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2403.12702
Haoyuan Li
Haoyuan Li, Chang Xu, Wen Yang, Huai Yu, Gui-Song Xia
Learning Cross-view Visual Geo-localization without Ground Truth
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Cross-View Geo-Localization (CVGL) involves determining the geographical location of a query image by matching it with a corresponding GPS-tagged reference image. Current state-of-the-art methods predominantly rely on training models with labeled paired images, incurring substantial annotation costs and training burd...
[ { "created": "Tue, 19 Mar 2024 13:01:57 GMT", "version": "v1" } ]
2024-03-20
[ [ "Li", "Haoyuan", "" ], [ "Xu", "Chang", "" ], [ "Yang", "Wen", "" ], [ "Yu", "Huai", "" ], [ "Xia", "Gui-Song", "" ] ]
Cross-View Geo-Localization (CVGL) involves determining the geographical location of a query image by matching it with a corresponding GPS-tagged reference image. Current state-of-the-art methods predominantly rely on training models with labeled paired images, incurring substantial annotation costs and training burden...
2011.11706
Hossein Jowhari
Hossein Jowhari
An Estimator for Matching Size in Low Arboricity Graphs with Two Applications
null
null
null
null
cs.DS
http://creativecommons.org/licenses/by/4.0/
In this paper, we present a new simple degree-based estimator for the size of maximum matching in bounded arboricity graphs. When the arboricity of the graph is bounded by $\alpha$, the estimator gives a $\alpha+2$ factor approximation of the matching size. For planar graphs, we show the estimator does better and ret...
[ { "created": "Mon, 23 Nov 2020 20:19:48 GMT", "version": "v1" }, { "created": "Wed, 25 Nov 2020 05:11:44 GMT", "version": "v2" } ]
2020-11-26
[ [ "Jowhari", "Hossein", "" ] ]
In this paper, we present a new simple degree-based estimator for the size of maximum matching in bounded arboricity graphs. When the arboricity of the graph is bounded by $\alpha$, the estimator gives a $\alpha+2$ factor approximation of the matching size. For planar graphs, we show the estimator does better and retur...
1204.4253
Chun Tung Chou
Chun Tung Chou
Extended master equation models for molecular communication networks
IEEE Transactions on Nanobioscience, 2013
null
10.1109/TNB.2013.2237785
null
cs.CE physics.bio-ph q-bio.QM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We consider molecular communication networks consisting of transmitters and receivers distributed in a fluidic medium. In such networks, a transmitter sends one or more signalling molecules, which are diffused over the medium, to the receiver to realise the communication. In order to be able to engineer synthetic mol...
[ { "created": "Thu, 19 Apr 2012 05:28:34 GMT", "version": "v1" }, { "created": "Fri, 20 Apr 2012 12:50:29 GMT", "version": "v2" }, { "created": "Mon, 17 Dec 2012 04:57:22 GMT", "version": "v3" }, { "created": "Thu, 3 Jan 2013 11:15:29 GMT", "version": "v4" }, { "cr...
2015-03-20
[ [ "Chou", "Chun Tung", "" ] ]
We consider molecular communication networks consisting of transmitters and receivers distributed in a fluidic medium. In such networks, a transmitter sends one or more signalling molecules, which are diffused over the medium, to the receiver to realise the communication. In order to be able to engineer synthetic molec...
2105.14850
Lin Zheng
Lin Zheng, Zhiyong Wu, Lingpeng Kong
Cascaded Head-colliding Attention
ACL 2021 Camera-ready version
null
null
null
cs.CL cs.LG
http://creativecommons.org/licenses/by/4.0/
Transformers have advanced the field of natural language processing (NLP) on a variety of important tasks. At the cornerstone of the Transformer architecture is the multi-head attention (MHA) mechanism which models pairwise interactions between the elements of the sequence. Despite its massive success, the current fr...
[ { "created": "Mon, 31 May 2021 10:06:42 GMT", "version": "v1" } ]
2021-06-01
[ [ "Zheng", "Lin", "" ], [ "Wu", "Zhiyong", "" ], [ "Kong", "Lingpeng", "" ] ]
Transformers have advanced the field of natural language processing (NLP) on a variety of important tasks. At the cornerstone of the Transformer architecture is the multi-head attention (MHA) mechanism which models pairwise interactions between the elements of the sequence. Despite its massive success, the current fram...
