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2207.11511
Ho Man Kwan
Ho Man Kwan and Shenghui Song
SSBNet: Improving Visual Recognition Efficiency by Adaptive Sampling
null
null
null
null
cs.CV cs.AI cs.LG
http://creativecommons.org/licenses/by/4.0/
Downsampling is widely adopted to achieve a good trade-off between accuracy and latency for visual recognition. Unfortunately, the commonly used pooling layers are not learned, and thus cannot preserve important information. As another dimension reduction method, adaptive sampling weights and processes regions that a...
[ { "created": "Sat, 23 Jul 2022 13:01:55 GMT", "version": "v1" } ]
2022-07-26
[ [ "Kwan", "Ho Man", "" ], [ "Song", "Shenghui", "" ] ]
Downsampling is widely adopted to achieve a good trade-off between accuracy and latency for visual recognition. Unfortunately, the commonly used pooling layers are not learned, and thus cannot preserve important information. As another dimension reduction method, adaptive sampling weights and processes regions that are...
2406.14979
Zihan Niu
Yuanjie Lyu, Zihan Niu, Zheyong Xie, Chao Zhang, Tong Xu, Yang Wang, Enhong Chen
Retrieve-Plan-Generation: An Iterative Planning and Answering Framework for Knowledge-Intensive LLM Generation
null
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Despite the significant progress of large language models (LLMs) in various tasks, they often produce factual errors due to their limited internal knowledge. Retrieval-Augmented Generation (RAG), which enhances LLMs with external knowledge sources, offers a promising solution. However, these methods can be misled by ...
[ { "created": "Fri, 21 Jun 2024 08:45:52 GMT", "version": "v1" } ]
2024-06-24
[ [ "Lyu", "Yuanjie", "" ], [ "Niu", "Zihan", "" ], [ "Xie", "Zheyong", "" ], [ "Zhang", "Chao", "" ], [ "Xu", "Tong", "" ], [ "Wang", "Yang", "" ], [ "Chen", "Enhong", "" ] ]
Despite the significant progress of large language models (LLMs) in various tasks, they often produce factual errors due to their limited internal knowledge. Retrieval-Augmented Generation (RAG), which enhances LLMs with external knowledge sources, offers a promising solution. However, these methods can be misled by ir...
1902.07420
Yitao Han
Yitao Han, Lingjie Duan, Rui Zhang
Jamming-assisted Eavesdropping over Parallel Fading Channels
null
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper advances the proactive eavesdropping research by considering a practical half-duplex mode for the legitimate monitor and dealing with the challenging case that the suspicious link opportunistically communicates over parallel fading channels. To increase eavesdropping success probability, we propose cogniti...
[ { "created": "Wed, 20 Feb 2019 05:51:30 GMT", "version": "v1" } ]
2019-02-21
[ [ "Han", "Yitao", "" ], [ "Duan", "Lingjie", "" ], [ "Zhang", "Rui", "" ] ]
This paper advances the proactive eavesdropping research by considering a practical half-duplex mode for the legitimate monitor and dealing with the challenging case that the suspicious link opportunistically communicates over parallel fading channels. To increase eavesdropping success probability, we propose cognitive...
2210.00960
Jiancong Xiao
Jiancong Xiao, Yanbo Fan, Ruoyu Sun, Jue Wang, Zhi-Quan Luo
Stability Analysis and Generalization Bounds of Adversarial Training
Published as a conference paper in NeurIPS2022
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In adversarial machine learning, deep neural networks can fit the adversarial examples on the training dataset but have poor generalization ability on the test set. This phenomenon is called robust overfitting, and it can be observed when adversarially training neural nets on common datasets, including SVHN, CIFAR-10...
[ { "created": "Mon, 3 Oct 2022 14:21:46 GMT", "version": "v1" }, { "created": "Mon, 31 Oct 2022 09:39:54 GMT", "version": "v2" } ]
2022-11-01
[ [ "Xiao", "Jiancong", "" ], [ "Fan", "Yanbo", "" ], [ "Sun", "Ruoyu", "" ], [ "Wang", "Jue", "" ], [ "Luo", "Zhi-Quan", "" ] ]
In adversarial machine learning, deep neural networks can fit the adversarial examples on the training dataset but have poor generalization ability on the test set. This phenomenon is called robust overfitting, and it can be observed when adversarially training neural nets on common datasets, including SVHN, CIFAR-10, ...
1806.00810
William Farmer
William M. Farmer
A New Style of Proof for Mathematics Organized as a Network of Axiomatic Theories
14 pages. This is a longer, revised version with a modified title
null
null
null
cs.LO math.LO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A theory graph is a network of axiomatic theories connected with meaning-preserving mappings called theory morphisms. Theory graphs are well suited for organizing large bodies of mathematical knowledge. Traditional and formal proofs do not adequately fulfill all the purposes that mathematical proofs have, and they do...
[ { "created": "Sun, 3 Jun 2018 15:18:01 GMT", "version": "v1" }, { "created": "Sat, 1 Dec 2018 12:25:07 GMT", "version": "v2" } ]
2018-12-04
[ [ "Farmer", "William M.", "" ] ]
A theory graph is a network of axiomatic theories connected with meaning-preserving mappings called theory morphisms. Theory graphs are well suited for organizing large bodies of mathematical knowledge. Traditional and formal proofs do not adequately fulfill all the purposes that mathematical proofs have, and they do n...
1206.6487
Csaba Szepesvari
Gabor Bartok (University of Alberta), Navid Zolghadr (University of Alberta), Csaba Szepesvari (University of Alberta)
An Adaptive Algorithm for Finite Stochastic Partial Monitoring
Appears in Proceedings of the 29th International Conference on Machine Learning (ICML 2012)
null
null
null
cs.LG cs.GT stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present a new anytime algorithm that achieves near-optimal regret for any instance of finite stochastic partial monitoring. In particular, the new algorithm achieves the minimax regret, within logarithmic factors, for both "easy" and "hard" problems. For easy problems, it additionally achieves logarithmic individu...
[ { "created": "Wed, 27 Jun 2012 19:59:59 GMT", "version": "v1" } ]
2012-07-03
[ [ "Bartok", "Gabor", "", "University of Alberta" ], [ "Zolghadr", "Navid", "", "University of\n Alberta" ], [ "Szepesvari", "Csaba", "", "University of Alberta" ] ]
We present a new anytime algorithm that achieves near-optimal regret for any instance of finite stochastic partial monitoring. In particular, the new algorithm achieves the minimax regret, within logarithmic factors, for both "easy" and "hard" problems. For easy problems, it additionally achieves logarithmic individual...
2204.04937
Piotr Gramacki
Krzysztof Rajda, {\L}ukasz Augustyniak, Piotr Gramacki, Marcin Gruza, Szymon Wo\'zniak, Tomasz Kajdanowicz
Assessment of Massively Multilingual Sentiment Classifiers
Accepted for WASSA at ACL 2022
null
null
null
cs.CL cs.LG
http://creativecommons.org/licenses/by-nc-sa/4.0/
Models are increasing in size and complexity in the hunt for SOTA. But what if those 2\% increase in performance does not make a difference in a production use case? Maybe benefits from a smaller, faster model outweigh those slight performance gains. Also, equally good performance across languages in multilingual tas...
[ { "created": "Mon, 11 Apr 2022 08:22:05 GMT", "version": "v1" } ]
2022-04-12
[ [ "Rajda", "Krzysztof", "" ], [ "Augustyniak", "Łukasz", "" ], [ "Gramacki", "Piotr", "" ], [ "Gruza", "Marcin", "" ], [ "Woźniak", "Szymon", "" ], [ "Kajdanowicz", "Tomasz", "" ] ]
Models are increasing in size and complexity in the hunt for SOTA. But what if those 2\% increase in performance does not make a difference in a production use case? Maybe benefits from a smaller, faster model outweigh those slight performance gains. Also, equally good performance across languages in multilingual tasks...
2209.02370
Quang Pham
Quang Pham, Chenghao Liu, Steven C. H. Hoi
Continual Learning, Fast and Slow
arXiv admin note: substantial text overlap with arXiv:2110.00175
null
null
null
cs.AI cs.CV cs.LG
http://creativecommons.org/licenses/by/4.0/
According to the Complementary Learning Systems (CLS) theory~\cite{mcclelland1995there} in neuroscience, humans do effective \emph{continual learning} through two complementary systems: a fast learning system centered on the hippocampus for rapid learning of the specifics, individual experiences; and a slow learning ...
[ { "created": "Tue, 6 Sep 2022 10:48:45 GMT", "version": "v1" }, { "created": "Wed, 26 Oct 2022 12:27:25 GMT", "version": "v2" }, { "created": "Sun, 9 Jul 2023 10:02:41 GMT", "version": "v3" } ]
2023-07-11
[ [ "Pham", "Quang", "" ], [ "Liu", "Chenghao", "" ], [ "Hoi", "Steven C. H.", "" ] ]
According to the Complementary Learning Systems (CLS) theory~\cite{mcclelland1995there} in neuroscience, humans do effective \emph{continual learning} through two complementary systems: a fast learning system centered on the hippocampus for rapid learning of the specifics, individual experiences; and a slow learning sy...
2002.11497
Sanghyun Hong
Sanghyun Hong, Varun Chandrasekaran, Yi\u{g}itcan Kaya, Tudor Dumitra\c{s}, Nicolas Papernot
On the Effectiveness of Mitigating Data Poisoning Attacks with Gradient Shaping
null
null
null
null
cs.CR cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Machine learning algorithms are vulnerable to data poisoning attacks. Prior taxonomies that focus on specific scenarios, e.g., indiscriminate or targeted, have enabled defenses for the corresponding subset of known attacks. Yet, this introduces an inevitable arms race between adversaries and defenders. In this work, ...
[ { "created": "Wed, 26 Feb 2020 14:04:16 GMT", "version": "v1" }, { "created": "Thu, 27 Feb 2020 19:00:01 GMT", "version": "v2" } ]
2020-03-02
[ [ "Hong", "Sanghyun", "" ], [ "Chandrasekaran", "Varun", "" ], [ "Kaya", "Yiğitcan", "" ], [ "Dumitraş", "Tudor", "" ], [ "Papernot", "Nicolas", "" ] ]
Machine learning algorithms are vulnerable to data poisoning attacks. Prior taxonomies that focus on specific scenarios, e.g., indiscriminate or targeted, have enabled defenses for the corresponding subset of known attacks. Yet, this introduces an inevitable arms race between adversaries and defenders. In this work, we...
1703.09400
Naeemul Hassan
Md Main Uddin Rony, Naeemul Hassan, Mohammad Yousuf
Diving Deep into Clickbaits: Who Use Them to What Extents in Which Topics with What Effects?
null
null
null
null
cs.SI cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The use of alluring headlines (clickbait) to tempt the readers has become a growing practice nowadays. For the sake of existence in the highly competitive media industry, most of the on-line media including the mainstream ones, have started following this practice. Although the wide-spread practice of clickbait makes...
[ { "created": "Tue, 28 Mar 2017 05:07:38 GMT", "version": "v1" } ]
2017-03-29
[ [ "Rony", "Md Main Uddin", "" ], [ "Hassan", "Naeemul", "" ], [ "Yousuf", "Mohammad", "" ] ]
The use of alluring headlines (clickbait) to tempt the readers has become a growing practice nowadays. For the sake of existence in the highly competitive media industry, most of the on-line media including the mainstream ones, have started following this practice. Although the wide-spread practice of clickbait makes t...
2405.14977
Robert Alexander Marsden
Mario D\"obler, Robert A. Marsden, Tobias Raichle, Bin Yang
A Lost Opportunity for Vision-Language Models: A Comparative Study of Online Test-time Adaptation for Vision-Language Models
Accepted at CVPR 2024 MAT Workshop Community Track
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In the realm of deep learning, maintaining model robustness against distribution shifts is critical. This paper investigates test-time adaptation strategies for vision-language models, with a specific focus on CLIP and its variants. Through a systematic exploration of prompt-based techniques and existing test-time ad...
[ { "created": "Thu, 23 May 2024 18:27:07 GMT", "version": "v1" } ]
2024-05-27
[ [ "Döbler", "Mario", "" ], [ "Marsden", "Robert A.", "" ], [ "Raichle", "Tobias", "" ], [ "Yang", "Bin", "" ] ]
In the realm of deep learning, maintaining model robustness against distribution shifts is critical. This paper investigates test-time adaptation strategies for vision-language models, with a specific focus on CLIP and its variants. Through a systematic exploration of prompt-based techniques and existing test-time adap...
1712.00368
Adrien Lagrange
Adrien Lagrange, Mathieu Fauvel, St\'ephane May and Nicolas Dobigeon
Hierarchical Bayesian image analysis: from low-level modeling to robust supervised learning
null
null
null
null
cs.CV stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Within a supervised classification framework, labeled data are used to learn classifier parameters. Prior to that, it is generally required to perform dimensionality reduction via feature extraction. These preprocessing steps have motivated numerous research works aiming at recovering latent variables in an unsupervi...
[ { "created": "Fri, 1 Dec 2017 15:32:58 GMT", "version": "v1" } ]
2017-12-04
[ [ "Lagrange", "Adrien", "" ], [ "Fauvel", "Mathieu", "" ], [ "May", "Stéphane", "" ], [ "Dobigeon", "Nicolas", "" ] ]
Within a supervised classification framework, labeled data are used to learn classifier parameters. Prior to that, it is generally required to perform dimensionality reduction via feature extraction. These preprocessing steps have motivated numerous research works aiming at recovering latent variables in an unsupervise...
0710.3779
Sumanth Gangasani
Sumanth Kumar Reddy Gangasani
Testing D-Sequences for their Randomness
8 pages, 5 figures
null
null
null
cs.CR
null
This paper examines the randomness of d-sequences, which are decimal sequences to an arbitrary base. Our motivation is to check their suitability for application to cryptography, spread-spectrum systems and use as pseudorandom sequence.
[ { "created": "Fri, 19 Oct 2007 20:18:42 GMT", "version": "v1" } ]
2007-10-23
[ [ "Gangasani", "Sumanth Kumar Reddy", "" ] ]
This paper examines the randomness of d-sequences, which are decimal sequences to an arbitrary base. Our motivation is to check their suitability for application to cryptography, spread-spectrum systems and use as pseudorandom sequence.
