateways, Bridges and Delegated Hash-Locks
8 figures
null
null
null
cs.CR
http://creativecommons.org/licenses/by-nc-nd/4.0/
In the current work we discuss the notion of gateways as a means for interoperability across different blockchain systems. We discuss two key principles for the design of gateway nodes and scalable gateway protocols, namely (i) the opaque ledgers principle as the analogue of the autonomous systems principle in IP dat...
[ { "created": "Sun, 7 Feb 2021 22:14:04 GMT", "version": "v1" } ]
2021-02-09
[ [ "Hardjono", "Thomas", "" ] ]
In the current work we discuss the notion of gateways as a means for interoperability across different blockchain systems. We discuss two key principles for the design of gateway nodes and scalable gateway protocols, namely (i) the opaque ledgers principle as the analogue of the autonomous systems principle in IP datag...
2110.09978
Michael R. Douglas
Michael R. Douglas, Michael Simkin, Omri Ben-Eliezer, Tianqi Wu, Peter Chin, Trung V. Dang and Andrew Wood
What is Learned in Knowledge Graph Embeddings?
16 pages
null
null
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A knowledge graph (KG) is a data structure which represents entities and relations as the vertices and edges of a directed graph with edge types. KGs are an important primitive in modern machine learning and artificial intelligence. Embedding-based models, such as the seminal TransE [Bordes et al., 2013] and the rece...
[ { "created": "Tue, 19 Oct 2021 13:52:11 GMT", "version": "v1" } ]
2021-10-20
[ [ "Douglas", "Michael R.", "" ], [ "Simkin", "Michael", "" ], [ "Ben-Eliezer", "Omri", "" ], [ "Wu", "Tianqi", "" ], [ "Chin", "Peter", "" ], [ "Dang", "Trung V.", "" ], [ "Wood", "Andrew", "" ] ]
A knowledge graph (KG) is a data structure which represents entities and relations as the vertices and edges of a directed graph with edge types. KGs are an important primitive in modern machine learning and artificial intelligence. Embedding-based models, such as the seminal TransE [Bordes et al., 2013] and the recent...
2306.12893
Harry Zhang Mr.
Harry Zhang, Ben Eisner, David Held
FlowBot++: Learning Generalized Articulated Objects Manipulation via Articulation Projection
arXiv admin note: text overlap with arXiv:2205.04382
null
null
null
cs.RO
http://creativecommons.org/licenses/by/4.0/
Understanding and manipulating articulated objects, such as doors and drawers, is crucial for robots operating in human environments. We wish to develop a system that can learn to articulate novel objects with no prior interaction, after training on other articulated objects. Previous approaches for articulated objec...
[ { "created": "Thu, 22 Jun 2023 14:00:48 GMT", "version": "v1" }, { "created": "Mon, 25 Sep 2023 19:30:37 GMT", "version": "v2" }, { "created": "Thu, 15 Feb 2024 20:05:21 GMT", "version": "v3" }, { "created": "Wed, 1 May 2024 23:57:20 GMT", "version": "v4" } ]
2024-05-03
[ [ "Zhang", "Harry", "" ], [ "Eisner", "Ben", "" ], [ "Held", "David", "" ] ]
Understanding and manipulating articulated objects, such as doors and drawers, is crucial for robots operating in human environments. We wish to develop a system that can learn to articulate novel objects with no prior interaction, after training on other articulated objects. Previous approaches for articulated object ...
2211.01987
Daniel Pook-Kolb
Daniel Pook-Kolb, Bruce Allen, Erik Agrell
Exact calculation of quantizer constants for arbitrary lattices
24 pages, 7 figures
null
null
null
cs.IT math.IT math.MG
http://creativecommons.org/licenses/by/4.0/
We present an algorithm for the exact computer-aided construction of the Voronoi cells of lattices with known symmetry group. Our algorithm scales better than linearly with the total number of faces and is applicable to dimensions beyond 12, which previous methods could not achieve. The new algorithm is applied to th...
[ { "created": "Fri, 14 Oct 2022 08:03:16 GMT", "version": "v1" }, { "created": "Sat, 1 Apr 2023 10:41:47 GMT", "version": "v2" }, { "created": "Sun, 18 Feb 2024 15:40:19 GMT", "version": "v3" } ]
2024-02-20
[ [ "Pook-Kolb", "Daniel", "" ], [ "Allen", "Bruce", "" ], [ "Agrell", "Erik", "" ] ]
We present an algorithm for the exact computer-aided construction of the Voronoi cells of lattices with known symmetry group. Our algorithm scales better than linearly with the total number of faces and is applicable to dimensions beyond 12, which previous methods could not achieve. The new algorithm is applied to the ...
2305.03187
Zikang Leng
Zikang Leng, Hyeokhyen Kwon, Thomas Pl\"otz
Generating Virtual On-body Accelerometer Data from Virtual Textual Descriptions for Human Activity Recognition
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The development of robust, generalized models in human activity recognition (HAR) has been hindered by the scarcity of large-scale, labeled data sets. Recent work has shown that virtual IMU data extracted from videos using computer vision techniques can lead to substantial performance improvements when training HAR m...
[ { "created": "Thu, 4 May 2023 22:14:44 GMT", "version": "v1" } ]
2023-05-08
[ [ "Leng", "Zikang", "" ], [ "Kwon", "Hyeokhyen", "" ], [ "Plötz", "Thomas", "" ] ]
The development of robust, generalized models in human activity recognition (HAR) has been hindered by the scarcity of large-scale, labeled data sets. Recent work has shown that virtual IMU data extracted from videos using computer vision techniques can lead to substantial performance improvements when training HAR mod...
1912.10589
Yuan Yao
Yuan Yao, Nico Schertler, Enrique Rosales, Helge Rhodin, Leonid Sigal, Alla Sheffer
Front2Back: Single View 3D Shape Reconstruction via Front to Back Prediction
null
null
null
null
cs.CV cs.GR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Reconstruction of a 3D shape from a single 2D image is a classical computer vision problem, whose difficulty stems from the inherent ambiguity of recovering occluded or only partially observed surfaces. Recent methods address this challenge through the use of largely unstructured neural networks that effectively dist...