1007.0496
Matthew Mckay Dr.
Yang Chen and Matthew R. McKay
Perturbed Hankel Determinants: Applications to the Information Theory of MIMO Wireless Communications
77 pages; 6 figures
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper we compute two important information-theoretic quantities which arise in the application of multiple-input multiple-output (MIMO) antenna wireless communication systems: the distribution of the mutual information of multi-antenna Gaussian channels, and the Gallager random coding upper bound on the error...
[ { "created": "Sat, 3 Jul 2010 13:52:53 GMT", "version": "v1" } ]
2010-07-06
[ [ "Chen", "Yang", "" ], [ "McKay", "Matthew R.", "" ] ]
In this paper we compute two important information-theoretic quantities which arise in the application of multiple-input multiple-output (MIMO) antenna wireless communication systems: the distribution of the mutual information of multi-antenna Gaussian channels, and the Gallager random coding upper bound on the error p...
2309.01472
Timur Sattarov
Timur Sattarov, Marco Schreyer, Damian Borth
FinDiff: Diffusion Models for Financial Tabular Data Generation
9 pages, 5 figures, 3 tables, preprint version, currently under review
null
null
null
cs.LG q-fin.ST
http://creativecommons.org/licenses/by-nc-nd/4.0/
The sharing of microdata, such as fund holdings and derivative instruments, by regulatory institutions presents a unique challenge due to strict data confidentiality and privacy regulations. These challenges often hinder the ability of both academics and practitioners to conduct collaborative research effectively. Th...
[ { "created": "Mon, 4 Sep 2023 09:30:15 GMT", "version": "v1" } ]
2023-09-06
[ [ "Sattarov", "Timur", "" ], [ "Schreyer", "Marco", "" ], [ "Borth", "Damian", "" ] ]
The sharing of microdata, such as fund holdings and derivative instruments, by regulatory institutions presents a unique challenge due to strict data confidentiality and privacy regulations. These challenges often hinder the ability of both academics and practitioners to conduct collaborative research effectively. The ...
2204.02675
Chen Yan
Chen Yan, Zhijian Xu, Zhanyuan Yin, Xiaoyu Ji, Wenyuan Xu
Rolling Colors: Adversarial Laser Exploits against Traffic Light Recognition
To be published in USENIX Security 2022
null
null
null
cs.CV cs.CR
http://creativecommons.org/licenses/by-nc-nd/4.0/
Traffic light recognition is essential for fully autonomous driving in urban areas. In this paper, we investigate the feasibility of fooling traffic light recognition mechanisms by shedding laser interference on the camera. By exploiting the rolling shutter of CMOS sensors, we manage to inject a color stripe overlapp...
[ { "created": "Wed, 6 Apr 2022 08:57:25 GMT", "version": "v1" } ]
2022-04-07
[ [ "Yan", "Chen", "" ], [ "Xu", "Zhijian", "" ], [ "Yin", "Zhanyuan", "" ], [ "Ji", "Xiaoyu", "" ], [ "Xu", "Wenyuan", "" ] ]
Traffic light recognition is essential for fully autonomous driving in urban areas. In this paper, we investigate the feasibility of fooling traffic light recognition mechanisms by shedding laser interference on the camera. By exploiting the rolling shutter of CMOS sensors, we manage to inject a color stripe overlapped...
1711.09255
Atchutananda Surampudi
Atchutananda Surampudi, Krishnamoorthy Kalimuthu
An Energy Efficient Spectrum Sensing in Cognitive Radio Wireless Sensor Networks
null
null
null
null
cs.IT math.IT
http://creativecommons.org/licenses/by/4.0/
The cognitive radio wireless sensor networks have become an integral part of communicating spectrum information to the fusion center, in a cooperative spectrum sensing environment. A group of battery operated sensors or nodes, sensing information about spectrum availability in the radio links, needs an energy efficie...
[ { "created": "Sat, 25 Nov 2017 16:03:29 GMT", "version": "v1" } ]
2017-11-28
[ [ "Surampudi", "Atchutananda", "" ], [ "Kalimuthu", "Krishnamoorthy", "" ] ]
The cognitive radio wireless sensor networks have become an integral part of communicating spectrum information to the fusion center, in a cooperative spectrum sensing environment. A group of battery operated sensors or nodes, sensing information about spectrum availability in the radio links, needs an energy efficient...