1409.3696
Peter Bezd\u{e}k
Peter Bezd\v{e}k and Nikola Bene\v{s} and Ji\v{r}\'i Barnat and Ivana \v{C}ern\'a
LTL Parameter Synthesis of Parametric Timed Automata
23 pages, extended version
null
null
null
cs.FL cs.LO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The parameter synthesis problem for parametric timed automata is undecidable in general even for very simple reachability properties. In this paper we introduce restrictions on parameter valuations under which the parameter synthesis problem is decidable for LTL properties. The investigated bounded integer parameter ...
[ { "created": "Fri, 12 Sep 2014 10:53:32 GMT", "version": "v1" }, { "created": "Fri, 4 Mar 2016 17:03:49 GMT", "version": "v2" } ]
2016-03-07
[ [ "Bezděk", "Peter", "" ], [ "Beneš", "Nikola", "" ], [ "Barnat", "Jiří", "" ], [ "Černá", "Ivana", "" ] ]
The parameter synthesis problem for parametric timed automata is undecidable in general even for very simple reachability properties. In this paper we introduce restrictions on parameter valuations under which the parameter synthesis problem is decidable for LTL properties. The investigated bounded integer parameter sy...
2009.01465
Damla Cay
Damla \c{C}ay, Till Nagel, As{\i}m Evren Yanta\c{c}
Understanding User Experience of COVID-19 Maps through Remote Elicitation Interviews
null
null
null
null
cs.HC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
During the coronavirus pandemic, visualizations gained a new level of popularity and meaning for a wider audience. People were bombarded with a wide set of public health visualizations ranging from simple graphs to complex interactive dashboards. In a pandemic setting, where large amounts of the world population are ...
[ { "created": "Thu, 3 Sep 2020 06:12:09 GMT", "version": "v1" } ]
2020-09-04
[ [ "Çay", "Damla", "" ], [ "Nagel", "Till", "" ], [ "Yantaç", "Asım Evren", "" ] ]
During the coronavirus pandemic, visualizations gained a new level of popularity and meaning for a wider audience. People were bombarded with a wide set of public health visualizations ranging from simple graphs to complex interactive dashboards. In a pandemic setting, where large amounts of the world population are so...
1401.3476
Piero A. Bonatti
Piero A. Bonatti, Carsten Lutz, Frank Wolter
The Complexity of Circumscription in DLs
null
Journal Of Artificial Intelligence Research, Volume 35, pages 717-773, 2009
10.1613/jair.2763
null
cs.LO cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
As fragments of first-order logic, Description logics (DLs) do not provide nonmonotonic features such as defeasible inheritance and default rules. Since many applications would benefit from the availability of such features, several families of nonmonotonic DLs have been developed that are mostly based on default log...
[ { "created": "Wed, 15 Jan 2014 05:32:08 GMT", "version": "v1" } ]
2014-01-16
[ [ "Bonatti", "Piero A.", "" ], [ "Lutz", "Carsten", "" ], [ "Wolter", "Frank", "" ] ]
As fragments of first-order logic, Description logics (DLs) do not provide nonmonotonic features such as defeasible inheritance and default rules. Since many applications would benefit from the availability of such features, several families of nonmonotonic DLs have been developed that are mostly based on default logic...
1907.00719
Sun Chunlong
Junyong Eom, Manabu Machida, Gen Nakamura, Goro Nishimura, and Chunlong Sun
Expression of the peak time for time-domain boundary measurements in diffuse light
null
null
null
null
cs.CE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Light propagation through diffusive media can be described by the diffusion equation in a space-time domain. Further, fluorescence can be described by a system of coupled diffusion equations. This paper analyzes time-domain measurements, which measure the temporal point-spread function (TPSF), at a boundary of such d...
[ { "created": "Thu, 27 Jun 2019 04:03:54 GMT", "version": "v1" }, { "created": "Wed, 8 Dec 2021 04:39:04 GMT", "version": "v2" } ]
2021-12-09
[ [ "Eom", "Junyong", "" ], [ "Machida", "Manabu", "" ], [ "Nakamura", "Gen", "" ], [ "Nishimura", "Goro", "" ], [ "Sun", "Chunlong", "" ] ]
Light propagation through diffusive media can be described by the diffusion equation in a space-time domain. Further, fluorescence can be described by a system of coupled diffusion equations. This paper analyzes time-domain measurements, which measure the temporal point-spread function (TPSF), at a boundary of such dif...
1909.03934
Jan Karwowski
Jan Karwowski and Jacek Ma\'ndziuk
Double-oracle sampling method for Stackelberg Equilibrium approximation in general-sum extensive-form games
null
Thirty-Fourth AAAI Conference on Artificial Intelligence, AAAI 2020, 2054-2061
10.1609/aaai.v34i02.5578
null
cs.GT cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The paper presents a new method for approximating Strong Stackelberg Equilibrium in general-sum sequential games with imperfect information and perfect recall. The proposed approach is generic as it does not rely on any specific properties of a particular game model. The method is based on iterative interleaving of t...
[ { "created": "Mon, 9 Sep 2019 15:34:04 GMT", "version": "v1" } ]
2022-08-16
[ [ "Karwowski", "Jan", "" ], [ "Mańdziuk", "Jacek", "" ] ]
The paper presents a new method for approximating Strong Stackelberg Equilibrium in general-sum sequential games with imperfect information and perfect recall. The proposed approach is generic as it does not rely on any specific properties of a particular game model. The method is based on iterative interleaving of the...
2204.11337
Anastassia Kornilova
Anastassia Kornilova, Daniel Argyle, Vladimir Eidelman
An Item Response Theory Framework for Persuasion
null
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we apply Item Response Theory, popular in education and political science research, to the analysis of argument persuasiveness in language. We empirically evaluate the model's performance on three datasets, including a novel dataset in the area of political advocacy. We show the advantages of separatin...
[ { "created": "Sun, 24 Apr 2022 19:14:11 GMT", "version": "v1" } ]
2022-04-26
[ [ "Kornilova", "Anastassia", "" ], [ "Argyle", "Daniel", "" ], [ "Eidelman", "Vladimir", "" ] ]
In this paper, we apply Item Response Theory, popular in education and political science research, to the analysis of argument persuasiveness in language. We empirically evaluate the model's performance on three datasets, including a novel dataset in the area of political advocacy. We show the advantages of separating ...
2306.11719
Ayush Tewari
Ayush Tewari, Tianwei Yin, George Cazenavette, Semon Rezchikov, Joshua B. Tenenbaum, Fr\'edo Durand, William T. Freeman, Vincent Sitzmann
Diffusion with Forward Models: Solving Stochastic Inverse Problems Without Direct Supervision
Project page: https://diffusion-with-forward-models.github.io/
null
null
null
cs.CV cs.GR cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Denoising diffusion models are a powerful type of generative models used to capture complex distributions of real-world signals. However, their applicability is limited to scenarios where training samples are readily available, which is not always the case in real-world applications. For example, in inverse graphics,...
[ { "created": "Tue, 20 Jun 2023 17:53:00 GMT", "version": "v1" }, { "created": "Fri, 17 Nov 2023 04:17:34 GMT", "version": "v2" } ]
2023-11-20
[ [ "Tewari", "Ayush", "" ], [ "Yin", "Tianwei", "" ], [ "Cazenavette", "George", "" ], [ "Rezchikov", "Semon", "" ], [ "Tenenbaum", "Joshua B.", "" ], [ "Durand", "Frédo", "" ], [ "Freeman", "William T.", "" ...
Denoising diffusion models are a powerful type of generative models used to capture complex distributions of real-world signals. However, their applicability is limited to scenarios where training samples are readily available, which is not always the case in real-world applications. For example, in inverse graphics, t...
2011.08130
Thomas Zimmermann
Paige Rodeghero, Thomas Zimmermann, Brian Houck, Denae Ford
Please Turn Your Cameras On: Remote Onboarding of Software Developers during a Pandemic
10 pages. Final version of the paper accepted at ICSE 2021 in the SEIP track
null
null
null
cs.SE cs.HC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The COVID-19 pandemic has impacted the way that software development teams onboard new hires. Previously, most software developers worked in physical offices and new hires onboarded to their teams in the physical office, following a standard onboarding process. However, when companies transitioned employees to work f...
[ { "created": "Mon, 16 Nov 2020 17:52:03 GMT", "version": "v1" }, { "created": "Sun, 7 Mar 2021 03:33:28 GMT", "version": "v2" } ]
2021-03-09
[ [ "Rodeghero", "Paige", "" ], [ "Zimmermann", "Thomas", "" ], [ "Houck", "Brian", "" ], [ "Ford", "Denae", "" ] ]
The COVID-19 pandemic has impacted the way that software development teams onboard new hires. Previously, most software developers worked in physical offices and new hires onboarded to their teams in the physical office, following a standard onboarding process. However, when companies transitioned employees to work fro...
2109.01727
Yiqing Hua
Yiqing Hua, Armin Namavari, Kaishuo Cheng, Mor Naaman, Thomas Ristenpart
Increasing Adversarial Uncertainty to Scale Private Similarity Testing
null
null
null
null
cs.CR
http://creativecommons.org/licenses/by/4.0/
Social media and other platforms rely on automated detection of abusive content to help combat disinformation, harassment, and abuse. One common approach is to check user content for similarity against a server-side database of problematic items. However, this method fundamentally endangers user privacy. Instead, we ...
[ { "created": "Fri, 3 Sep 2021 20:54:34 GMT", "version": "v1" }, { "created": "Tue, 7 Sep 2021 19:54:51 GMT", "version": "v2" }, { "created": "Wed, 29 Sep 2021 22:02:14 GMT", "version": "v3" }, { "created": "Mon, 4 Oct 2021 20:14:17 GMT", "version": "v4" } ]
2021-10-06
[ [ "Hua", "Yiqing", "" ], [ "Namavari", "Armin", "" ], [ "Cheng", "Kaishuo", "" ], [ "Naaman", "Mor", "" ], [ "Ristenpart", "Thomas", "" ] ]
Social media and other platforms rely on automated detection of abusive content to help combat disinformation, harassment, and abuse. One common approach is to check user content for similarity against a server-side database of problematic items. However, this method fundamentally endangers user privacy. Instead, we ta...
2104.09993
Lo\"ic J\'ez\'equel
Loic Jezequel, Ngoc-Son Vu, Jean Beaudet, Aymeric Histace
Fine-grained Anomaly Detection via Multi-task Self-Supervision
null
L. J\'ez\'equel, N. -S. Vu, J. Beaudet and A. Histace, "Fine-grained anomaly detection via multi-task self-supervision," 2021 17th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), 2021, pp. 1-8
10.1109/AVSS52988.2021.9663783
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Detecting anomalies using deep learning has become a major challenge over the last years, and is becoming increasingly promising in several fields. The introduction of self-supervised learning has greatly helped many methods including anomaly detection where simple geometric transformation recognition tasks are used....
[ { "created": "Tue, 20 Apr 2021 14:19:08 GMT", "version": "v1" }, { "created": "Thu, 17 Mar 2022 09:53:56 GMT", "version": "v2" } ]
2022-03-18
[ [ "Jezequel", "Loic", "" ], [ "Vu", "Ngoc-Son", "" ], [ "Beaudet", "Jean", "" ], [ "Histace", "Aymeric", "" ] ]
Detecting anomalies using deep learning has become a major challenge over the last years, and is becoming increasingly promising in several fields. The introduction of self-supervised learning has greatly helped many methods including anomaly detection where simple geometric transformation recognition tasks are used. H...
2401.15865
Sifan Zhou
Sifan Zhou, Liang Li, Xinyu Zhang, Bo Zhang, Shipeng Bai, Miao Sun, Ziyu Zhao, Xiaobo Lu, Xiangxiang Chu
LiDAR-PTQ: Post-Training Quantization for Point Cloud 3D Object Detection
Accepted in ICLR 2024
null
null
null
cs.CV
http://creativecommons.org/licenses/by-nc-sa/4.0/
Due to highly constrained computing power and memory, deploying 3D lidar-based detectors on edge devices equipped in autonomous vehicles and robots poses a crucial challenge. Being a convenient and straightforward model compression approach, Post-Training Quantization (PTQ) has been widely adopted in 2D vision tasks....
[ { "created": "Mon, 29 Jan 2024 03:35:55 GMT", "version": "v1" } ]
2024-01-30
[ [ "Zhou", "Sifan", "" ], [ "Li", "Liang", "" ], [ "Zhang", "Xinyu", "" ], [ "Zhang", "Bo", "" ], [ "Bai", "Shipeng", "" ], [ "Sun", "Miao", "" ], [ "Zhao", "Ziyu", "" ], [ "Lu", "Xiaobo", "" ...
Due to highly constrained computing power and memory, deploying 3D lidar-based detectors on edge devices equipped in autonomous vehicles and robots poses a crucial challenge. Being a convenient and straightforward model compression approach, Post-Training Quantization (PTQ) has been widely adopted in 2D vision tasks. H...
2401.02582
Daoan Zhang
Daoan Zhang, Junming Yang, Hanjia Lyu, Zijian Jin, Yuan Yao, Mingkai Chen, Jiebo Luo
CoCoT: Contrastive Chain-of-Thought Prompting for Large Multimodal Models with Multiple Image Inputs
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
When exploring the development of Artificial General Intelligence (AGI), a critical task for these models involves interpreting and processing information from multiple image inputs. However, Large Multimodal Models (LMMs) encounter two issues in such scenarios: (1) a lack of fine-grained perception, and (2) a tenden...
[ { "created": "Fri, 5 Jan 2024 00:26:07 GMT", "version": "v1" } ]
2024-01-08
[ [ "Zhang", "Daoan", "" ], [ "Yang", "Junming", "" ], [ "Lyu", "Hanjia", "" ], [ "Jin", "Zijian", "" ], [ "Yao", "Yuan", "" ], [ "Chen", "Mingkai", "" ], [ "Luo", "Jiebo", "" ] ]
When exploring the development of Artificial General Intelligence (AGI), a critical task for these models involves interpreting and processing information from multiple image inputs. However, Large Multimodal Models (LMMs) encounter two issues in such scenarios: (1) a lack of fine-grained perception, and (2) a tendency...
1704.04205
Maxim Buzdalov
Margarita Markina and Maxim Buzdalov
Hybridizing Non-dominated Sorting Algorithms: Divide-and-Conquer Meets Best Order Sort
A two-page abstract of this paper will appear in the proceedings companion of the 2017 Genetic and Evolutionary Computation Conference (GECCO 2017)
null
10.1145/3067695.3076074
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Many production-grade algorithms benefit from combining an asymptotically efficient algorithm for solving big problem instances, by splitting them into smaller ones, and an asymptotically inefficient algorithm with a very small implementation constant for solving small subproblems. A well-known example is stable sort...