[ { "created": "Mon, 23 Dec 2019 02:27:05 GMT", "version": "v1" }, { "created": "Fri, 31 Jan 2020 23:51:41 GMT", "version": "v2" } ]
2020-02-04
[ [ "Yao", "Yuan", "" ], [ "Schertler", "Nico", "" ], [ "Rosales", "Enrique", "" ], [ "Rhodin", "Helge", "" ], [ "Sigal", "Leonid", "" ], [ "Sheffer", "Alla", "" ] ]
Reconstruction of a 3D shape from a single 2D image is a classical computer vision problem, whose difficulty stems from the inherent ambiguity of recovering occluded or only partially observed surfaces. Recent methods address this challenge through the use of largely unstructured neural networks that effectively distil...
2201.12303
Robin Fritsch
Robin Fritsch and Roger Wattenhofer
The Price of Majority Support
9 pages, 2 figures
Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems (2022) 436-444
10.5555/3535850.3535900
null
cs.LG cs.GT cs.MA
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We consider the problem of finding a compromise between the opinions of a group of individuals on a number of mutually independent, binary topics. In this paper, we quantify the loss in representativeness that results from requiring the outcome to have majority support, in other words, the "price of majority support"...
[ { "created": "Fri, 28 Jan 2022 18:09:16 GMT", "version": "v1" } ]
2023-10-30
[ [ "Fritsch", "Robin", "" ], [ "Wattenhofer", "Roger", "" ] ]
We consider the problem of finding a compromise between the opinions of a group of individuals on a number of mutually independent, binary topics. In this paper, we quantify the loss in representativeness that results from requiring the outcome to have majority support, in other words, the "price of majority support". ...
2307.01464
Helen Carson
Helen Carson, Jason J. Ford, Michael Milford
Unsupervised Quality Prediction for Improved Single-Frame and Weighted Sequential Visual Place Recognition
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
While substantial progress has been made in the absolute performance of localization and Visual Place Recognition (VPR) techniques, it is becoming increasingly clear from translating these systems into applications that other capabilities like integrity and predictability are just as important, especially for safety-...
[ { "created": "Tue, 4 Jul 2023 03:53:05 GMT", "version": "v1" } ]
2023-07-06
[ [ "Carson", "Helen", "" ], [ "Ford", "Jason J.", "" ], [ "Milford", "Michael", "" ] ]
While substantial progress has been made in the absolute performance of localization and Visual Place Recognition (VPR) techniques, it is becoming increasingly clear from translating these systems into applications that other capabilities like integrity and predictability are just as important, especially for safety- o...
2304.13216
Ashrya Agrawal
Sourabh Prakash, Priyanshi Shah, Ashrya Agrawal
Exploiting CNNs for Semantic Segmentation with Pascal VOC
null
null
null
null
cs.CV cs.AI
http://creativecommons.org/licenses/by/4.0/
In this paper, we present a comprehensive study on semantic segmentation with the Pascal VOC dataset. Here, we have to label each pixel with a class which in turn segments the entire image based on the objects/entities present. To tackle this, we firstly use a Fully Convolution Network (FCN) baseline which gave 71.31...
[ { "created": "Wed, 26 Apr 2023 00:40:27 GMT", "version": "v1" }, { "created": "Fri, 5 May 2023 05:27:24 GMT", "version": "v2" } ]
2023-05-08
[ [ "Prakash", "Sourabh", "" ], [ "Shah", "Priyanshi", "" ], [ "Agrawal", "Ashrya", "" ] ]
In this paper, we present a comprehensive study on semantic segmentation with the Pascal VOC dataset. Here, we have to label each pixel with a class which in turn segments the entire image based on the objects/entities present. To tackle this, we firstly use a Fully Convolution Network (FCN) baseline which gave 71.31% ...
1512.01043
Harsh Thakkar
Harsh Thakkar, Dhiren Patel
Approaches for Sentiment Analysis on Twitter: A State-of-Art study
null
null
null
null
cs.SI cs.CL cs.IR
http://creativecommons.org/licenses/by-nc-sa/4.0/
Microbloging is an extremely prevalent broadcast medium amidst the Internet fraternity these days. People share their opinions and sentiments about variety of subjects like products, news, institutions, etc., every day on microbloging websites. Sentiment analysis plays a key role in prediction systems, opinion mining...
[ { "created": "Thu, 3 Dec 2015 11:29:36 GMT", "version": "v1" } ]
2015-12-04
[ [ "Thakkar", "Harsh", "" ], [ "Patel", "Dhiren", "" ] ]
Microbloging is an extremely prevalent broadcast medium amidst the Internet fraternity these days. People share their opinions and sentiments about variety of subjects like products, news, institutions, etc., every day on microbloging websites. Sentiment analysis plays a key role in prediction systems, opinion mining s...
1606.01467
Jie Fu
Jie Fu
Deep Q-Networks for Accelerating the Training of Deep Neural Networks
We choose to withdraw this paper. The DQN itself has too many hyperparameters, which makes it almost impossible to be applied to reasonably large datasets. In the later versions (from v4) with SGDR experiments, it seems that the agent only performs random actions
null
null
null
cs.LG cs.NE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we propose a principled deep reinforcement learning (RL) approach that is able to accelerate the convergence rate of general deep neural networks (DNNs). With our approach, a deep RL agent (synonym for optimizer in this work) is used to automatically learn policies about how to schedule learning rates ...
[ { "created": "Sun, 5 Jun 2016 06:42:56 GMT", "version": "v1" }, { "created": "Thu, 13 Jul 2017 08:49:36 GMT", "version": "v10" }, { "created": "Wed, 8 Jun 2016 17:02:49 GMT", "version": "v2" }, { "created": "Mon, 1 Aug 2016 14:17:18 GMT", "version": "v3" }, { "cre...
2017-07-14
[ [ "Fu", "Jie", "" ] ]
In this paper, we propose a principled deep reinforcement learning (RL) approach that is able to accelerate the convergence rate of general deep neural networks (DNNs). With our approach, a deep RL agent (synonym for optimizer in this work) is used to automatically learn policies about how to schedule learning rates du...
1901.04933
David Puljiz
David Puljiz, Erik St\"ohr, Katharina S. Riesterer, Bj\"orn Hein, Torsten Kr\"oger
Sensorless Hand Guidance using Microsoft Hololens
Accepted to HRI2019 - Late Breaking reports
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Hand guidance of robots has proven to be a useful tool both for programming trajectories and in kinesthetic teaching. However hand guidance is usually relegated to robots possessing joint-torque sensors (JTS). Here we propose to extend hand guidance to robots lacking those sensors through the use of an Augmented Real...
[ { "created": "Tue, 15 Jan 2019 16:55:43 GMT", "version": "v1" } ]
2019-01-16
[ [ "Puljiz", "David", "" ], [ "Stöhr", "Erik", "" ], [ "Riesterer", "Katharina S.", "" ], [ "Hein", "Björn", "" ], [ "Kröger", "Torsten", "" ] ]
Hand guidance of robots has proven to be a useful tool both for programming trajectories and in kinesthetic teaching. However hand guidance is usually relegated to robots possessing joint-torque sensors (JTS). Here we propose to extend hand guidance to robots lacking those sensors through the use of an Augmented Realit...
1612.05016
Johannes Stegmann Dr.
Johannes Stegmann
Research performance of UNU - A bibliometric analysis of the United Nations University
13 pages, 4 figures, 9 tables
null
null
null
cs.DL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The scientific paper output of the United Nations University (UNU) was bibliometrically analysed. It was found that (i) a noticeable continous paper output starts in 1995, (ii) about 65% of the research papers have been published as international cooperations and 18% as single-authored papers, (iv) the research paper...
[ { "created": "Thu, 15 Dec 2016 11:08:02 GMT", "version": "v1" } ]
2020-05-13
[ [ "Stegmann", "Johannes", "" ] ]
The scientific paper output of the United Nations University (UNU) was bibliometrically analysed. It was found that (i) a noticeable continous paper output starts in 1995, (ii) about 65% of the research papers have been published as international cooperations and 18% as single-authored papers, (iv) the research papers ...
2407.16430
Kai Liu
Kai Liu, Zhihang Fu, Sheng Jin, Chao Chen, Ze Chen, Rongxin Jiang, Fan Zhou, Yaowu Chen, Jieping Ye
Rethinking Out-of-Distribution Detection on Imbalanced Data Distribution
N/A
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Detecting and rejecting unknown out-of-distribution (OOD) samples is critical for deployed neural networks to void unreliable predictions. In real-world scenarios, however, the efficacy of existing OOD detection methods is often impeded by the inherent imbalance of in-distribution (ID) data, which causes significant ...
[ { "created": "Tue, 23 Jul 2024 12:28:59 GMT", "version": "v1" } ]
2024-07-24
[ [ "Liu", "Kai", "" ], [ "Fu", "Zhihang", "" ], [ "Jin", "Sheng", "" ], [ "Chen", "Chao", "" ], [ "Chen", "Ze", "" ], [ "Jiang", "Rongxin", "" ], [ "Zhou", "Fan", "" ], [ "Chen", "Yaowu", "" ...
Detecting and rejecting unknown out-of-distribution (OOD) samples is critical for deployed neural networks to void unreliable predictions. In real-world scenarios, however, the efficacy of existing OOD detection methods is often impeded by the inherent imbalance of in-distribution (ID) data, which causes significant pe...
2111.04007
Nitika Saran
Sanjith Athlur, Nitika Saran, Muthian Sivathanu, Ramachandran Ramjee and Nipun Kwatra
Varuna: Scalable, Low-cost Training of Massive Deep Learning Models
14 pages, 10 figures
null
null
null
cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Systems for training massive deep learning models (billions of parameters) today assume and require specialized "hyper-clusters": hundreds or thousands of GPUs wired with specialized high-bandwidth interconnects such as NV-Link and Infiniband. Besides being expensive, such dependence on hyper-clusters and custom high...
[ { "created": "Sun, 7 Nov 2021 05:33:48 GMT", "version": "v1" }, { "created": "Mon, 15 Nov 2021 08:30:00 GMT", "version": "v2" } ]
2021-11-16
[ [ "Athlur", "Sanjith", "" ], [ "Saran", "Nitika", "" ], [ "Sivathanu", "Muthian", "" ], [ "Ramjee", "Ramachandran", "" ], [ "Kwatra", "Nipun", "" ] ]
Systems for training massive deep learning models (billions of parameters) today assume and require specialized "hyper-clusters": hundreds or thousands of GPUs wired with specialized high-bandwidth interconnects such as NV-Link and Infiniband. Besides being expensive, such dependence on hyper-clusters and custom high-s...
1211.4520
Chuan Zhang
Chuan Zhang, Gerhard Dangelmayr, Iuliana Oprea
Storing cycles in Hopfield-type networks with pseudoinverse learning rule: admissibility and network topology
48 pages, 3 figures
Neural Networks, Volume 46, October 2013, Pages 283-298
10.1016/j.neunet.2013.06.008
null
cs.NE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Cyclic patterns of neuronal activity are ubiquitous in animal nervous systems, and partially responsible for generating and controlling rhythmic movements such as locomotion, respiration, swallowing and so on. Clarifying the role of the network connectivities for generating cyclic patterns is fundamental for understa...
[ { "created": "Mon, 19 Nov 2012 17:45:25 GMT", "version": "v1" }, { "created": "Sun, 28 Apr 2013 04:33:58 GMT", "version": "v2" } ]
2013-08-26
[ [ "Zhang", "Chuan", "" ], [ "Dangelmayr", "Gerhard", "" ], [ "Oprea", "Iuliana", "" ] ]
Cyclic patterns of neuronal activity are ubiquitous in animal nervous systems, and partially responsible for generating and controlling rhythmic movements such as locomotion, respiration, swallowing and so on. Clarifying the role of the network connectivities for generating cyclic patterns is fundamental for understand...
1610.00681
Muhammed Omer Sayin
Muhammed O. Sayin, Suleyman S. Kozat, and Tamer Ba\c{s}ar
Team-Optimal Distributed MMSE Estimation in General and Tree Networks
Submitted to Digital Signal Processing
null
null
null
cs.SY cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We construct team-optimal estimation algorithms over distributed networks for state estimation in the finite-horizon mean-square error (MSE) sense. Here, we have a distributed collection of agents with processing and cooperation capabilities. These agents observe noisy samples of a desired state through a linear mode...
[ { "created": "Mon, 3 Oct 2016 19:09:01 GMT", "version": "v1" }, { "created": "Sun, 8 Jan 2017 19:28:02 GMT", "version": "v2" } ]
2017-01-10
[ [ "Sayin", "Muhammed O.", "" ], [ "Kozat", "Suleyman S.", "" ], [ "Başar", "Tamer", "" ] ]
We construct team-optimal estimation algorithms over distributed networks for state estimation in the finite-horizon mean-square error (MSE) sense. Here, we have a distributed collection of agents with processing and cooperation capabilities. These agents observe noisy samples of a desired state through a linear model ...