[ { "created": "Thu, 13 Apr 2017 16:36:44 GMT", "version": "v1" } ]
2017-04-14
[ [ "Markina", "Margarita", "" ], [ "Buzdalov", "Maxim", "" ] ]
Many production-grade algorithms benefit from combining an asymptotically efficient algorithm for solving big problem instances, by splitting them into smaller ones, and an asymptotically inefficient algorithm with a very small implementation constant for solving small subproblems. A well-known example is stable sortin...
2402.06782
Akbir M Khan Mr
Akbir Khan, John Hughes, Dan Valentine, Laura Ruis, Kshitij Sachan, Ansh Radhakrishnan, Edward Grefenstette, Samuel R. Bowman, Tim Rockt\"aschel and Ethan Perez
Debating with More Persuasive LLMs Leads to More Truthful Answers
For code please check: https://github.com/ucl-dark/llm_debate
null
null
null
cs.AI cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Common methods for aligning large language models (LLMs) with desired behaviour heavily rely on human-labelled data. However, as models grow increasingly sophisticated, they will surpass human expertise, and the role of human evaluation will evolve into non-experts overseeing experts. In anticipation of this, we ask:...
[ { "created": "Fri, 9 Feb 2024 21:05:01 GMT", "version": "v1" }, { "created": "Thu, 15 Feb 2024 22:09:52 GMT", "version": "v2" }, { "created": "Thu, 30 May 2024 13:59:34 GMT", "version": "v3" }, { "created": "Thu, 25 Jul 2024 23:32:21 GMT", "version": "v4" } ]
2024-07-29
[ [ "Khan", "Akbir", "" ], [ "Hughes", "John", "" ], [ "Valentine", "Dan", "" ], [ "Ruis", "Laura", "" ], [ "Sachan", "Kshitij", "" ], [ "Radhakrishnan", "Ansh", "" ], [ "Grefenstette", "Edward", "" ], [ ...
Common methods for aligning large language models (LLMs) with desired behaviour heavily rely on human-labelled data. However, as models grow increasingly sophisticated, they will surpass human expertise, and the role of human evaluation will evolve into non-experts overseeing experts. In anticipation of this, we ask: c...
2011.03841
Jean Pablo Vieira de Mello
Jean Pablo Vieira de Mello, Lucas Tabelini, Rodrigo F. Berriel, Thiago M. Paix\~ao, Alberto F. de Souza, Claudine Badue, Nicu Sebe, Thiago Oliveira-Santos
Deep traffic light detection by overlaying synthetic context on arbitrary natural images
null
Computers & Graphics (2020)
10.1016/j.cag.2020.09.012
null
cs.CV
http://creativecommons.org/licenses/by-nc-nd/4.0/
Deep neural networks come as an effective solution to many problems associated with autonomous driving. By providing real image samples with traffic context to the network, the model learns to detect and classify elements of interest, such as pedestrians, traffic signs, and traffic lights. However, acquiring and anno...
[ { "created": "Sat, 7 Nov 2020 19:57:22 GMT", "version": "v1" }, { "created": "Tue, 10 Nov 2020 02:30:51 GMT", "version": "v2" }, { "created": "Thu, 10 Dec 2020 22:44:41 GMT", "version": "v3" } ]
2020-12-14
[ [ "de Mello", "Jean Pablo Vieira", "" ], [ "Tabelini", "Lucas", "" ], [ "Berriel", "Rodrigo F.", "" ], [ "Paixão", "Thiago M.", "" ], [ "de Souza", "Alberto F.", "" ], [ "Badue", "Claudine", "" ], [ "Sebe", "Nicu...
Deep neural networks come as an effective solution to many problems associated with autonomous driving. By providing real image samples with traffic context to the network, the model learns to detect and classify elements of interest, such as pedestrians, traffic signs, and traffic lights. However, acquiring and annota...
2309.15417
Tobias Weinzierl
Peter Noble, Tobias Weinzierl
Parallel local time stepping for rigid bodies represented by triangulated meshes
null
null
null
null
cs.MS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Discrete Element Methods (DEM), i.e.~the simulation of many rigid particles, suffer from very stiff differential equations plus multiscale challenges in space and time. The particles move smoothly through space until they interact almost instantaneously due to collisions. Dense particle packings hence require tiny ti...
[ { "created": "Wed, 27 Sep 2023 05:46:57 GMT", "version": "v1" } ]
2023-09-28
[ [ "Noble", "Peter", "" ], [ "Weinzierl", "Tobias", "" ] ]
Discrete Element Methods (DEM), i.e.~the simulation of many rigid particles, suffer from very stiff differential equations plus multiscale challenges in space and time. The particles move smoothly through space until they interact almost instantaneously due to collisions. Dense particle packings hence require tiny time...
2404.09593
Zepeng Ding
Zepeng Ding, Wenhao Huang, Jiaqing Liang, Deqing Yang, Yanghua Xiao
Improving Recall of Large Language Models: A Model Collaboration Approach for Relational Triple Extraction
Accepted at LREC-COLING 2024 main conference
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Relation triple extraction, which outputs a set of triples from long sentences, plays a vital role in knowledge acquisition. Large language models can accurately extract triples from simple sentences through few-shot learning or fine-tuning when given appropriate instructions. However, they often miss out when extrac...
[ { "created": "Mon, 15 Apr 2024 09:03:05 GMT", "version": "v1" } ]
2024-04-16
[ [ "Ding", "Zepeng", "" ], [ "Huang", "Wenhao", "" ], [ "Liang", "Jiaqing", "" ], [ "Yang", "Deqing", "" ], [ "Xiao", "Yanghua", "" ] ]
Relation triple extraction, which outputs a set of triples from long sentences, plays a vital role in knowledge acquisition. Large language models can accurately extract triples from simple sentences through few-shot learning or fine-tuning when given appropriate instructions. However, they often miss out when extracti...
1711.06837
Iqbal H. Sarker
Iqbal H. Sarker, Muhammad Ashad Kabir, Alan Colman, Jun Han
Identifying Recent Behavioral Data Length in Mobile Phone Log
14th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services (MobiQuitous 2017), Melbourne, Australia
null
null
null
cs.CY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Mobile phone log data (e.g., phone call log) is not static as it is progressively added to day-by-day according to individ- ual's diverse behaviors with mobile phones. Since human behavior changes over time, the most recent pattern is more interesting and significant than older ones for predicting in- dividual's beha...
[ { "created": "Sat, 18 Nov 2017 10:10:51 GMT", "version": "v1" }, { "created": "Mon, 18 Dec 2017 06:32:43 GMT", "version": "v2" } ]
2017-12-19
[ [ "Sarker", "Iqbal H.", "" ], [ "Kabir", "Muhammad Ashad", "" ], [ "Colman", "Alan", "" ], [ "Han", "Jun", "" ] ]
Mobile phone log data (e.g., phone call log) is not static as it is progressively added to day-by-day according to individ- ual's diverse behaviors with mobile phones. Since human behavior changes over time, the most recent pattern is more interesting and significant than older ones for predicting in- dividual's behavi...
2209.15029
Richard Brath
Richard Brath
Multimodal analogs to infer humanities visualization requirements
6 pages, 11 figures. Visualization for Digital Humanities 2022
null
null
null
cs.HC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Gaps and requirements for multi-modal interfaces for humanities can be explored by observing the configuration of real-world environments and the tasks of visitors within them compared to digital environments. Examples include stores, museums, galleries, and stages with tasks similar to visualization tasks such as ov...
[ { "created": "Thu, 29 Sep 2022 18:09:16 GMT", "version": "v1" } ]
2022-10-03
[ [ "Brath", "Richard", "" ] ]
Gaps and requirements for multi-modal interfaces for humanities can be explored by observing the configuration of real-world environments and the tasks of visitors within them compared to digital environments. Examples include stores, museums, galleries, and stages with tasks similar to visualization tasks such as over...
2301.09567
Mathieu Marquis Bolduc
Mathieu Marquis Bolduc, Hau Nghiep Phan
Rig Inversion by Training a Differentiable Rig Function
Presented at Siggraph Asia '22 in Daegu, South Korea
SA '22: SIGGRAPH Asia 2022 Technical Communications, December 2022, Article No.: 15
10.1145/3550340.3564218
null
cs.GR cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Rig inversion is the problem of creating a method that can find the rig parameter vector that best approximates a given input mesh. In this paper we propose to solve this problem by first obtaining a differentiable rig function by training a multi layer perceptron to approximate the rig function. This differentiable ...
[ { "created": "Wed, 11 Jan 2023 20:21:58 GMT", "version": "v1" } ]
2023-01-24
[ [ "Bolduc", "Mathieu Marquis", "" ], [ "Phan", "Hau Nghiep", "" ] ]
Rig inversion is the problem of creating a method that can find the rig parameter vector that best approximates a given input mesh. In this paper we propose to solve this problem by first obtaining a differentiable rig function by training a multi layer perceptron to approximate the rig function. This differentiable ri...
2407.09984
Yu Zhang
Yu Zhang, Haoyu Zhang, Yongxiang Zou, Houcheng Li and Long Cheng
Stabilizing Dynamic Systems through Neural Network Learning: A Robust Approach
arXiv admin note: text overlap with arXiv:2309.08849
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Point-to-point and periodic motions are ubiquitous in the world of robotics. To master these motions, Autonomous Dynamic System (DS) based algorithms are fundamental in the domain of Learning from Demonstration (LfD). However, these algorithms face the significant challenge of balancing precision in learning with the...
[ { "created": "Sat, 13 Jul 2024 19:13:43 GMT", "version": "v1" } ]
2024-07-16
[ [ "Zhang", "Yu", "" ], [ "Zhang", "Haoyu", "" ], [ "Zou", "Yongxiang", "" ], [ "Li", "Houcheng", "" ], [ "Cheng", "Long", "" ] ]
Point-to-point and periodic motions are ubiquitous in the world of robotics. To master these motions, Autonomous Dynamic System (DS) based algorithms are fundamental in the domain of Learning from Demonstration (LfD). However, these algorithms face the significant challenge of balancing precision in learning with the m...
2102.09009
Louis Tiao
Louis C. Tiao, Aaron Klein, Matthias Seeger, Edwin V. Bonilla, Cedric Archambeau, Fabio Ramos
BORE: Bayesian Optimization by Density-Ratio Estimation
preprint, under review
null
null
null
cs.LG stat.ML
http://creativecommons.org/licenses/by/4.0/
Bayesian optimization (BO) is among the most effective and widely-used blackbox optimization methods. BO proposes solutions according to an explore-exploit trade-off criterion encoded in an acquisition function, many of which are computed from the posterior predictive of a probabilistic surrogate model. Prevalent amo...
[ { "created": "Wed, 17 Feb 2021 20:04:11 GMT", "version": "v1" } ]
2021-02-19
[ [ "Tiao", "Louis C.", "" ], [ "Klein", "Aaron", "" ], [ "Seeger", "Matthias", "" ], [ "Bonilla", "Edwin V.", "" ], [ "Archambeau", "Cedric", "" ], [ "Ramos", "Fabio", "" ] ]
Bayesian optimization (BO) is among the most effective and widely-used blackbox optimization methods. BO proposes solutions according to an explore-exploit trade-off criterion encoded in an acquisition function, many of which are computed from the posterior predictive of a probabilistic surrogate model. Prevalent among...
1611.01761
Konstantin Turitsyn
Petr Vorobev, Po-Hsu Huang, Mohamed Al Hosani, James L. Kirtley, Konstantin Turitsyn
High-Fidelity Model Order Reduction for Microgrids Stability Assessment
null
null
null
null
cs.SY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Proper modeling of inverter-based microgrids is crucial for accurate assessment of stability boundaries. It has been recently realized that the stability conditions for such microgrids are significantly different from those known for large- scale power systems. While detailed models are available, they are both compu...
[ { "created": "Sun, 6 Nov 2016 11:50:06 GMT", "version": "v1" } ]
2016-11-08
[ [ "Vorobev", "Petr", "" ], [ "Huang", "Po-Hsu", "" ], [ "Hosani", "Mohamed Al", "" ], [ "Kirtley", "James L.", "" ], [ "Turitsyn", "Konstantin", "" ] ]
Proper modeling of inverter-based microgrids is crucial for accurate assessment of stability boundaries. It has been recently realized that the stability conditions for such microgrids are significantly different from those known for large- scale power systems. While detailed models are available, they are both computa...
1202.5482
Richard McClatchey
Hanene Boussi Rahmouni, Kamran Munir, Mohammed Odeh and Richard McClatchey
Risk-Driven Compliant Access Controls for Clouds
9 pages, 3 figures. International Arab Conference on Information Technology (ACIT 2011) / Riyadh, Saudi Arabia. December 2012
null
null
null
cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
There is widespread agreement that cloud computing have proven cost cutting and agility benefits. However, security and regulatory compliance issues are continuing to challenge the wide acceptance of such technology both from social and commercial stakeholders. An important facture behind this is the fact that clouds...
[ { "created": "Fri, 24 Feb 2012 15:49:39 GMT", "version": "v1" }, { "created": "Tue, 13 Nov 2012 08:55:44 GMT", "version": "v2" } ]
2012-11-14
[ [ "Rahmouni", "Hanene Boussi", "" ], [ "Munir", "Kamran", "" ], [ "Odeh", "Mohammed", "" ], [ "McClatchey", "Richard", "" ] ]
There is widespread agreement that cloud computing have proven cost cutting and agility benefits. However, security and regulatory compliance issues are continuing to challenge the wide acceptance of such technology both from social and commercial stakeholders. An important facture behind this is the fact that clouds a...
2109.04954
Gobinda Saha
Gobinda Saha and Kaushik Roy
Saliency Guided Experience Packing for Replay in Continual Learning
To appear in IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) 2023
null
null
null
cs.LG cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Artificial learning systems aspire to mimic human intelligence by continually learning from a stream of tasks without forgetting past knowledge. One way to enable such learning is to store past experiences in the form of input examples in episodic memory and replay them when learning new tasks. However, performance o...
[ { "created": "Fri, 10 Sep 2021 15:54:58 GMT", "version": "v1" }, { "created": "Wed, 12 Oct 2022 05:17:55 GMT", "version": "v2" } ]
2022-10-13
[ [ "Saha", "Gobinda", "" ], [ "Roy", "Kaushik", "" ] ]
Artificial learning systems aspire to mimic human intelligence by continually learning from a stream of tasks without forgetting past knowledge. One way to enable such learning is to store past experiences in the form of input examples in episodic memory and replay them when learning new tasks. However, performance of ...