1502.04888
Haris Aziz
Haris Aziz and Serge Gaspers and Simon Mackenzie and Nicholas Mattei and Nina Narodytska and Toby Walsh
Equilibria Under the Probabilistic Serial Rule
arXiv admin note: text overlap with arXiv:1401.6523, this paper supersedes the equilibria section in our previous report arXiv:1401.6523
null
null
null
cs.GT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The probabilistic serial (PS) rule is a prominent randomized rule for assigning indivisible goods to agents. Although it is well known for its good fairness and welfare properties, it is not strategyproof. In view of this, we address several fundamental questions regarding equilibria under PS. Firstly, we show that N...
[ { "created": "Tue, 17 Feb 2015 13:26:38 GMT", "version": "v1" }, { "created": "Mon, 30 Mar 2015 22:32:01 GMT", "version": "v2" } ]
2015-04-01
[ [ "Aziz", "Haris", "" ], [ "Gaspers", "Serge", "" ], [ "Mackenzie", "Simon", "" ], [ "Mattei", "Nicholas", "" ], [ "Narodytska", "Nina", "" ], [ "Walsh", "Toby", "" ] ]
The probabilistic serial (PS) rule is a prominent randomized rule for assigning indivisible goods to agents. Although it is well known for its good fairness and welfare properties, it is not strategyproof. In view of this, we address several fundamental questions regarding equilibria under PS. Firstly, we show that Nas...
1202.4033
Arun Sridharan
Arun Sridharan, C.Emre Koksal
Energy Efficient Greedy Link Scheduling and Power Control in wireless networks
null
null
null
null
cs.NI cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We consider the problem of joint link scheduling and power control for wireless networks with average transmission power constraints. Due to the high computational complexity of the optimal policies, we extend the class of greedy link scheduling policies to handle average power constraints. We develop a greedy link s...
[ { "created": "Fri, 17 Feb 2012 22:46:12 GMT", "version": "v1" } ]
2012-02-21
[ [ "Sridharan", "Arun", "" ], [ "Koksal", "C. Emre", "" ] ]
We consider the problem of joint link scheduling and power control for wireless networks with average transmission power constraints. Due to the high computational complexity of the optimal policies, we extend the class of greedy link scheduling policies to handle average power constraints. We develop a greedy link sch...
2306.12245
Yinghui Li
Yinghui Li, Yong Jiang, Yangning Li, Xingyu Lu, Pengjun Xie, Ying Shen, Hai-Tao Zheng
Bidirectional End-to-End Learning of Retriever-Reader Paradigm for Entity Linking
null
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Entity Linking (EL) is a fundamental task for Information Extraction and Knowledge Graphs. The general form of EL (i.e., end-to-end EL) aims to first find mentions in the given input document and then link the mentions to corresponding entities in a specific knowledge base. Recently, the paradigm of retriever-reader ...
[ { "created": "Wed, 21 Jun 2023 13:04:30 GMT", "version": "v1" }, { "created": "Mon, 3 Jul 2023 09:03:22 GMT", "version": "v2" }, { "created": "Wed, 10 Jan 2024 17:48:25 GMT", "version": "v3" }, { "created": "Wed, 20 Mar 2024 03:51:23 GMT", "version": "v4" } ]
2024-03-21
[ [ "Li", "Yinghui", "" ], [ "Jiang", "Yong", "" ], [ "Li", "Yangning", "" ], [ "Lu", "Xingyu", "" ], [ "Xie", "Pengjun", "" ], [ "Shen", "Ying", "" ], [ "Zheng", "Hai-Tao", "" ] ]
Entity Linking (EL) is a fundamental task for Information Extraction and Knowledge Graphs. The general form of EL (i.e., end-to-end EL) aims to first find mentions in the given input document and then link the mentions to corresponding entities in a specific knowledge base. Recently, the paradigm of retriever-reader pr...
2307.03630
B\'alint Zolt\'an Dar\'oczy
D\'aniel R\'acz and Mih\'aly Petreczky and B\'alint Dar\'oczy
PAC bounds of continuous Linear Parameter-Varying systems related to neural ODEs
12 pages
null
null
null
cs.LG
http://creativecommons.org/licenses/by/4.0/
We consider the problem of learning Neural Ordinary Differential Equations (neural ODEs) within the context of Linear Parameter-Varying (LPV) systems in continuous-time. LPV systems contain bilinear systems which are known to be universal approximators for non-linear systems. Moreover, a large class of neural ODEs ca...
[ { "created": "Fri, 7 Jul 2023 14:39:18 GMT", "version": "v1" } ]
2023-07-10
[ [ "Rácz", "Dániel", "" ], [ "Petreczky", "Mihály", "" ], [ "Daróczy", "Bálint", "" ] ]
We consider the problem of learning Neural Ordinary Differential Equations (neural ODEs) within the context of Linear Parameter-Varying (LPV) systems in continuous-time. LPV systems contain bilinear systems which are known to be universal approximators for non-linear systems. Moreover, a large class of neural ODEs can ...
2008.02456
Hao Guo
Hao Guo, Zhenchang Xing, Xiaohong Li
Predicting Missing Information of Key Aspects in Vulnerability Reports
null
null
null
null
cs.SE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Software vulnerabilities have been continually disclosed and documented. An important practice in documenting vulnerabilities is to describe the key vulnerability aspects, such as vulnerability type, root cause, affected product, impact, attacker type and attack vector, for the effective search and management of fast...
[ { "created": "Thu, 6 Aug 2020 04:53:33 GMT", "version": "v1" } ]
2020-08-07
[ [ "Guo", "Hao", "" ], [ "Xing", "Zhenchang", "" ], [ "Li", "Xiaohong", "" ] ]
Software vulnerabilities have been continually disclosed and documented. An important practice in documenting vulnerabilities is to describe the key vulnerability aspects, such as vulnerability type, root cause, affected product, impact, attacker type and attack vector, for the effective search and management of fast-g...
2201.07197
Uri Zwick
Robert E. Tarjan, Uri Zwick
Finding Strong Components Using Depth-First Search
27 pages. In memory of Pierre Rosenstiehl. A slightly revised version
null
null
null
cs.DS
http://creativecommons.org/licenses/by/4.0/
We survey three algorithms that use depth-first search to find the strong components of a directed graph in linear time: (1) Tarjan's algorithm; (2) a cycle-finding algorithm; and (3) a bidirectional search algorithm.
[ { "created": "Tue, 18 Jan 2022 18:48:58 GMT", "version": "v1" }, { "created": "Thu, 24 Mar 2022 18:30:50 GMT", "version": "v2" }, { "created": "Mon, 11 Apr 2022 16:08:24 GMT", "version": "v3" } ]
2022-04-12
[ [ "Tarjan", "Robert E.", "" ], [ "Zwick", "Uri", "" ] ]
We survey three algorithms that use depth-first search to find the strong components of a directed graph in linear time: (1) Tarjan's algorithm; (2) a cycle-finding algorithm; and (3) a bidirectional search algorithm.
2109.14830
Masataro Asai
Clement Gehring, Masataro Asai, Rohan Chitnis, Tom Silver, Leslie Pack Kaelbling, Shirin Sohrabi, Michael Katz
Reinforcement Learning for Classical Planning: Viewing Heuristics as Dense Reward Generators
Equal contributions by the first two authors. This manuscript is a camera-ready version accepted in ICAPS-2022. It is significantly updated from past versions (e.g., in the ICAPS PRL (Planning and RL) workshop) with additional experiments comparing existing work (STRIPS-HGN (Shen, Trevizan, and Thiebaux 2020) a...
null
null
null
cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recent advances in reinforcement learning (RL) have led to a growing interest in applying RL to classical planning domains or applying classical planning methods to some complex RL domains. However, the long-horizon goal-based problems found in classical planning lead to sparse rewards for RL, making direct applicati...
[ { "created": "Thu, 30 Sep 2021 03:36:01 GMT", "version": "v1" }, { "created": "Mon, 7 Mar 2022 18:51:01 GMT", "version": "v2" } ]
2022-03-08
[ [ "Gehring", "Clement", "" ], [ "Asai", "Masataro", "" ], [ "Chitnis", "Rohan", "" ], [ "Silver", "Tom", "" ], [ "Kaelbling", "Leslie Pack", "" ], [ "Sohrabi", "Shirin", "" ], [ "Katz", "Michael", "" ] ]
Recent advances in reinforcement learning (RL) have led to a growing interest in applying RL to classical planning domains or applying classical planning methods to some complex RL domains. However, the long-horizon goal-based problems found in classical planning lead to sparse rewards for RL, making direct application...
2311.05646
Sean Hooten
Sean Hooten, Peng Sun, Liron Gantz, Marco Fiorentino, Raymond G. Beausoleil, Thomas Van Vaerenbergh
Automatic differentiation accelerated shape optimization approaches to photonic inverse design on rectilinear simulation grids
29 pages, 15 figures
null
null
null
cs.CE physics.optics
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Shape optimization approaches to inverse design offer low-dimensional, physically-guided parameterizations of structures by representing them as combinations of shape primitives. However, on discretized rectilinear simulation grids, computing the gradient of a user objective via the adjoint variables method requires ...
[ { "created": "Tue, 7 Nov 2023 06:46:59 GMT", "version": "v1" } ]
2023-11-13
[ [ "Hooten", "Sean", "" ], [ "Sun", "Peng", "" ], [ "Gantz", "Liron", "" ], [ "Fiorentino", "Marco", "" ], [ "Beausoleil", "Raymond G.", "" ], [ "Van Vaerenbergh", "Thomas", "" ] ]
Shape optimization approaches to inverse design offer low-dimensional, physically-guided parameterizations of structures by representing them as combinations of shape primitives. However, on discretized rectilinear simulation grids, computing the gradient of a user objective via the adjoint variables method requires a ...
1202.4503
Arvind Narayanan
Arvind Narayanan and Vincent Toubiana and Solon Barocas and Helen Nissenbaum and Dan Boneh
A Critical Look at Decentralized Personal Data Architectures
null
null
null
null
cs.CY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
While the Internet was conceived as a decentralized network, the most widely used web applications today tend toward centralization. Control increasingly rests with centralized service providers who, as a consequence, have also amassed unprecedented amounts of data about the behaviors and personalities of individuals...
[ { "created": "Tue, 21 Feb 2012 01:15:51 GMT", "version": "v1" } ]
2012-02-22
[ [ "Narayanan", "Arvind", "" ], [ "Toubiana", "Vincent", "" ], [ "Barocas", "Solon", "" ], [ "Nissenbaum", "Helen", "" ], [ "Boneh", "Dan", "" ] ]
While the Internet was conceived as a decentralized network, the most widely used web applications today tend toward centralization. Control increasingly rests with centralized service providers who, as a consequence, have also amassed unprecedented amounts of data about the behaviors and personalities of individuals. ...
1905.04447
Zhao Song
Yin Tat Lee, Zhao Song, Qiuyi Zhang
Solving Empirical Risk Minimization in the Current Matrix Multiplication Time
null
null
null
null
cs.DS cs.LG math.OC stat.ML
http://creativecommons.org/licenses/by-sa/4.0/
Many convex problems in machine learning and computer science share the same form: \begin{align*} \min_{x} \sum_{i} f_i( A_i x + b_i), \end{align*} where $f_i$ are convex functions on $\mathbb{R}^{n_i}$ with constant $n_i$, $A_i \in \mathbb{R}^{n_i \times d}$, $b_i \in \mathbb{R}^{n_i}$ and $\sum_i n_i = n$. This pro...
[ { "created": "Sat, 11 May 2019 04:42:16 GMT", "version": "v1" } ]
2019-05-14
[ [ "Lee", "Yin Tat", "" ], [ "Song", "Zhao", "" ], [ "Zhang", "Qiuyi", "" ] ]
Many convex problems in machine learning and computer science share the same form: \begin{align*} \min_{x} \sum_{i} f_i( A_i x + b_i), \end{align*} where $f_i$ are convex functions on $\mathbb{R}^{n_i}$ with constant $n_i$, $A_i \in \mathbb{R}^{n_i \times d}$, $b_i \in \mathbb{R}^{n_i}$ and $\sum_i n_i = n$. This probl...
2306.01855
Joel Ruben Antony Moniz
Jiarui Lu, Bo-Hsiang Tseng, Joel Ruben Antony Moniz, Site Li, Xueyun Zhu, Hong Yu, Murat Akbacak
5IDER: Unified Query Rewriting for Steering, Intent Carryover, Disfluencies, Entity Carryover and Repair
Interspeech 2023
null
10.21437/Interspeech.2023-1038
null
cs.CL cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Providing voice assistants the ability to navigate multi-turn conversations is a challenging problem. Handling multi-turn interactions requires the system to understand various conversational use-cases, such as steering, intent carryover, disfluencies, entity carryover, and repair. The complexity of this problem is c...