1506.08907
Sidharth Kashyap N
Sidharth N. Kashyap, Ade J. Fewings, Jay Davies, Ian Morris, Andrew Thomas Thomas Green, Martyn F. Guest
Big Data at HPC Wales
Accepted for publication at the 'Big Data Analytics Workshop' - 2014 http://web.ornl.gov/sci/knowledgediscovery/CloudComputing/PDAC-SC14/BDAC-14-Agenda.htm
null
null
null
cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper describes an automated approach to handling Big Data workloads on HPC systems. We describe a solution that dynamically creates a unified cluster based on YARN in an HPC Environment, without the need to configure and allocate a dedicated Hadoop cluster. The end user can choose to write the solution in any c...
[ { "created": "Tue, 30 Jun 2015 00:18:11 GMT", "version": "v1" } ]
2015-07-01
[ [ "Kashyap", "Sidharth N.", "" ], [ "Fewings", "Ade J.", "" ], [ "Davies", "Jay", "" ], [ "Morris", "Ian", "" ], [ "Green", "Andrew Thomas Thomas", "" ], [ "Guest", "Martyn F.", "" ] ]
This paper describes an automated approach to handling Big Data workloads on HPC systems. We describe a solution that dynamically creates a unified cluster based on YARN in an HPC Environment, without the need to configure and allocate a dedicated Hadoop cluster. The end user can choose to write the solution in any com...
2205.11710
Davide Modolo
Michael Dorkenwald, Fanyi Xiao, Biagio Brattoli, Joseph Tighe, Davide Modolo
SCVRL: Shuffled Contrastive Video Representation Learning
CVPR 2022 - L3DIVU workshop
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We propose SCVRL, a novel contrastive-based framework for self-supervised learning for videos. Differently from previous contrast learning based methods that mostly focus on learning visual semantics (e.g., CVRL), SCVRL is capable of learning both semantic and motion patterns. For that, we reformulate the popular shu...
[ { "created": "Tue, 24 May 2022 01:24:47 GMT", "version": "v1" } ]
2022-05-25
[ [ "Dorkenwald", "Michael", "" ], [ "Xiao", "Fanyi", "" ], [ "Brattoli", "Biagio", "" ], [ "Tighe", "Joseph", "" ], [ "Modolo", "Davide", "" ] ]
We propose SCVRL, a novel contrastive-based framework for self-supervised learning for videos. Differently from previous contrast learning based methods that mostly focus on learning visual semantics (e.g., CVRL), SCVRL is capable of learning both semantic and motion patterns. For that, we reformulate the popular shuff...
2406.05815
Yinan Huang
Yinan Huang, Siqi Miao, Pan Li
What Can We Learn from State Space Models for Machine Learning on Graphs?
null
null
null
null
cs.LG
http://creativecommons.org/licenses/by/4.0/
Machine learning on graphs has recently found extensive applications across domains. However, the commonly used Message Passing Neural Networks (MPNNs) suffer from limited expressive power and struggle to capture long-range dependencies. Graph transformers offer a strong alternative due to their global attention mech...
[ { "created": "Sun, 9 Jun 2024 15:03:36 GMT", "version": "v1" } ]
2024-06-11
[ [ "Huang", "Yinan", "" ], [ "Miao", "Siqi", "" ], [ "Li", "Pan", "" ] ]
Machine learning on graphs has recently found extensive applications across domains. However, the commonly used Message Passing Neural Networks (MPNNs) suffer from limited expressive power and struggle to capture long-range dependencies. Graph transformers offer a strong alternative due to their global attention mechan...
1807.01748
Pablo Fernandez Carmona
Pablo Fernandez Carmona, Michael Eichin, Alexandre Mayor, Harald Regele, Martin Grossmann, Damien Charles Weber
Significant acceleration of development by automating quality assurance of a medical particle accelerator safety system using a formal language driven test stand
6 pages, 9 figures, 21st IEEE Real Time Conference, 9-15 June 2018 Colonial Williamsburg, USA
null
null
null
cs.SE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
At the Centre for Proton Therapy at the Paul Scherrer Institute cancer patients are treated with a fixed beamline and in two gantries for ocular and non-ocular malignancies, respectively. For the installation of a third gantry a new patient safety system (PaSS) was developed and is sequentially being rolled out to up...
[ { "created": "Sat, 23 Jun 2018 12:43:04 GMT", "version": "v1" } ]
2018-07-06
[ [ "Carmona", "Pablo Fernandez", "" ], [ "Eichin", "Michael", "" ], [ "Mayor", "Alexandre", "" ], [ "Regele", "Harald", "" ], [ "Grossmann", "Martin", "" ], [ "Weber", "Damien Charles", "" ] ]
At the Centre for Proton Therapy at the Paul Scherrer Institute cancer patients are treated with a fixed beamline and in two gantries for ocular and non-ocular malignancies, respectively. For the installation of a third gantry a new patient safety system (PaSS) was developed and is sequentially being rolled out to upda...
2210.10618
Chen Tang
Henglin Huang, Chen Tang, Tyler Loakman, Frank Guerin and Chenghua Lin
Improving Chinese Story Generation via Awareness of Syntactic Dependencies and Semantics
null
AACL 2022
null
null
cs.CL cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Story generation aims to generate a long narrative conditioned on a given input. In spite of the success of prior works with the application of pre-trained models, current neural models for Chinese stories still struggle to generate high-quality long text narratives. We hypothesise that this stems from ambiguity in s...
[ { "created": "Wed, 19 Oct 2022 15:01:52 GMT", "version": "v1" } ]
2022-10-20
[ [ "Huang", "Henglin", "" ], [ "Tang", "Chen", "" ], [ "Loakman", "Tyler", "" ], [ "Guerin", "Frank", "" ], [ "Lin", "Chenghua", "" ] ]
Story generation aims to generate a long narrative conditioned on a given input. In spite of the success of prior works with the application of pre-trained models, current neural models for Chinese stories still struggle to generate high-quality long text narratives. We hypothesise that this stems from ambiguity in syn...
1905.08388
Angel Beltre
Pankaj Saha, Angel Beltre, Madhusudhan Govindaraju
Exploring the Fairness and Resource Distribution in an Apache Mesos Environment
null
2018 IEEE 11th International Conference on Cloud Computing (CLOUD)
10.1109/CLOUD.2018.00061
null
cs.PF cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Apache Mesos, a cluster-wide resource manager, is widely deployed in massive scale at several Clouds and Data Centers. Mesos aims to provide high cluster utilization via fine grained resource co-scheduling and resource fairness among multiple users through Dominant Resource Fairness (DRF) based allocation. DRF takes ...
[ { "created": "Tue, 21 May 2019 00:00:07 GMT", "version": "v1" } ]
2019-05-22
[ [ "Saha", "Pankaj", "" ], [ "Beltre", "Angel", "" ], [ "Govindaraju", "Madhusudhan", "" ] ]
Apache Mesos, a cluster-wide resource manager, is widely deployed in massive scale at several Clouds and Data Centers. Mesos aims to provide high cluster utilization via fine grained resource co-scheduling and resource fairness among multiple users through Dominant Resource Fairness (DRF) based allocation. DRF takes in...
2112.10332
Limeng Dong
Limeng Dong, Hui-Ming Wang, Jiale Bai
Active Reconfigurable Intelligent Surface Aided Secure Transmission
Accepted by IEEE TVT
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Reconfigurable Intelligent Surface (RIS) draws great attentions in academic and industry due to its passive and low power consumption nature, and has currently been used in physical layer security to enhance the secure transmission. However, due to the existence of double fading effect on the reflecting channel link ...
[ { "created": "Mon, 20 Dec 2021 04:34:26 GMT", "version": "v1" } ]
2021-12-21
[ [ "Dong", "Limeng", "" ], [ "Wang", "Hui-Ming", "" ], [ "Bai", "Jiale", "" ] ]
Reconfigurable Intelligent Surface (RIS) draws great attentions in academic and industry due to its passive and low power consumption nature, and has currently been used in physical layer security to enhance the secure transmission. However, due to the existence of double fading effect on the reflecting channel link be...
2101.04799
Ananda Samajdar
Ananda Samajdar, Michael Pellauer, Tushar Krishna
Self-Adaptive Reconfigurable Arrays (SARA): Using ML to Assist Scaling GEMM Acceleration
null
null
null
null
cs.AR cs.LG
http://creativecommons.org/licenses/by-nc-sa/4.0/
With increasing diversity in Deep Neural Network(DNN) models in terms of layer shapes and sizes, the research community has been investigating flexible/reconfigurable accelerator substrates. This line of research has opened up two challenges. The first is to determine the appropriate amount of flexibility within an a...
[ { "created": "Tue, 12 Jan 2021 23:20:23 GMT", "version": "v1" }, { "created": "Sat, 23 Apr 2022 18:33:06 GMT", "version": "v2" } ]
2022-04-26
[ [ "Samajdar", "Ananda", "" ], [ "Pellauer", "Michael", "" ], [ "Krishna", "Tushar", "" ] ]
With increasing diversity in Deep Neural Network(DNN) models in terms of layer shapes and sizes, the research community has been investigating flexible/reconfigurable accelerator substrates. This line of research has opened up two challenges. The first is to determine the appropriate amount of flexibility within an acc...
2406.00723
Hao Wu
Hao Wu
Throughput and Link Utilization Improvement in Satellite Networks: A Learning-Enabled Approach
5 pages, 6 figures
null
null
null
cs.NI cs.SY eess.SY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Satellite networks provide communication services to global users with an uneven geographical distribution. In densely populated regions, Inter-satellite links (ISLs) often experience congestion, blocking traffic from other links and leading to low link utilization and throughput. In such cases, delay-tolerant traffi...
[ { "created": "Sun, 2 Jun 2024 12:16:08 GMT", "version": "v1" } ]
2024-06-04
[ [ "Wu", "Hao", "" ] ]
Satellite networks provide communication services to global users with an uneven geographical distribution. In densely populated regions, Inter-satellite links (ISLs) often experience congestion, blocking traffic from other links and leading to low link utilization and throughput. In such cases, delay-tolerant traffic ...
2302.12250
Dayal Singh Kalra
Dayal Singh Kalra and Maissam Barkeshli
Phase diagram of early training dynamics in deep neural networks: effect of the learning rate, depth, and width
Accepted at NeurIPS 2023 (camera-ready version): Additional results added for cross-entropy loss and effect on network output at initialization; 10+32 pages, 8+35 figures
null
null
null
cs.LG cond-mat.dis-nn
http://creativecommons.org/licenses/by/4.0/
We systematically analyze optimization dynamics in deep neural networks (DNNs) trained with stochastic gradient descent (SGD) and study the effect of learning rate $\eta$, depth $d$, and width $w$ of the neural network. By analyzing the maximum eigenvalue $\lambda^H_t$ of the Hessian of the loss, which is a measure o...
[ { "created": "Thu, 23 Feb 2023 18:59:30 GMT", "version": "v1" }, { "created": "Tue, 24 Oct 2023 17:59:46 GMT", "version": "v2" } ]
2023-10-25
[ [ "Kalra", "Dayal Singh", "" ], [ "Barkeshli", "Maissam", "" ] ]
We systematically analyze optimization dynamics in deep neural networks (DNNs) trained with stochastic gradient descent (SGD) and study the effect of learning rate $\eta$, depth $d$, and width $w$ of the neural network. By analyzing the maximum eigenvalue $\lambda^H_t$ of the Hessian of the loss, which is a measure of ...
1908.00310
Buddhika Nettasinghe
Buddhika Nettasinghe and Vikram Krishnamurthy
Maximum Likelihood Estimation of Power-law Degree Distributions via Friendship Paradox based Sampling
Accepted to ACM Transactions on Knowledge Discovery from Data (2021)
null
null
null
cs.SI physics.data-an physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper considers the problem of estimating a power-law degree distribution of an undirected network using sampled data. Although power-law degree distributions are ubiquitous in nature, the widely used parametric methods for estimating them (e.g. linear regression on double-logarithmic axes, maximum likelihood es...
[ { "created": "Thu, 1 Aug 2019 10:29:14 GMT", "version": "v1" }, { "created": "Wed, 4 Sep 2019 01:00:12 GMT", "version": "v2" }, { "created": "Mon, 28 Dec 2020 18:50:43 GMT", "version": "v3" }, { "created": "Sun, 7 Mar 2021 19:42:49 GMT", "version": "v4" } ]
2021-03-09
[ [ "Nettasinghe", "Buddhika", "" ], [ "Krishnamurthy", "Vikram", "" ] ]
This paper considers the problem of estimating a power-law degree distribution of an undirected network using sampled data. Although power-law degree distributions are ubiquitous in nature, the widely used parametric methods for estimating them (e.g. linear regression on double-logarithmic axes, maximum likelihood esti...
2209.09580
Pierre-Louis Roman
Martina Camaioni, Rachid Guerraoui, Jovan Komatovic, Matteo Monti, Pierre-Louis Roman, Manuel Vidigueira, Gauthier Voron
Carbon: Scaling Trusted Payments with Untrusted Machines
This is an extended version of the paper appearing at IEEE TDSC 2024 under DOI 10.1109/TDSC.2024.3428617 with formal definitions, pseudocode, and proofs added in appendices; these appendices correspond to the previous version of this paper on arXiv (arXiv:2209.09580v2)
null
10.1109/TDSC.2024.3428617
null
cs.DC
http://creativecommons.org/licenses/by/4.0/
This paper introduces Carbon, a high-throughput system enabling asynchronous (safe) and consensus-free (efficient) payments and votes within a dynamic set of clients. Carbon is operated by a dynamic set of validators that may be reconfigured asynchronously, offering its clients eclipse resistance as well as lightweig...
[ { "created": "Tue, 20 Sep 2022 09:50:44 GMT", "version": "v1" }, { "created": "Fri, 30 Sep 2022 09:26:59 GMT", "version": "v2" }, { "created": "Thu, 15 Aug 2024 16:12:53 GMT", "version": "v3" } ]
2024-08-16
[ [ "Camaioni", "Martina", "" ], [ "Guerraoui", "Rachid", "" ], [ "Komatovic", "Jovan", "" ], [ "Monti", "Matteo", "" ], [ "Roman", "Pierre-Louis", "" ], [ "Vidigueira", "Manuel", "" ], [ "Voron", "Gauthier", "...
This paper introduces Carbon, a high-throughput system enabling asynchronous (safe) and consensus-free (efficient) payments and votes within a dynamic set of clients. Carbon is operated by a dynamic set of validators that may be reconfigured asynchronously, offering its clients eclipse resistance as well as lightweight...
1305.5228
Richard Mayr
Parosh Aziz Abdulla, Lorenzo Clemente, Richard Mayr, Sven Sandberg
Stochastic Parity Games on Lossy Channel Systems
19 pages
null
null
EDI-INF-RR-1416
cs.GT cs.LO
http://creativecommons.org/licenses/by/3.0/
We give an algorithm for solving stochastic parity games with almost-sure winning conditions on lossy channel systems, for the case where the players are restricted to finite-memory strategies. First, we describe a general framework, where we consider the class of 2.5-player games with almost-sure parity winning cond...
[ { "created": "Wed, 22 May 2013 18:43:54 GMT", "version": "v1" }, { "created": "Thu, 13 Jun 2013 10:17:22 GMT", "version": "v2" } ]
2013-06-14
[ [ "Abdulla", "Parosh Aziz", "" ], [ "Clemente", "Lorenzo", "" ], [ "Mayr", "Richard", "" ], [ "Sandberg", "Sven", "" ] ]
We give an algorithm for solving stochastic parity games with almost-sure winning conditions on lossy channel systems, for the case where the players are restricted to finite-memory strategies. First, we describe a general framework, where we consider the class of 2.5-player games with almost-sure parity winning condit...
1012.2524
Jaydip Sen
Jaydip Sen, Munir Sayyad, and Basavaraj Hooli
Convergence and Next Generation Networks
67 pages, 11 figures, 4 tables. Bootk Chapter published in the book "Future trends and Challenegs for ICT Standardization", pp. 107 - 192
BooK: Future Trends and Challenges for ICT Standardization. Editor: Ramjee Prasad, River Publishers, Aalborg, Denmark, 2010
10.13140/RG.2.1.2986.2640
null
cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The communications sector is undergoing significant changes, with the emergence of a number of platforms available to provide a different range of services. Some of these platforms are complementary to each other, while others are competitive, or can provide a valid substitute for some of the services provided. Up ti...
[ { "created": "Sun, 12 Dec 2010 08:28:25 GMT", "version": "v1" } ]
2021-09-07
[ [ "Sen", "Jaydip", "" ], [ "Sayyad", "Munir", "" ], [ "Hooli", "Basavaraj", "" ] ]
The communications sector is undergoing significant changes, with the emergence of a number of platforms available to provide a different range of services. Some of these platforms are complementary to each other, while others are competitive, or can provide a valid substitute for some of the services provided. Up till...
1705.03529
Andre Puschmann
Andr\'e Puschmann, Paul Sutton, Ismael Gomez
Implementing NB-IoT in Software - Experiences Using the srsLTE Library
Appears in the proceedings of the Wireless Innovation Forum Europe 2017
null
null
null
cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
NB-IoT is the 3GPP standard for machine-to-machine communications, recently finalized within LTE release 13. This article gives a brief overview about this new LTE-based radio access technology and presents a implementation developed using the srsLTE software radio suite. We also carry out a performance study in whic...
[ { "created": "Tue, 9 May 2017 20:28:30 GMT", "version": "v1" } ]
2017-05-11
[ [ "Puschmann", "André", "" ], [ "Sutton", "Paul", "" ], [ "Gomez", "Ismael", "" ] ]
NB-IoT is the 3GPP standard for machine-to-machine communications, recently finalized within LTE release 13. This article gives a brief overview about this new LTE-based radio access technology and presents a implementation developed using the srsLTE software radio suite. We also carry out a performance study in which ...
2011.11635
Sebastian Friedemann
Sebastian Friedemann (DATAMOVE), Bruno Raffin (DATAMOVE)
An elastic framework for ensemble-based large-scale data assimilation
null
null
null
null
cs.CE cs.DC physics.comp-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Prediction of chaotic systems relies on a floating fusion of sensor data (observations) with a numerical model to decide on a good system trajectory and to compensate nonlinear feedback effects. Ensemble-based data assimilation (DA) is a major method for this concern depending on propagating an ensemble of perturbed ...
[ { "created": "Sat, 21 Nov 2020 11:23:43 GMT", "version": "v1" }, { "created": "Wed, 25 Nov 2020 08:23:29 GMT", "version": "v2" } ]
2020-11-26
[ [ "Friedemann", "Sebastian", "", "DATAMOVE" ], [ "Raffin", "Bruno", "", "DATAMOVE" ] ]
Prediction of chaotic systems relies on a floating fusion of sensor data (observations) with a numerical model to decide on a good system trajectory and to compensate nonlinear feedback effects. Ensemble-based data assimilation (DA) is a major method for this concern depending on propagating an ensemble of perturbed mo...
1905.08204
Duncan Brown
Karan Vahi, Mats Rynge, George Papadimitriou, Duncan A. Brown, Rajiv Mayani, Rafael Ferreira da Silva, Ewa Deelman, Anirban Mandal, Eric Lyons, Michael Zink
Custom Execution Environments with Containers in Pegasus-enabled Scientific Workflows
10 pages, 7 figures, submitted to eScience 2019
null
null
null
cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Science reproducibility is a cornerstone feature in scientific workflows. In most cases, this has been implemented as a way to exactly reproduce the computational steps taken to reach the final results. While these steps are often completely described, including the input parameters, datasets, and codes, the environm...
[ { "created": "Mon, 20 May 2019 16:41:20 GMT", "version": "v1" } ]
2019-05-21
[ [ "Vahi", "Karan", "" ], [ "Rynge", "Mats", "" ], [ "Papadimitriou", "George", "" ], [ "Brown", "Duncan A.", "" ], [ "Mayani", "Rajiv", "" ], [ "da Silva", "Rafael Ferreira", "" ], [ "Deelman", "Ewa", "" ],...
Science reproducibility is a cornerstone feature in scientific workflows. In most cases, this has been implemented as a way to exactly reproduce the computational steps taken to reach the final results. While these steps are often completely described, including the input parameters, datasets, and codes, the environmen...
2404.10289
Max Kreminski
Max Kreminski
The Dearth of the Author in AI-Supported Writing
Published as a workshop paper at the In2Writing workshop at CHI 2024
null
null
null
cs.HC cs.AI
http://creativecommons.org/licenses/by-nc-sa/4.0/
We diagnose and briefly discuss the dearth of the author: a condition that arises when AI-based creativity support tools for writing allow users to produce large amounts of text without making a commensurate number of creative decisions, resulting in output that is sparse in expressive intent. We argue that the deart...
[ { "created": "Tue, 16 Apr 2024 05:23:03 GMT", "version": "v1" } ]
2024-04-17
[ [ "Kreminski", "Max", "" ] ]
We diagnose and briefly discuss the dearth of the author: a condition that arises when AI-based creativity support tools for writing allow users to produce large amounts of text without making a commensurate number of creative decisions, resulting in output that is sparse in expressive intent. We argue that the dearth ...
1706.06714
Van-Khanh Tran
Van-Khanh Tran and Le-Minh Nguyen
Neural-based Natural Language Generation in Dialogue using RNN Encoder-Decoder with Semantic Aggregation
To be appear at SIGDIAL 2017. arXiv admin note: text overlap with arXiv:1706.00134, arXiv:1706.00139
null
null
null
cs.CL cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Natural language generation (NLG) is an important component in spoken dialogue systems. This paper presents a model called Encoder-Aggregator-Decoder which is an extension of an Recurrent Neural Network based Encoder-Decoder architecture. The proposed Semantic Aggregator consists of two components: an Aligner and a R...
[ { "created": "Wed, 21 Jun 2017 01:07:02 GMT", "version": "v1" }, { "created": "Sun, 25 Jun 2017 09:31:34 GMT", "version": "v2" }, { "created": "Tue, 11 Jul 2017 14:47:13 GMT", "version": "v3" } ]
2017-07-12
[ [ "Tran", "Van-Khanh", "" ], [ "Nguyen", "Le-Minh", "" ] ]
Natural language generation (NLG) is an important component in spoken dialogue systems. This paper presents a model called Encoder-Aggregator-Decoder which is an extension of an Recurrent Neural Network based Encoder-Decoder architecture. The proposed Semantic Aggregator consists of two components: an Aligner and a Ref...
1009.2118
Sahand Negahban
Sahand Negahban and Martin J. Wainwright
Restricted strong convexity and weighted matrix completion: Optimal bounds with noise
null
null
null
null
cs.IT math.IT math.ST stat.TH
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We consider the matrix completion problem under a form of row/column weighted entrywise sampling, including the case of uniform entrywise sampling as a special case. We analyze the associated random observation operator, and prove that with high probability, it satisfies a form of restricted strong convexity with res...
[ { "created": "Fri, 10 Sep 2010 23:08:58 GMT", "version": "v1" }, { "created": "Sun, 15 May 2011 17:30:12 GMT", "version": "v2" } ]
2011-05-17
[ [ "Negahban", "Sahand", "" ], [ "Wainwright", "Martin J.", "" ] ]
We consider the matrix completion problem under a form of row/column weighted entrywise sampling, including the case of uniform entrywise sampling as a special case. We analyze the associated random observation operator, and prove that with high probability, it satisfies a form of restricted strong convexity with respe...
2109.11891
Aishwarya Venkataramanan
Aishwarya Venkataramanan, Martin Laviale, C\'ecile Figus, Philippe Usseglio-Polatera, C\'edric Pradalier
Tackling Inter-Class Similarity and Intra-Class Variance for Microscopic Image-based Classification
13th International Conference on Computer Vision Systems (2021)
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Automatic classification of aquatic microorganisms is based on the morphological features extracted from individual images. The current works on their classification do not consider the inter-class similarity and intra-class variance that causes misclassification. We are particularly interested in the case where vari...
[ { "created": "Fri, 24 Sep 2021 11:17:02 GMT", "version": "v1" } ]
2021-09-27
[ [ "Venkataramanan", "Aishwarya", "" ], [ "Laviale", "Martin", "" ], [ "Figus", "Cécile", "" ], [ "Usseglio-Polatera", "Philippe", "" ], [ "Pradalier", "Cédric", "" ] ]
Automatic classification of aquatic microorganisms is based on the morphological features extracted from individual images. The current works on their classification do not consider the inter-class similarity and intra-class variance that causes misclassification. We are particularly interested in the case where varian...
2406.18094
Hiroaki Yamagiwa
Yunzhen He, Hiroaki Yamagiwa, Hidetoshi Shimodaira
Shimo Lab at "Discharge Me!": Discharge Summarization by Prompt-Driven Concatenation of Electronic Health Record Sections
BioNLP @ ACL2024
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we present our approach to the shared task "Discharge Me!" at the BioNLP Workshop 2024. The primary goal of this task is to reduce the time and effort clinicians spend on writing detailed notes in the electronic health record (EHR). Participants develop a pipeline to generate the "Brief Hospital Course...
[ { "created": "Wed, 26 Jun 2024 06:10:20 GMT", "version": "v1" } ]
2024-06-27
[ [ "He", "Yunzhen", "" ], [ "Yamagiwa", "Hiroaki", "" ], [ "Shimodaira", "Hidetoshi", "" ] ]
In this paper, we present our approach to the shared task "Discharge Me!" at the BioNLP Workshop 2024. The primary goal of this task is to reduce the time and effort clinicians spend on writing detailed notes in the electronic health record (EHR). Participants develop a pipeline to generate the "Brief Hospital Course" ...
2303.07814
Adam Goldbraikh
Adam Goldbraikh, Omer Shubi, Or Rubin, Carla M Pugh, Shlomi Laufer
MS-TCRNet: Multi-Stage Temporal Convolutional Recurrent Networks for Action Segmentation Using Sensor-Augmented Kinematics
41 pages, 7 figures. Submitted to Pattern Recognition
null
null
null
cs.CV cs.LG cs.RO eess.IV
http://creativecommons.org/licenses/by-nc-nd/4.0/
Action segmentation is a challenging task in high-level process analysis, typically performed on video or kinematic data obtained from various sensors. This work presents two contributions related to action segmentation on kinematic data. Firstly, we introduce two versions of Multi-Stage Temporal Convolutional Recurr...
[ { "created": "Tue, 14 Mar 2023 11:44:58 GMT", "version": "v1" }, { "created": "Fri, 12 Jul 2024 15:48:09 GMT", "version": "v2" } ]
2024-07-15
[ [ "Goldbraikh", "Adam", "" ], [ "Shubi", "Omer", "" ], [ "Rubin", "Or", "" ], [ "Pugh", "Carla M", "" ], [ "Laufer", "Shlomi", "" ] ]
Action segmentation is a challenging task in high-level process analysis, typically performed on video or kinematic data obtained from various sensors. This work presents two contributions related to action segmentation on kinematic data. Firstly, we introduce two versions of Multi-Stage Temporal Convolutional Recurren...
1903.04463
Farzin Salek Shishavan
Farzin Salek, Min-Hsiu Hsieh, Javier R. Fonollosa
Publicness, Privacy and Confidentiality in the Single-Serving Quantum Broadcast Channel
23 pages, 1 figure, journal
null
null
null
cs.IT math.IT quant-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The 2-receiver broadcast channel is studied: a network with three parties where the transmitter and one of the receivers are the primarily involved parties and the other receiver considered as third party. The messages that are determined to be communicated are classified into public, private and confidential based o...
[ { "created": "Mon, 11 Mar 2019 17:38:03 GMT", "version": "v1" } ]
2019-03-12
[ [ "Salek", "Farzin", "" ], [ "Hsieh", "Min-Hsiu", "" ], [ "Fonollosa", "Javier R.", "" ] ]
The 2-receiver broadcast channel is studied: a network with three parties where the transmitter and one of the receivers are the primarily involved parties and the other receiver considered as third party. The messages that are determined to be communicated are classified into public, private and confidential based on ...
2206.11541
Mohammed Salah
Mohammed Salah, Mohammed Chehadah, Muhammed Humais, Mohammed Wahbah, Abdulla Ayyad, Rana Azzam, Lakmal Seneviratne, and Yahya Zweiri
A Neuromorphic Vision-Based Measurement for Robust Relative Localization in Future Space Exploration Missions
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Space exploration has witnessed revolutionary changes upon landing of the Perseverance Rover on the Martian surface and demonstrating the first flight beyond Earth by the Mars helicopter, Ingenuity. During their mission on Mars, Perseverance Rover and Ingenuity collaboratively explore the Martian surface, where Ingen...