[ { "created": "Fri, 2 Jun 2023 18:17:52 GMT", "version": "v1" } ]
2023-10-30
[ [ "Lu", "Jiarui", "" ], [ "Tseng", "Bo-Hsiang", "" ], [ "Moniz", "Joel Ruben Antony", "" ], [ "Li", "Site", "" ], [ "Zhu", "Xueyun", "" ], [ "Yu", "Hong", "" ], [ "Akbacak", "Murat", "" ] ]
Providing voice assistants the ability to navigate multi-turn conversations is a challenging problem. Handling multi-turn interactions requires the system to understand various conversational use-cases, such as steering, intent carryover, disfluencies, entity carryover, and repair. The complexity of this problem is com...
2007.03433
Jin Guo
Jin Guo
Decentralized Deep Reinforcement Learning for Network Level Traffic Signal Control
null
null
null
null
cs.LG cs.AI eess.SP
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this thesis, I propose a family of fully decentralized deep multi-agent reinforcement learning (MARL) algorithms to achieve high, real-time performance in network-level traffic signal control. In this approach, each intersection is modeled as an agent that plays a Markovian Game against the other intersection node...
[ { "created": "Thu, 2 Jul 2020 06:58:27 GMT", "version": "v1" }, { "created": "Fri, 17 Jul 2020 23:15:45 GMT", "version": "v2" } ]
2020-07-21
[ [ "Guo", "Jin", "" ] ]
In this thesis, I propose a family of fully decentralized deep multi-agent reinforcement learning (MARL) algorithms to achieve high, real-time performance in network-level traffic signal control. In this approach, each intersection is modeled as an agent that plays a Markovian Game against the other intersection nodes ...
1804.08803
Fei Hu
Fei Hu, Jiong Du, Du Xu
Optimized Deployment of Network Function for Resource Pooling Switch
6 pages
null
null
null
cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The disadvantages of the combination of traditional switches and middleboxes have being exposed under the condition of increasingly various network function demands,such as function flexibility, performance scalability and resource utilization. To solve this problem, we design Resource Pooling Switch Architecture (RP...
[ { "created": "Tue, 24 Apr 2018 01:43:39 GMT", "version": "v1" } ]
2018-04-25
[ [ "Hu", "Fei", "" ], [ "Du", "Jiong", "" ], [ "Xu", "Du", "" ] ]
The disadvantages of the combination of traditional switches and middleboxes have being exposed under the condition of increasingly various network function demands,such as function flexibility, performance scalability and resource utilization. To solve this problem, we design Resource Pooling Switch Architecture (RPSA...
2308.04402
Shafiq Ahmad
Shafiq Ahmad, Pietro Morerio, Alessio Del Bue
Person Re-Identification without Identification via Event Anonymization
Accepted at International Conference on Computer Vision (ICCV), 2023
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Wide-scale use of visual surveillance in public spaces puts individual privacy at stake while increasing resource consumption (energy, bandwidth, and computation). Neuromorphic vision sensors (event-cameras) have been recently considered a valid solution to the privacy issue because they do not capture detailed RGB v...
[ { "created": "Tue, 8 Aug 2023 17:04:53 GMT", "version": "v1" }, { "created": "Wed, 9 Aug 2023 13:15:37 GMT", "version": "v2" }, { "created": "Fri, 11 Aug 2023 01:21:44 GMT", "version": "v3" }, { "created": "Thu, 17 Aug 2023 23:00:58 GMT", "version": "v4" } ]
2023-08-21
[ [ "Ahmad", "Shafiq", "" ], [ "Morerio", "Pietro", "" ], [ "Del Bue", "Alessio", "" ] ]
Wide-scale use of visual surveillance in public spaces puts individual privacy at stake while increasing resource consumption (energy, bandwidth, and computation). Neuromorphic vision sensors (event-cameras) have been recently considered a valid solution to the privacy issue because they do not capture detailed RGB vis...
2112.08261
Juan Camilo V\'asquez-Correa
Juan Camilo Vasquez-Correa, Juan Carlos Guerrero-Sierra, Jose Luis Pemberty-Tamayo, Juan Esteban Jaramillo, Andres Felipe Tejada-Castro
One System to Rule them All: a Universal Intent Recognition System for Customer Service Chatbots
null
null
null
null
cs.HC cs.CL
http://creativecommons.org/publicdomain/zero/1.0/
Customer service chatbots are conversational systems designed to provide information to customers about products/services offered by different companies. Particularly, intent recognition is one of the core components in the natural language understating capabilities of a chatbot system. Among the different intents th...
[ { "created": "Wed, 15 Dec 2021 16:45:55 GMT", "version": "v1" } ]
2021-12-16
[ [ "Vasquez-Correa", "Juan Camilo", "" ], [ "Guerrero-Sierra", "Juan Carlos", "" ], [ "Pemberty-Tamayo", "Jose Luis", "" ], [ "Jaramillo", "Juan Esteban", "" ], [ "Tejada-Castro", "Andres Felipe", "" ] ]
Customer service chatbots are conversational systems designed to provide information to customers about products/services offered by different companies. Particularly, intent recognition is one of the core components in the natural language understating capabilities of a chatbot system. Among the different intents that...
2111.02662
Trent Muhr
Wensheng Zhang, Trent Muhr
TEE-based Selective Testing of Local Workers in Federated Learning Systems
null
null
null
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper considers a federated learning system composed of a central coordinating server and multiple distributed local workers, all having access to trusted execution environments (TEEs). In order to ensure that the untrusted workers correctly perform local learning, we propose a new TEE-based approach that also c...
[ { "created": "Thu, 4 Nov 2021 07:02:58 GMT", "version": "v1" } ]
2021-11-05
[ [ "Zhang", "Wensheng", "" ], [ "Muhr", "Trent", "" ] ]
This paper considers a federated learning system composed of a central coordinating server and multiple distributed local workers, all having access to trusted execution environments (TEEs). In order to ensure that the untrusted workers correctly perform local learning, we propose a new TEE-based approach that also com...
2002.03388
Shushan Arakelyan
Shushan Arakelyan, Sima Arasteh, Christophe Hauser, Erik Kline and Aram Galstyan
Bin2vec: Learning Representations of Binary Executable Programs for Security Tasks
null
null
null
null
cs.CR cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Tackling binary program analysis problems has traditionally implied manually defining rules and heuristics, a tedious and time-consuming task for human analysts. In order to improve automation and scalability, we propose an alternative direction based on distributed representations of binary programs with applicabili...
[ { "created": "Sun, 9 Feb 2020 15:46:43 GMT", "version": "v1" }, { "created": "Sat, 22 May 2021 17:27:57 GMT", "version": "v2" } ]
2021-05-25
[ [ "Arakelyan", "Shushan", "" ], [ "Arasteh", "Sima", "" ], [ "Hauser", "Christophe", "" ], [ "Kline", "Erik", "" ], [ "Galstyan", "Aram", "" ] ]
Tackling binary program analysis problems has traditionally implied manually defining rules and heuristics, a tedious and time-consuming task for human analysts. In order to improve automation and scalability, we propose an alternative direction based on distributed representations of binary programs with applicability...
1809.02665
Michael Jacobs
Sanghyun Choi, Nikita Ivkin, Vladimir Braverman, Michael A. Jacobs
DreamNLP: Novel NLP System for Clinical Report Metadata Extraction using Count Sketch Data Streaming Algorithm: Preliminary Results
13 pages, 3 figures, US patent
null
null
null
cs.LG eess.AS stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Extracting information from electronic health records (EHR) is a challenging task since it requires prior knowledge of the reports and some natural language processing algorithm (NLP). With the growing number of EHR implementations, such knowledge is increasingly challenging to obtain in an efficient manner. We addre...
[ { "created": "Sun, 26 Aug 2018 01:42:29 GMT", "version": "v1" } ]
2019-08-02
[ [ "Choi", "Sanghyun", "" ], [ "Ivkin", "Nikita", "" ], [ "Braverman", "Vladimir", "" ], [ "Jacobs", "Michael A.", "" ] ]
Extracting information from electronic health records (EHR) is a challenging task since it requires prior knowledge of the reports and some natural language processing algorithm (NLP). With the growing number of EHR implementations, such knowledge is increasingly challenging to obtain in an efficient manner. We address...
2310.11417
Xiao Wang
Bo Jiang, Zitian Wang, Xixi Wang, Ziyan Zhang, Lan Chen, Xiao Wang, Bin Luo
VcT: Visual change Transformer for Remote Sensing Image Change Detection
Accepted by IEEE Transactions on Geoscience and Remote Sensing (TGRS) 2023
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Existing visual change detectors usually adopt CNNs or Transformers for feature representation learning and focus on learning effective representation for the changed regions between images. Although good performance can be obtained by enhancing the features of the change regions, however, these works are still limit...
[ { "created": "Tue, 17 Oct 2023 17:25:31 GMT", "version": "v1" } ]
2023-10-18
[ [ "Jiang", "Bo", "" ], [ "Wang", "Zitian", "" ], [ "Wang", "Xixi", "" ], [ "Zhang", "Ziyan", "" ], [ "Chen", "Lan", "" ], [ "Wang", "Xiao", "" ], [ "Luo", "Bin", "" ] ]
Existing visual change detectors usually adopt CNNs or Transformers for feature representation learning and focus on learning effective representation for the changed regions between images. Although good performance can be obtained by enhancing the features of the change regions, however, these works are still limited...
1804.09808
Paolo Frasconi
Tijn Borghuis, Alessandro Tibo, Simone Conforti, Luca Canciello, Lorenzo Brusci, Paolo Frasconi
Off the Beaten Track: Using Deep Learning to Interpolate Between Music Genres
null
null
null
null
cs.SD cs.LG cs.MM eess.AS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We describe a system based on deep learning that generates drum patterns in the electronic dance music domain. Experimental results reveal that generated patterns can be employed to produce musically sound and creative transitions between different genres, and that the process of generation is of interest to practiti...
[ { "created": "Wed, 25 Apr 2018 21:39:39 GMT", "version": "v1" }, { "created": "Wed, 2 May 2018 16:56:08 GMT", "version": "v2" } ]
2018-05-03
[ [ "Borghuis", "Tijn", "" ], [ "Tibo", "Alessandro", "" ], [ "Conforti", "Simone", "" ], [ "Canciello", "Luca", "" ], [ "Brusci", "Lorenzo", "" ], [ "Frasconi", "Paolo", "" ] ]
We describe a system based on deep learning that generates drum patterns in the electronic dance music domain. Experimental results reveal that generated patterns can be employed to produce musically sound and creative transitions between different genres, and that the process of generation is of interest to practition...
2105.09413
Mateus de Oliveira Oliveira
Emmanuel Arrighi, Henning Fernau, Daniel Lokshtanov, Mateus de Oliveira Oliveira, Petra Wolf
Diversity in Kemeny Rank Aggregation: A Parameterized Approach
Accepted to the 30th International Joint Conference on Artificial Intelligence (IJCAI 2021)
null
null
null
cs.AI cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In its most traditional setting, the main concern of optimization theory is the search for optimal solutions for instances of a given computational problem. A recent trend of research in artificial intelligence, called solution diversity, has focused on the development of notions of optimality that may be more approp...
[ { "created": "Wed, 19 May 2021 21:50:03 GMT", "version": "v1" } ]
2021-05-21
[ [ "Arrighi", "Emmanuel", "" ], [ "Fernau", "Henning", "" ], [ "Lokshtanov", "Daniel", "" ], [ "Oliveira", "Mateus de Oliveira", "" ], [ "Wolf", "Petra", "" ] ]
In its most traditional setting, the main concern of optimization theory is the search for optimal solutions for instances of a given computational problem. A recent trend of research in artificial intelligence, called solution diversity, has focused on the development of notions of optimality that may be more appropri...
2308.11161
Thanh Dat Nguyen
Thanh-Dat Nguyen, Yang Zhou, Xuan Bach D. Le, Patanamon (Pick) Thongtanunam, David Lo
Adversarial Attacks on Code Models with Discriminative Graph Patterns
null
null
null
null
cs.SE
http://creativecommons.org/licenses/by/4.0/
Pre-trained language models of code are now widely used in various software engineering tasks such as code generation, code completion, vulnerability detection, etc. This, in turn, poses security and reliability risks to these models. One of the important threats is \textit{adversarial attacks}, which can lead to err...
[ { "created": "Tue, 22 Aug 2023 03:40:34 GMT", "version": "v1" } ]
2023-08-23
[ [ "Nguyen", "Thanh-Dat", "", "Pick" ], [ "Zhou", "Yang", "", "Pick" ], [ "Le", "Xuan Bach D.", "", "Pick" ], [ "Patanamon", "", "", "Pick" ], [ "Thongtanunam", "", "" ], [ "Lo", "David", "" ] ]
Pre-trained language models of code are now widely used in various software engineering tasks such as code generation, code completion, vulnerability detection, etc. This, in turn, poses security and reliability risks to these models. One of the important threats is \textit{adversarial attacks}, which can lead to erron...