[ { "created": "Thu, 23 Jun 2022 08:39:05 GMT", "version": "v1" }, { "created": "Wed, 12 Oct 2022 08:25:59 GMT", "version": "v2" } ]
2022-10-13
[ [ "Salah", "Mohammed", "" ], [ "Chehadah", "Mohammed", "" ], [ "Humais", "Muhammed", "" ], [ "Wahbah", "Mohammed", "" ], [ "Ayyad", "Abdulla", "" ], [ "Azzam", "Rana", "" ], [ "Seneviratne", "Lakmal", "" ],...
Space exploration has witnessed revolutionary changes upon landing of the Perseverance Rover on the Martian surface and demonstrating the first flight beyond Earth by the Mars helicopter, Ingenuity. During their mission on Mars, Perseverance Rover and Ingenuity collaboratively explore the Martian surface, where Ingenui...
2105.09540
Xiaolin Chen
Xiaolin Chen, Shuai Zhou, Bei guan, Kai Yang, Hao Fan, Hu Wang, Yongji Wang
Fed-EINI: An Efficient and Interpretable Inference Framework for Decision Tree Ensembles in Federated Learning
10 pages, 8 figures. This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible
null
null
null
cs.LG cs.AI cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The increasing concerns about data privacy and security drive an emerging field of studying privacy-preserving machine learning from isolated data sources, i.e., federated learning. A class of federated learning, vertical federated learning, where different parties hold different features for common users, has a grea...
[ { "created": "Thu, 20 May 2021 06:40:05 GMT", "version": "v1" }, { "created": "Thu, 2 Dec 2021 03:34:46 GMT", "version": "v10" }, { "created": "Wed, 8 Dec 2021 02:06:36 GMT", "version": "v11" }, { "created": "Mon, 12 Jul 2021 08:09:39 GMT", "version": "v2" }, { "c...
2021-12-10
[ [ "Chen", "Xiaolin", "" ], [ "Zhou", "Shuai", "" ], [ "guan", "Bei", "" ], [ "Yang", "Kai", "" ], [ "Fan", "Hao", "" ], [ "Wang", "Hu", "" ], [ "Wang", "Yongji", "" ] ]
The increasing concerns about data privacy and security drive an emerging field of studying privacy-preserving machine learning from isolated data sources, i.e., federated learning. A class of federated learning, vertical federated learning, where different parties hold different features for common users, has a great ...
2303.17661
Muntabir Hasan Choudhury
Muntabir Hasan Choudhury, Lamia Salsabil, Himarsha R. Jayanetti, Jian Wu, William A. Ingram, Edward A. Fox
MetaEnhance: Metadata Quality Improvement for Electronic Theses and Dissertations of University Libraries
7 pages, 3 tables, and 1 figure. Accepted by 2023 ACM/IEEE Joint Conference on Digital Libraries (JCDL '23) as a short paper
null
null
null
cs.DL cs.AI cs.LG
http://creativecommons.org/licenses/by-nc-sa/4.0/
Metadata quality is crucial for digital objects to be discovered through digital library interfaces. However, due to various reasons, the metadata of digital objects often exhibits incomplete, inconsistent, and incorrect values. We investigate methods to automatically detect, correct, and canonicalize scholarly metad...
[ { "created": "Thu, 30 Mar 2023 18:56:42 GMT", "version": "v1" } ]
2023-04-03
[ [ "Choudhury", "Muntabir Hasan", "" ], [ "Salsabil", "Lamia", "" ], [ "Jayanetti", "Himarsha R.", "" ], [ "Wu", "Jian", "" ], [ "Ingram", "William A.", "" ], [ "Fox", "Edward A.", "" ] ]
Metadata quality is crucial for digital objects to be discovered through digital library interfaces. However, due to various reasons, the metadata of digital objects often exhibits incomplete, inconsistent, and incorrect values. We investigate methods to automatically detect, correct, and canonicalize scholarly metadat...
2405.09114
Qihe Pan
Yiming Wu, Qihe Pan, Zhen Zhao, Zicheng Wang, Sifan Long, Ronghua Liang
SOEDiff: Efficient Distillation for Small Object Editing
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we delve into a new task known as small object editing (SOE), which focuses on text-based image inpainting within a constrained, small-sized area. Despite the remarkable success have been achieved by current image inpainting approaches, their application to the SOE task generally results in failure cas...
[ { "created": "Wed, 15 May 2024 06:14:31 GMT", "version": "v1" }, { "created": "Thu, 25 Jul 2024 21:30:41 GMT", "version": "v2" } ]
2024-07-29
[ [ "Wu", "Yiming", "" ], [ "Pan", "Qihe", "" ], [ "Zhao", "Zhen", "" ], [ "Wang", "Zicheng", "" ], [ "Long", "Sifan", "" ], [ "Liang", "Ronghua", "" ] ]
In this paper, we delve into a new task known as small object editing (SOE), which focuses on text-based image inpainting within a constrained, small-sized area. Despite the remarkable success have been achieved by current image inpainting approaches, their application to the SOE task generally results in failure cases...
2309.06844
Dimitar Dimitrov
Georgi Pachov, Dimitar Dimitrov, Ivan Koychev, Preslav Nakov
Gpachov at CheckThat! 2023: A Diverse Multi-Approach Ensemble for Subjectivity Detection in News Articles
null
null
null
null
cs.CL cs.AI cs.MM
http://creativecommons.org/licenses/by-sa/4.0/
The wide-spread use of social networks has given rise to subjective, misleading, and even false information on the Internet. Thus, subjectivity detection can play an important role in ensuring the objectiveness and the quality of a piece of information. This paper presents the solution built by the Gpachov team for t...
[ { "created": "Wed, 13 Sep 2023 09:49:20 GMT", "version": "v1" } ]
2023-09-14
[ [ "Pachov", "Georgi", "" ], [ "Dimitrov", "Dimitar", "" ], [ "Koychev", "Ivan", "" ], [ "Nakov", "Preslav", "" ] ]
The wide-spread use of social networks has given rise to subjective, misleading, and even false information on the Internet. Thus, subjectivity detection can play an important role in ensuring the objectiveness and the quality of a piece of information. This paper presents the solution built by the Gpachov team for the...
2306.02287
Mamtaj Akter
Mamtaj Akter, Leena Alghamdi, Jess Kropczynski, Heather Lipford, Pamela Wisniewski
It Takes a Village: A Case for Including Extended Family Members in the Joint Oversight of Family-based Privacy and Security for Mobile Smartphones
null
Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems
10.1145/3544549.3585904
null
cs.HC
http://creativecommons.org/licenses/by-nc-nd/4.0/
We conducted a user study with 19 parent-teen dyads to understand the perceived benefits and drawbacks of using a mobile app that allows them to co-manage mobile privacy, safety, and security within their families. While the primary goal of the study was to understand the use case as it pertained to parents and teens...
[ { "created": "Sun, 4 Jun 2023 07:33:37 GMT", "version": "v1" }, { "created": "Tue, 16 Apr 2024 03:31:03 GMT", "version": "v2" } ]
2024-04-17
[ [ "Akter", "Mamtaj", "" ], [ "Alghamdi", "Leena", "" ], [ "Kropczynski", "Jess", "" ], [ "Lipford", "Heather", "" ], [ "Wisniewski", "Pamela", "" ] ]
We conducted a user study with 19 parent-teen dyads to understand the perceived benefits and drawbacks of using a mobile app that allows them to co-manage mobile privacy, safety, and security within their families. While the primary goal of the study was to understand the use case as it pertained to parents and teens, ...
1909.10686
Weiwei Wan
Daniel Sanchez, Weiwei Wan, and Kensuke Harada
Tethered Tool Manipulation Planning with Cable Maneuvering
null
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we present a planner for manipulating tethered tools using dual-armed robots. The planner generates robot motion sequences to maneuver a tool and its cable while avoiding robot-cable entanglements. Firstly, the planner generates an Object Manipulation Motion Sequence (OMMS) to handle the tool and place...
[ { "created": "Tue, 24 Sep 2019 02:55:43 GMT", "version": "v1" } ]
2019-09-25
[ [ "Sanchez", "Daniel", "" ], [ "Wan", "Weiwei", "" ], [ "Harada", "Kensuke", "" ] ]
In this paper, we present a planner for manipulating tethered tools using dual-armed robots. The planner generates robot motion sequences to maneuver a tool and its cable while avoiding robot-cable entanglements. Firstly, the planner generates an Object Manipulation Motion Sequence (OMMS) to handle the tool and place i...
2210.05419
Yante Li
Yante Li, Yang Liu, Kh\'Anh Nguyen, Henglin Shi, Eija Vuorenmaa, Sanna Jarvela, and Guoying Zhao
Exploring Interactions and Regulations in Collaborative Learning: An Interdisciplinary Multimodal Dataset
17 pages, 9 figures
null
null
null
cs.CV cs.DB
http://creativecommons.org/licenses/by-nc-nd/4.0/
Collaborative learning is an educational approach that enhances learning through shared goals and working together. Interaction and regulation are two essential factors related to the success of collaborative learning. Since the information from various modalities can reflect the quality of collaboration, a new multi...
[ { "created": "Tue, 11 Oct 2022 12:56:36 GMT", "version": "v1" } ]
2022-10-12
[ [ "Li", "Yante", "" ], [ "Liu", "Yang", "" ], [ "Nguyen", "KhÁnh", "" ], [ "Shi", "Henglin", "" ], [ "Vuorenmaa", "Eija", "" ], [ "Jarvela", "Sanna", "" ], [ "Zhao", "Guoying", "" ] ]
Collaborative learning is an educational approach that enhances learning through shared goals and working together. Interaction and regulation are two essential factors related to the success of collaborative learning. Since the information from various modalities can reflect the quality of collaboration, a new multimo...
1901.02802
Alireza Shamsoshoara
Alireza Shamsoshoara
Overview of Blakley's Secret Sharing Scheme
8 pages, 4 Figures
null
null
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this report, I explained the problem of Secret Sharing Scheme. Then based on the definition of the problem, two old methods: Blakley's Secret Sharing Scheme and Shamir's Secret Sharing are introduced. However, we explained the details of the first one since it's the topic of this work. Blakley's method has an appl...
[ { "created": "Wed, 9 Jan 2019 16:08:30 GMT", "version": "v1" } ]
2019-01-10
[ [ "Shamsoshoara", "Alireza", "" ] ]
In this report, I explained the problem of Secret Sharing Scheme. Then based on the definition of the problem, two old methods: Blakley's Secret Sharing Scheme and Shamir's Secret Sharing are introduced. However, we explained the details of the first one since it's the topic of this work. Blakley's method has an applic...
1912.00497
Himangi Mittal
Himangi Mittal, Brian Okorn, David Held
Just Go with the Flow: Self-Supervised Scene Flow Estimation
Accepted at CVPR 2020 (Oral)
null
null
null
cs.CV cs.LG cs.RO eess.IV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
When interacting with highly dynamic environments, scene flow allows autonomous systems to reason about the non-rigid motion of multiple independent objects. This is of particular interest in the field of autonomous driving, in which many cars, people, bicycles, and other objects need to be accurately tracked. Curren...
[ { "created": "Sun, 1 Dec 2019 20:32:54 GMT", "version": "v1" }, { "created": "Mon, 13 Apr 2020 19:10:57 GMT", "version": "v2" } ]
2020-04-15
[ [ "Mittal", "Himangi", "" ], [ "Okorn", "Brian", "" ], [ "Held", "David", "" ] ]
When interacting with highly dynamic environments, scene flow allows autonomous systems to reason about the non-rigid motion of multiple independent objects. This is of particular interest in the field of autonomous driving, in which many cars, people, bicycles, and other objects need to be accurately tracked. Current ...
2006.14964
Anna Melnichenko
Hagen Echzell, Tobias Friedrich, Pascal Lenzner, Anna Melnichenko
Flow-Based Network Creation Games
To appear at the 29th International Joint Conference on Artificial Intelligence and the 17th Pacific Rim International Conference on Artificial Intelligence (IJCAI-PRICAI 2020)
null
null
null
cs.GT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Network Creation Games(NCGs) model the creation of decentralized communication networks like the Internet. In such games strategic agents corresponding to network nodes selfishly decide with whom to connect to optimize some objective function. Past research intensively analyzed models where the agents strive for a ce...
[ { "created": "Fri, 26 Jun 2020 12:59:24 GMT", "version": "v1" } ]
2020-06-29
[ [ "Echzell", "Hagen", "" ], [ "Friedrich", "Tobias", "" ], [ "Lenzner", "Pascal", "" ], [ "Melnichenko", "Anna", "" ] ]
Network Creation Games(NCGs) model the creation of decentralized communication networks like the Internet. In such games strategic agents corresponding to network nodes selfishly decide with whom to connect to optimize some objective function. Past research intensively analyzed models where the agents strive for a cent...
2307.09777
Shuo Huang
Shuo Huang, Chengpeng Hu, Julian Togelius, Jialin Liu
Generating Redstone Style Cities in Minecraft
null
null
null
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Procedurally generating cities in Minecraft provides players more diverse scenarios and could help understand and improve the design of cities in other digital worlds and the real world. This paper presents a city generator that was submitted as an entry to the 2023 Edition of Minecraft Settlement Generation Competit...
[ { "created": "Wed, 19 Jul 2023 06:36:01 GMT", "version": "v1" } ]
2023-07-20
[ [ "Huang", "Shuo", "" ], [ "Hu", "Chengpeng", "" ], [ "Togelius", "Julian", "" ], [ "Liu", "Jialin", "" ] ]
Procedurally generating cities in Minecraft provides players more diverse scenarios and could help understand and improve the design of cities in other digital worlds and the real world. This paper presents a city generator that was submitted as an entry to the 2023 Edition of Minecraft Settlement Generation Competitio...
1609.03500
Sheng Zou
Sheng Zou and Alina Zare
Hyperspectral Unmixing with Endmember Variability using Partial Membership Latent Dirichlet Allocation
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The application of Partial Membership Latent Dirichlet Allocation(PM-LDA) for hyperspectral endmember estimation and spectral unmixing is presented. PM-LDA provides a model for a hyperspectral image analysis that accounts for spectral variability and incorporates spatial information through the use of superpixel-base...