2101.02573
Hazem Soliman
Hazem M. Soliman, Geoff Salmon, Du\v{s}an Sovilj, Mohan Rao
RANK: AI-assisted End-to-End Architecture for Detecting Persistent Attacks in Enterprise Networks
null
null
null
null
cs.CR cs.LG
http://creativecommons.org/licenses/by-nc-sa/4.0/
Advanced Persistent Threats (APTs) are sophisticated multi-step attacks, planned and executed by skilled adversaries targeting modern government and enterprise networks. Intrusion Detection Systems (IDSs) and User and Entity Behavior Analytics (UEBA) are commonly employed to aid a security analyst in the detection of...
[ { "created": "Wed, 6 Jan 2021 15:59:51 GMT", "version": "v1" } ]
2021-01-08
[ [ "Soliman", "Hazem M.", "" ], [ "Salmon", "Geoff", "" ], [ "Sovilj", "Dušan", "" ], [ "Rao", "Mohan", "" ] ]
Advanced Persistent Threats (APTs) are sophisticated multi-step attacks, planned and executed by skilled adversaries targeting modern government and enterprise networks. Intrusion Detection Systems (IDSs) and User and Entity Behavior Analytics (UEBA) are commonly employed to aid a security analyst in the detection of A...
2202.02906
Junlong Lyu
Junlong Lyu, Zhitang Chen, Chang Feng, Wenjing Cun, Shengyu Zhu, Yanhui Geng, Zhijie Xu, Yongwei Chen
Universality of parametric Coupling Flows over parametric diffeomorphisms
22 pages, 6 figures
null
null
null
cs.LG cs.AI math.DG math.FA
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Invertible neural networks based on Coupling Flows CFlows) have various applications such as image synthesis and data compression. The approximation universality for CFlows is of paramount importance to ensure the model expressiveness. In this paper, we prove that CFlows can approximate any diffeomorphism in C^k-norm...
[ { "created": "Mon, 7 Feb 2022 02:10:32 GMT", "version": "v1" }, { "created": "Tue, 8 Feb 2022 07:32:34 GMT", "version": "v2" } ]
2022-02-09
[ [ "Lyu", "Junlong", "" ], [ "Chen", "Zhitang", "" ], [ "Feng", "Chang", "" ], [ "Cun", "Wenjing", "" ], [ "Zhu", "Shengyu", "" ], [ "Geng", "Yanhui", "" ], [ "Xu", "Zhijie", "" ], [ "Chen", "Yongw...
Invertible neural networks based on Coupling Flows CFlows) have various applications such as image synthesis and data compression. The approximation universality for CFlows is of paramount importance to ensure the model expressiveness. In this paper, we prove that CFlows can approximate any diffeomorphism in C^k-norm i...
2205.12381
Siddharth Reddy
Siddharth Reddy, Sergey Levine, Anca D. Dragan
First Contact: Unsupervised Human-Machine Co-Adaptation via Mutual Information Maximization
Accepted to Neural Information Processing Systems (NeurIPS) 2022
null
null
null
cs.LG cs.HC cs.RO
http://creativecommons.org/licenses/by/4.0/
How can we train an assistive human-machine interface (e.g., an electromyography-based limb prosthesis) to translate a user's raw command signals into the actions of a robot or computer when there is no prior mapping, we cannot ask the user for supervision in the form of action labels or reward feedback, and we do no...
[ { "created": "Tue, 24 May 2022 21:57:18 GMT", "version": "v1" }, { "created": "Thu, 15 Sep 2022 03:08:54 GMT", "version": "v2" } ]
2022-09-16
[ [ "Reddy", "Siddharth", "" ], [ "Levine", "Sergey", "" ], [ "Dragan", "Anca D.", "" ] ]
How can we train an assistive human-machine interface (e.g., an electromyography-based limb prosthesis) to translate a user's raw command signals into the actions of a robot or computer when there is no prior mapping, we cannot ask the user for supervision in the form of action labels or reward feedback, and we do not ...
2101.05951
Houwang Tu
Tu Houwang, Wang Yongxian, Xiao Wenbin, Lan Qiang, Liu Wei
Two Chebyshev Spectral Methods for Solving Normal Modes in Atmospheric Acoustics
10 pages, 8 figures and 3 tables
null
10.3390/e23060705
null
cs.CE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The normal mode model is important in computational atmospheric acoustics. It is often used to compute the atmospheric acoustic field under a harmonic point source. Its solution consists of a set of discrete modes radiating into the upper atmosphere, usually related to the continuous spectrum. In this article, we pre...
[ { "created": "Fri, 15 Jan 2021 03:16:24 GMT", "version": "v1" } ]
2021-06-04
[ [ "Houwang", "Tu", "" ], [ "Yongxian", "Wang", "" ], [ "Wenbin", "Xiao", "" ], [ "Qiang", "Lan", "" ], [ "Wei", "Liu", "" ] ]
The normal mode model is important in computational atmospheric acoustics. It is often used to compute the atmospheric acoustic field under a harmonic point source. Its solution consists of a set of discrete modes radiating into the upper atmosphere, usually related to the continuous spectrum. In this article, we prese...
2001.08980
Alexandr Grichshenko
Barakat. J. Akinsanya, Luiz J.P. Ara\'ujo, Mariia Charikova, Susanna Gimaeva, Alexandr Grichshenko, Adil Khan, Manuel Mazzara, Ozioma Okonicha N and Daniil Shilintsev
Machine Learning and value generation in Software Development: a survey
To be published in the proceeding of International Conference on Software Testing, Machine Learning and Complex Process Analysis (TMPA-2019)
null
10.13140/RG.2.2.35867.62243
null
cs.SE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Machine Learning (ML) has become a ubiquitous tool for predicting and classifying data and has found application in several problem domains, including Software Development (SD). This paper reviews the literature between 2000 and 2019 on the use the learning models that have been employed for programming effort estima...
[ { "created": "Thu, 23 Jan 2020 11:56:10 GMT", "version": "v1" } ]
2020-01-27
[ [ "Akinsanya", "Barakat. J.", "" ], [ "Araújo", "Luiz J. P.", "" ], [ "Charikova", "Mariia", "" ], [ "Gimaeva", "Susanna", "" ], [ "Grichshenko", "Alexandr", "" ], [ "Khan", "Adil", "" ], [ "Mazzara", "Manuel", ...
Machine Learning (ML) has become a ubiquitous tool for predicting and classifying data and has found application in several problem domains, including Software Development (SD). This paper reviews the literature between 2000 and 2019 on the use the learning models that have been employed for programming effort estimati...