[ { "created": "Mon, 12 Sep 2016 17:32:41 GMT", "version": "v1" } ]
2016-09-13
[ [ "Zou", "Sheng", "" ], [ "Zare", "Alina", "" ] ]
The application of Partial Membership Latent Dirichlet Allocation(PM-LDA) for hyperspectral endmember estimation and spectral unmixing is presented. PM-LDA provides a model for a hyperspectral image analysis that accounts for spectral variability and incorporates spatial information through the use of superpixel-based ...
2206.15007
Zhiying Zhu
Zhiying Zhu, Weixin Liang, James Zou
GSCLIP : A Framework for Explaining Distribution Shifts in Natural Language
Accepted by ICML 2022 DataPerf
null
null
null
cs.CL cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Helping end users comprehend the abstract distribution shifts can greatly facilitate AI deployment. Motivated by this, we propose a novel task, dataset explanation. Given two image data sets, dataset explanation aims to automatically point out their dataset-level distribution shifts with natural language. Current tec...
[ { "created": "Thu, 30 Jun 2022 04:06:26 GMT", "version": "v1" } ]
2022-07-01
[ [ "Zhu", "Zhiying", "" ], [ "Liang", "Weixin", "" ], [ "Zou", "James", "" ] ]
Helping end users comprehend the abstract distribution shifts can greatly facilitate AI deployment. Motivated by this, we propose a novel task, dataset explanation. Given two image data sets, dataset explanation aims to automatically point out their dataset-level distribution shifts with natural language. Current techn...
1211.2073
Yang Lu
Yang Lu and Mengying Wang and Kenny Q. Zhu and Bo Yuan
LAGE: A Java Framework to reconstruct Gene Regulatory Networks from Large-Scale Continues Expression Data
2 pages
null
null
null
cs.LG cs.CE q-bio.QM stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
LAGE is a systematic framework developed in Java. The motivation of LAGE is to provide a scalable and parallel solution to reconstruct Gene Regulatory Networks (GRNs) from continuous gene expression data for very large amount of genes. The basic idea of our framework is motivated by the philosophy of divideand-conque...
[ { "created": "Fri, 9 Nov 2012 08:34:25 GMT", "version": "v1" } ]
2012-11-12
[ [ "Lu", "Yang", "" ], [ "Wang", "Mengying", "" ], [ "Zhu", "Kenny Q.", "" ], [ "Yuan", "Bo", "" ] ]
LAGE is a systematic framework developed in Java. The motivation of LAGE is to provide a scalable and parallel solution to reconstruct Gene Regulatory Networks (GRNs) from continuous gene expression data for very large amount of genes. The basic idea of our framework is motivated by the philosophy of divideand-conquer....
2305.04719
Zhiling Yan
Shaozu Yuan, Aijun Dai, Zhiling Yan, Ruixue Liu, Meng Chen, Baoyang Chen, Zhijie Qiu, Xiaodong He
Learning to Generate Poetic Chinese Landscape Painting with Calligraphy
Accepted by IJCAI 2022
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we present a novel system (denoted as Polaca) to generate poetic Chinese landscape painting with calligraphy. Unlike previous single image-to-image painting generation, Polaca takes the classic poetry as input and outputs the artistic landscape painting image with the corresponding calligraphy. It is e...
[ { "created": "Mon, 8 May 2023 14:10:10 GMT", "version": "v1" } ]
2023-05-09
[ [ "Yuan", "Shaozu", "" ], [ "Dai", "Aijun", "" ], [ "Yan", "Zhiling", "" ], [ "Liu", "Ruixue", "" ], [ "Chen", "Meng", "" ], [ "Chen", "Baoyang", "" ], [ "Qiu", "Zhijie", "" ], [ "He", "Xiaodong",...
In this paper, we present a novel system (denoted as Polaca) to generate poetic Chinese landscape painting with calligraphy. Unlike previous single image-to-image painting generation, Polaca takes the classic poetry as input and outputs the artistic landscape painting image with the corresponding calligraphy. It is equ...
2102.04875
Parwat Singh Anjana
Parwat Singh Anjana, Sweta Kumari, Sathya Peri, Sachin Rathor, Archit Somani
OptSmart: A Space Efficient Optimistic Concurrent Execution of Smart Contracts
43 pages, 13 figure, 1 Table
null
null
null
cs.DC
http://creativecommons.org/licenses/by/4.0/
Popular blockchains such as Ethereum and several others execute complex transactions in blocks through user-defined scripts known as smart contracts. Serial execution of smart contract transactions/atomic-units (AUs) fails to harness the multiprocessing power offered by the prevalence of multi-core processors. By add...
[ { "created": "Tue, 9 Feb 2021 15:18:42 GMT", "version": "v1" }, { "created": "Wed, 17 Feb 2021 06:20:02 GMT", "version": "v2" } ]
2021-02-18
[ [ "Anjana", "Parwat Singh", "" ], [ "Kumari", "Sweta", "" ], [ "Peri", "Sathya", "" ], [ "Rathor", "Sachin", "" ], [ "Somani", "Archit", "" ] ]
Popular blockchains such as Ethereum and several others execute complex transactions in blocks through user-defined scripts known as smart contracts. Serial execution of smart contract transactions/atomic-units (AUs) fails to harness the multiprocessing power offered by the prevalence of multi-core processors. By addin...
1301.0569
Phan H. Giang
Phan H. Giang, Prakash P. Shenoy
Statistical Decisions Using Likelihood Information Without Prior Probabilities
Appears in Proceedings of the Eighteenth Conference on Uncertainty in Artificial Intelligence (UAI2002)
null
null
UAI-P-2002-PG-170-178
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper presents a decision-theoretic approach to statistical inference that satisfies the likelihood principle (LP) without using prior information. Unlike the Bayesian approach, which also satisfies LP, we do not assume knowledge of the prior distribution of the unknown parameter. With respect to information tha...
[ { "created": "Wed, 12 Dec 2012 15:56:18 GMT", "version": "v1" } ]
2013-01-07
[ [ "Giang", "Phan H.", "" ], [ "Shenoy", "Prakash P.", "" ] ]
This paper presents a decision-theoretic approach to statistical inference that satisfies the likelihood principle (LP) without using prior information. Unlike the Bayesian approach, which also satisfies LP, we do not assume knowledge of the prior distribution of the unknown parameter. With respect to information that ...
2406.17223
Qi Cao
Qi Cao, Qi Chen, Baoming Bai
On Zero-Error Capacity of Graphs with One Edge
null
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we study the zero-error capacity of channels with memory, which are represented by graphs. We provide a method to construct code for any graph with one edge, thereby determining a lower bound on its zero-error capacity. Moreover, this code can achieve zero-error capacity when the symbols in a vertex wi...
[ { "created": "Tue, 25 Jun 2024 02:17:34 GMT", "version": "v1" } ]
2024-06-26
[ [ "Cao", "Qi", "" ], [ "Chen", "Qi", "" ], [ "Bai", "Baoming", "" ] ]
In this paper, we study the zero-error capacity of channels with memory, which are represented by graphs. We provide a method to construct code for any graph with one edge, thereby determining a lower bound on its zero-error capacity. Moreover, this code can achieve zero-error capacity when the symbols in a vertex with...
2408.02231
Agneet Chatterjee
Agneet Chatterjee, Yiran Luo, Tejas Gokhale, Yezhou Yang, Chitta Baral
REVISION: Rendering Tools Enable Spatial Fidelity in Vision-Language Models
Accepted to ECCV 2024. Project Page : https://agneetchatterjee.com/revision/
null
null
null
cs.CV
http://creativecommons.org/licenses/by-sa/4.0/
Text-to-Image (T2I) and multimodal large language models (MLLMs) have been adopted in solutions for several computer vision and multimodal learning tasks. However, it has been found that such vision-language models lack the ability to correctly reason over spatial relationships. To tackle this shortcoming, we develop...
[ { "created": "Mon, 5 Aug 2024 04:51:46 GMT", "version": "v1" } ]
2024-08-06
[ [ "Chatterjee", "Agneet", "" ], [ "Luo", "Yiran", "" ], [ "Gokhale", "Tejas", "" ], [ "Yang", "Yezhou", "" ], [ "Baral", "Chitta", "" ] ]
Text-to-Image (T2I) and multimodal large language models (MLLMs) have been adopted in solutions for several computer vision and multimodal learning tasks. However, it has been found that such vision-language models lack the ability to correctly reason over spatial relationships. To tackle this shortcoming, we develop t...
2003.04992
Hui Wan
Hui Wan
Multi-task Learning with Multi-head Attention for Multi-choice Reading Comprehension
null
null
null
null
cs.CL cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Multiple-choice Machine Reading Comprehension (MRC) is an important and challenging Natural Language Understanding (NLU) task, in which a machine must choose the answer to a question from a set of choices, with the question placed in context of text passages or dialog. In the last a couple of years the NLU field has ...
[ { "created": "Wed, 26 Feb 2020 16:32:25 GMT", "version": "v1" } ]
2020-03-12
[ [ "Wan", "Hui", "" ] ]
Multiple-choice Machine Reading Comprehension (MRC) is an important and challenging Natural Language Understanding (NLU) task, in which a machine must choose the answer to a question from a set of choices, with the question placed in context of text passages or dialog. In the last a couple of years the NLU field has be...
1605.03821
Jian Wang
Liqing Gao, Yanzhang Wang, Xin Ye and Jian Wang
Crowd Counting Considering Network Flow Constraints in Videos
20pages,9 figures
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The growth of the number of people in the monitoring scene may increase the probability of security threat, which makes crowd counting more and more important. Most of the existing approaches estimate the number of pedestrians within one frame, which results in inconsistent predictions in terms of time. This paper, f...
[ { "created": "Thu, 12 May 2016 14:12:21 GMT", "version": "v1" }, { "created": "Fri, 15 Dec 2017 14:22:55 GMT", "version": "v2" } ]
2017-12-18
[ [ "Gao", "Liqing", "" ], [ "Wang", "Yanzhang", "" ], [ "Ye", "Xin", "" ], [ "Wang", "Jian", "" ] ]
The growth of the number of people in the monitoring scene may increase the probability of security threat, which makes crowd counting more and more important. Most of the existing approaches estimate the number of pedestrians within one frame, which results in inconsistent predictions in terms of time. This paper, for...
1810.09798
Fernando Alonso-Fernandez
Fernando Alonso-Fernandez, Josef Bigun, Cristofer Englund
Expression Recognition Using the Periocular Region: A Feasibility Study
Accepted for publication at Intl Conf on Signal Image Technology & Internet Based Systems, SITIS 2018
Proc. Intl Conf on Signal Image Technology & Internet Based Systems, SITIS, Gran Canaria, Spain, 26-29 Nov 2018
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper investigates the feasibility of using the periocular region for expression recognition. Most works have tried to solve this by analyzing the whole face. Periocular is the facial region in the immediate vicinity of the eye. It has the advantage of being available over a wide range of distances and under par...
[ { "created": "Tue, 23 Oct 2018 11:56:20 GMT", "version": "v1" } ]
2020-10-19
[ [ "Alonso-Fernandez", "Fernando", "" ], [ "Bigun", "Josef", "" ], [ "Englund", "Cristofer", "" ] ]
This paper investigates the feasibility of using the periocular region for expression recognition. Most works have tried to solve this by analyzing the whole face. Periocular is the facial region in the immediate vicinity of the eye. It has the advantage of being available over a wide range of distances and under parti...
2003.13883
Wennie Tabib
Wennie Tabib, Kshitij Goel, John Yao, Curtis Boirum and Nathan Michael (Carnegie Mellon University)
Autonomous Cave Surveying with an Aerial Robot
17 pages, 14 figures; accepted for publication in IEEE Transactions on Robotics (TRO 2021) and adds additional experimental results
null
10.1109/TRO.2021.3104459
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper presents a method for cave surveying in total darkness using an autonomous aerial vehicle equipped with a depth camera for mapping, downward-facing camera for state estimation, and forward and downward lights. Traditional methods of cave surveying are labor-intensive and dangerous due to the risk of hypoth...
[ { "created": "Tue, 31 Mar 2020 00:22:04 GMT", "version": "v1" }, { "created": "Sat, 16 Oct 2021 03:32:51 GMT", "version": "v2" } ]
2021-10-19
[ [ "Tabib", "Wennie", "", "Carnegie Mellon University" ], [ "Goel", "Kshitij", "", "Carnegie Mellon University" ], [ "Yao", "John", "", "Carnegie Mellon University" ], [ "Boirum", "Curtis", "", "Carnegie Mellon University" ], [ "Mich...
This paper presents a method for cave surveying in total darkness using an autonomous aerial vehicle equipped with a depth camera for mapping, downward-facing camera for state estimation, and forward and downward lights. Traditional methods of cave surveying are labor-intensive and dangerous due to the risk of hypother...
2008.06101
Xiangyu Guo
Xiangyu Guo, Janardhan Kulkarni, Shi Li, Jiayi Xian
Consistent $k$-Median: Simpler, Better and Robust
null
null
null
null
cs.DS cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper we introduce and study the online consistent $k$-clustering with outliers problem, generalizing the non-outlier version of the problem studied in [Lattanzi-Vassilvitskii, ICML17]. We show that a simple local-search based online algorithm can give a bicriteria constant approximation for the problem wit...
[ { "created": "Thu, 13 Aug 2020 20:24:28 GMT", "version": "v1" } ]
2020-08-17
[ [ "Guo", "Xiangyu", "" ], [ "Kulkarni", "Janardhan", "" ], [ "Li", "Shi", "" ], [ "Xian", "Jiayi", "" ] ]
In this paper we introduce and study the online consistent $k$-clustering with outliers problem, generalizing the non-outlier version of the problem studied in [Lattanzi-Vassilvitskii, ICML17]. We show that a simple local-search based online algorithm can give a bicriteria constant approximation for the problem with $O...
2110.07244
Quan Wang
Quan Wang and Songtai Dai and Benfeng Xu and Yajuan Lyu and Yong Zhu and Hua Wu and Haifeng Wang
Building Chinese Biomedical Language Models via Multi-Level Text Discrimination
null
null
null
null
cs.CL cs.AI
http://creativecommons.org/licenses/by-sa/4.0/
Pre-trained language models (PLMs), such as BERT and GPT, have revolutionized the field of NLP, not only in the general domain but also in the biomedical domain. Most prior efforts in building biomedical PLMs have resorted simply to domain adaptation and focused mainly on English. In this work we introduce eHealth, a...
[ { "created": "Thu, 14 Oct 2021 10:43:28 GMT", "version": "v1" }, { "created": "Wed, 2 Mar 2022 10:04:24 GMT", "version": "v2" } ]
2022-03-03
[ [ "Wang", "Quan", "" ], [ "Dai", "Songtai", "" ], [ "Xu", "Benfeng", "" ], [ "Lyu", "Yajuan", "" ], [ "Zhu", "Yong", "" ], [ "Wu", "Hua", "" ], [ "Wang", "Haifeng", "" ] ]
Pre-trained language models (PLMs), such as BERT and GPT, have revolutionized the field of NLP, not only in the general domain but also in the biomedical domain. Most prior efforts in building biomedical PLMs have resorted simply to domain adaptation and focused mainly on English. In this work we introduce eHealth, a C...
1907.05391
Slobodan Mitrovi\'c
Jakub {\L}\k{a}cki, Slobodan Mitrovi\'c, Krzysztof Onak, Piotr Sankowski
Walking Randomly, Massively, and Efficiently
null
null
null
null
cs.DS cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We introduce a set of techniques that allow for efficiently generating many independent random walks in the Massive Parallel Computation (MPC) model with space per machine strongly sublinear in the number of vertices. In this space-per-machine regime, many natural approaches to graph problems struggle to overcome the...
[ { "created": "Thu, 11 Jul 2019 17:13:26 GMT", "version": "v1" }, { "created": "Sun, 21 Jul 2019 09:30:04 GMT", "version": "v2" }, { "created": "Mon, 28 Oct 2019 09:50:10 GMT", "version": "v3" }, { "created": "Wed, 6 Nov 2019 02:27:31 GMT", "version": "v4" } ]
2019-11-07
[ [ "Łącki", "Jakub", "" ], [ "Mitrović", "Slobodan", "" ], [ "Onak", "Krzysztof", "" ], [ "Sankowski", "Piotr", "" ] ]
We introduce a set of techniques that allow for efficiently generating many independent random walks in the Massive Parallel Computation (MPC) model with space per machine strongly sublinear in the number of vertices. In this space-per-machine regime, many natural approaches to graph problems struggle to overcome the $...
1812.09280
Hichem Sahbi
Hichem Sahbi
Canonical Correlation Analysis for Misaligned Satellite Image Change Detection
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Canonical correlation analysis (CCA) is a statistical learning method that seeks to build view-independent latent representations from multi-view data. This method has been successfully applied to several pattern analysis tasks such as image-to-text mapping and view-invariant object/action recognition. However, this ...
[ { "created": "Fri, 21 Dec 2018 17:43:16 GMT", "version": "v1" } ]
2018-12-24
[ [ "Sahbi", "Hichem", "" ] ]
Canonical correlation analysis (CCA) is a statistical learning method that seeks to build view-independent latent representations from multi-view data. This method has been successfully applied to several pattern analysis tasks such as image-to-text mapping and view-invariant object/action recognition. However, this su...
2402.04794
Chakib Fettal
Chakib Fettal, Lazhar Labiod, Mohamed Nadif
Scalable Multi-view Clustering via Explicit Kernel Features Maps
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A growing awareness of multi-view learning as an important component in data science and machine learning is a consequence of the increasing prevalence of multiple views in real-world applications, especially in the context of networks. In this paper we introduce a new scalability framework for multi-view subspace cl...
[ { "created": "Wed, 7 Feb 2024 12:35:31 GMT", "version": "v1" } ]
2024-02-08
[ [ "Fettal", "Chakib", "" ], [ "Labiod", "Lazhar", "" ], [ "Nadif", "Mohamed", "" ] ]
A growing awareness of multi-view learning as an important component in data science and machine learning is a consequence of the increasing prevalence of multiple views in real-world applications, especially in the context of networks. In this paper we introduce a new scalability framework for multi-view subspace clus...
2310.05804
Haoyu Zhang
Haoyu Zhang, Yu Wang, Guanghao Yin, Kejun Liu, Yuanyuan Liu, Tianshu Yu
Learning Language-guided Adaptive Hyper-modality Representation for Multimodal Sentiment Analysis
Published in EMNLP 2023
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
10.18653/v1/2023.emnlp-main.49
null
cs.AI cs.CL cs.CV cs.MM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Though Multimodal Sentiment Analysis (MSA) proves effective by utilizing rich information from multiple sources (e.g., language, video, and audio), the potential sentiment-irrelevant and conflicting information across modalities may hinder the performance from being further improved. To alleviate this, we present Ada...
[ { "created": "Mon, 9 Oct 2023 15:43:07 GMT", "version": "v1" }, { "created": "Thu, 14 Dec 2023 13:07:45 GMT", "version": "v2" } ]
2023-12-15
[ [ "Zhang", "Haoyu", "" ], [ "Wang", "Yu", "" ], [ "Yin", "Guanghao", "" ], [ "Liu", "Kejun", "" ], [ "Liu", "Yuanyuan", "" ], [ "Yu", "Tianshu", "" ] ]
Though Multimodal Sentiment Analysis (MSA) proves effective by utilizing rich information from multiple sources (e.g., language, video, and audio), the potential sentiment-irrelevant and conflicting information across modalities may hinder the performance from being further improved. To alleviate this, we present Adapt...
1903.09766
Md Jahidul Islam
Md Jahidul Islam, Youya Xia and Junaed Sattar
Fast Underwater Image Enhancement for Improved Visual Perception
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we present a conditional generative adversarial network-based model for real-time underwater image enhancement. To supervise the adversarial training, we formulate an objective function that evaluates the perceptual image quality based on its global content, color, local texture, and style information....
[ { "created": "Sat, 23 Mar 2019 05:21:05 GMT", "version": "v1" }, { "created": "Wed, 18 Dec 2019 23:40:48 GMT", "version": "v2" }, { "created": "Sun, 9 Feb 2020 02:06:40 GMT", "version": "v3" } ]
2020-02-11
[ [ "Islam", "Md Jahidul", "" ], [ "Xia", "Youya", "" ], [ "Sattar", "Junaed", "" ] ]
In this paper, we present a conditional generative adversarial network-based model for real-time underwater image enhancement. To supervise the adversarial training, we formulate an objective function that evaluates the perceptual image quality based on its global content, color, local texture, and style information. W...
2308.08741
Jiazhao Zhang
Yijie Tang, Jiazhao Zhang, Zhinan Yu, He Wang, Kai Xu
MIPS-Fusion: Multi-Implicit-Submaps for Scalable and Robust Online Neural RGB-D Reconstruction
null
null
null
null
cs.CV cs.GR
http://creativecommons.org/licenses/by/4.0/
We introduce MIPS-Fusion, a robust and scalable online RGB-D reconstruction method based on a novel neural implicit representation -- multi-implicit-submap. Different from existing neural RGB-D reconstruction methods lacking either flexibility with a single neural map or scalability due to extra storage of feature gr...
[ { "created": "Thu, 17 Aug 2023 02:33:16 GMT", "version": "v1" }, { "created": "Thu, 24 Aug 2023 15:43:17 GMT", "version": "v2" } ]
2023-08-25
[ [ "Tang", "Yijie", "" ], [ "Zhang", "Jiazhao", "" ], [ "Yu", "Zhinan", "" ], [ "Wang", "He", "" ], [ "Xu", "Kai", "" ] ]
We introduce MIPS-Fusion, a robust and scalable online RGB-D reconstruction method based on a novel neural implicit representation -- multi-implicit-submap. Different from existing neural RGB-D reconstruction methods lacking either flexibility with a single neural map or scalability due to extra storage of feature grid...
2402.07645
Isabelle Lorge PhD
Isabelle Lorge, Dan W. Joyce, Niall Taylor, Alejo Nevado-Holgado, Andrea Cipriani, Andrey Kormilitzin
Detecting the Clinical Features of Difficult-to-Treat Depression using Synthetic Data from Large Language Models
null
null
null
null
cs.CL
http://creativecommons.org/licenses/by-nc-sa/4.0/
Difficult-to-treat depression (DTD) has been proposed as a broader and more clinically comprehensive perspective on a person's depressive disorder where despite treatment, they continue to experience significant burden. We sought to develop a Large Language Model (LLM)-based tool capable of interrogating routinely-co...
[ { "created": "Mon, 12 Feb 2024 13:34:33 GMT", "version": "v1" } ]
2024-02-13
[ [ "Lorge", "Isabelle", "" ], [ "Joyce", "Dan W.", "" ], [ "Taylor", "Niall", "" ], [ "Nevado-Holgado", "Alejo", "" ], [ "Cipriani", "Andrea", "" ], [ "Kormilitzin", "Andrey", "" ] ]
Difficult-to-treat depression (DTD) has been proposed as a broader and more clinically comprehensive perspective on a person's depressive disorder where despite treatment, they continue to experience significant burden. We sought to develop a Large Language Model (LLM)-based tool capable of interrogating routinely-coll...
2408.06747
Jingyun Wang
Jingyun Wang and Guoliang Kang
ReCLIP++: Learn to Rectify the Bias of CLIP for Unsupervised Semantic Segmentation
Extended version of our CVPR 24 paper
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recent works utilize CLIP to perform the challenging unsupervised semantic segmentation task where only images without annotations are available. However, we observe that when adopting CLIP to such a pixel-level understanding task, unexpected bias (including class-preference bias and space-preference bias) occurs. Pr...
[ { "created": "Tue, 13 Aug 2024 09:10:48 GMT", "version": "v1" } ]
2024-08-14
[ [ "Wang", "Jingyun", "" ], [ "Kang", "Guoliang", "" ] ]
Recent works utilize CLIP to perform the challenging unsupervised semantic segmentation task where only images without annotations are available. However, we observe that when adopting CLIP to such a pixel-level understanding task, unexpected bias (including class-preference bias and space-preference bias) occurs. Prev...
2106.15166
Taekho You
Taekho You, Jinseo Park, June Young Lee, Jinhyuk Yun, Woo-Sung Jung
Disturbance of questionable publishing to academia
16 pages of main text including 4 figures + 42 pages of supplementary information including 38 supplementary figures
Journal of Informetrics, 2022, 16(2), 101294
10.1016/j.joi.2022.101294
null
cs.DL physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Questionable publications have been accused of "greedy" practices; however, their influence on academia has not been gauged. Here, we probe the impact of questionable publications through a systematic and comprehensive analysis with various participants from academia and compare the results with those of their unaccu...
[ { "created": "Tue, 29 Jun 2021 08:26:39 GMT", "version": "v1" }, { "created": "Tue, 6 Jul 2021 07:42:56 GMT", "version": "v2" }, { "created": "Mon, 7 Mar 2022 02:41:34 GMT", "version": "v3" }, { "created": "Tue, 19 Apr 2022 13:18:20 GMT", "version": "v4" } ]
2022-05-10
[ [ "You", "Taekho", "" ], [ "Park", "Jinseo", "" ], [ "Lee", "June Young", "" ], [ "Yun", "Jinhyuk", "" ], [ "Jung", "Woo-Sung", "" ] ]
Questionable publications have been accused of "greedy" practices; however, their influence on academia has not been gauged. Here, we probe the impact of questionable publications through a systematic and comprehensive analysis with various participants from academia and compare the results with those of their unaccuse...
2403.05156
Minghui Xu
Biwei Yan, Kun Li, Minghui Xu, Yueyan Dong, Yue Zhang, Zhaochun Ren and Xiuzhen Cheng
On Protecting the Data Privacy of Large Language Models (LLMs): A Survey
18 pages, 4 figures
null
null
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Large language models (LLMs) are complex artificial intelligence systems capable of understanding, generating and translating human language. They learn language patterns by analyzing large amounts of text data, allowing them to perform writing, conversation, summarizing and other language tasks. When LLMs process an...
[ { "created": "Fri, 8 Mar 2024 08:47:48 GMT", "version": "v1" }, { "created": "Thu, 14 Mar 2024 14:17:57 GMT", "version": "v2" } ]
2024-03-15
[ [ "Yan", "Biwei", "" ], [ "Li", "Kun", "" ], [ "Xu", "Minghui", "" ], [ "Dong", "Yueyan", "" ], [ "Zhang", "Yue", "" ], [ "Ren", "Zhaochun", "" ], [ "Cheng", "Xiuzhen", "" ] ]
Large language models (LLMs) are complex artificial intelligence systems capable of understanding, generating and translating human language. They learn language patterns by analyzing large amounts of text data, allowing them to perform writing, conversation, summarizing and other language tasks. When LLMs process and ...
2403.03473
Xinwei Ou
Xinwei Ou, Ce Zhu, Xiaolin Huang, and Yipeng Liu
Inverse-Free Fast Natural Gradient Descent Method for Deep Learning
null
null
null
null
cs.LG cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Second-order optimization techniques have the potential to achieve faster convergence rates compared to first-order methods through the incorporation of second-order derivatives or statistics. However, their utilization in deep learning is limited due to their computational inefficiency. Various approaches have been ...
[ { "created": "Wed, 6 Mar 2024 05:13:28 GMT", "version": "v1" }, { "created": "Sun, 28 Apr 2024 10:52:32 GMT", "version": "v2" } ]
2024-04-30
[ [ "Ou", "Xinwei", "" ], [ "Zhu", "Ce", "" ], [ "Huang", "Xiaolin", "" ], [ "Liu", "Yipeng", "" ] ]
Second-order optimization techniques have the potential to achieve faster convergence rates compared to first-order methods through the incorporation of second-order derivatives or statistics. However, their utilization in deep learning is limited due to their computational inefficiency. Various approaches have been pr...
2209.03447
Yulai Zhao
Yulai Zhao, Jianshu Chen, Simon S. Du
Blessing of Class Diversity in Pre-training
AISTATS 2023 (Oral)
null
null
null
cs.LG stat.ML
http://creativecommons.org/licenses/by/4.0/
This paper presents a new statistical analysis aiming to explain the recent superior achievements of the pre-training techniques in natural language processing (NLP). We prove that when the classes of the pre-training task (e.g., different words in the masked language model task) are sufficiently diverse, in the sens...
[ { "created": "Wed, 7 Sep 2022 20:10:12 GMT", "version": "v1" }, { "created": "Mon, 12 Sep 2022 15:44:41 GMT", "version": "v2" }, { "created": "Sun, 12 Feb 2023 17:45:39 GMT", "version": "v3" } ]
2023-02-14
[ [ "Zhao", "Yulai", "" ], [ "Chen", "Jianshu", "" ], [ "Du", "Simon S.", "" ] ]
This paper presents a new statistical analysis aiming to explain the recent superior achievements of the pre-training techniques in natural language processing (NLP). We prove that when the classes of the pre-training task (e.g., different words in the masked language model task) are sufficiently diverse, in the sense ...