2405.03801
Daniel Li
Kevin Hua, Daniel Li, Jaewoo Park, Thatchaphol Saranurak
Finding Most Shattering Minimum Vertex Cuts of Polylogarithmic Size in Near-Linear Time
Appears at ICALP 2024
null
10.4230/LIPIcs.ICALP.2024.87
null
cs.DS
http://creativecommons.org/licenses/by/4.0/
We show the first near-linear time randomized algorithms for listing all minimum vertex cuts of polylogarithmic size that separate the graph into at least three connected components (also known as shredders) and for finding the most shattering one, i.e., the one maximizing the number of connected components. Our algo...
[ { "created": "Mon, 6 May 2024 19:16:14 GMT", "version": "v1" }, { "created": "Thu, 11 Jul 2024 18:18:37 GMT", "version": "v2" } ]
2024-07-15
[ [ "Hua", "Kevin", "" ], [ "Li", "Daniel", "" ], [ "Park", "Jaewoo", "" ], [ "Saranurak", "Thatchaphol", "" ] ]
We show the first near-linear time randomized algorithms for listing all minimum vertex cuts of polylogarithmic size that separate the graph into at least three connected components (also known as shredders) and for finding the most shattering one, i.e., the one maximizing the number of connected components. Our algori...
1412.5949
Pengtao Xie
Pengtao Xie and Eric Xing
Large Scale Distributed Distance Metric Learning
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In large scale machine learning and data mining problems with high feature dimensionality, the Euclidean distance between data points can be uninformative, and Distance Metric Learning (DML) is often desired to learn a proper similarity measure (using side information such as example data pairs being similar or dissi...
[ { "created": "Thu, 18 Dec 2014 17:14:34 GMT", "version": "v1" } ]
2014-12-19
[ [ "Xie", "Pengtao", "" ], [ "Xing", "Eric", "" ] ]
In large scale machine learning and data mining problems with high feature dimensionality, the Euclidean distance between data points can be uninformative, and Distance Metric Learning (DML) is often desired to learn a proper similarity measure (using side information such as example data pairs being similar or dissimi...
2201.01693
Diptesh Kanojia
Diptesh Kanojia, Malhar Kulkarni, Sayali Ghodekar, Eivind Kahrs, Pushpak Bhattacharyya
Strategies of Effective Digitization of Commentaries and Sub-commentaries: Towards the Construction of Textual History
Accepted at TCDK @ SSSU 2020; ISBN: 978-93-83097-43-2; Pages 477--489
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
This paper describes additional aspects of a digital tool called the 'Textual History Tool'. We describe its various salient features with special reference to those of its features that may help the philologist digitize commentaries and sub-commentaries on a text. This tool captures the historical evolution of a tex...
[ { "created": "Wed, 5 Jan 2022 16:43:43 GMT", "version": "v1" } ]
2022-01-06
[ [ "Kanojia", "Diptesh", "" ], [ "Kulkarni", "Malhar", "" ], [ "Ghodekar", "Sayali", "" ], [ "Kahrs", "Eivind", "" ], [ "Bhattacharyya", "Pushpak", "" ] ]
This paper describes additional aspects of a digital tool called the 'Textual History Tool'. We describe its various salient features with special reference to those of its features that may help the philologist digitize commentaries and sub-commentaries on a text. This tool captures the historical evolution of a text ...
1309.5149
EPTCS
Martin Bodin (ENS Lyon and Inria), Thomas Jensen (Inria), Alan Schmitt (Inria)
Pretty-big-step-semantics-based Certified Abstract Interpretation (Preliminary version)
In Proceedings Festschrift for Dave Schmidt, arXiv:1309.4557
EPTCS 129, 2013, pp. 360-383
10.4204/EPTCS.129.23
null
cs.PL cs.LO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present a technique for deriving semantic program analyses from a natural semantics specification of the programming language. The technique is based on a particular kind of semantics called pretty-big-step semantics. We present a pretty-big-step semantics of a language with simple objects called O'While and speci...
[ { "created": "Fri, 20 Sep 2013 01:46:06 GMT", "version": "v1" } ]
2013-09-23
[ [ "Bodin", "Martin", "", "ENS Lyon and Inria" ], [ "Jensen", "Thomas", "", "Inria" ], [ "Schmitt", "Alan", "", "Inria" ] ]
We present a technique for deriving semantic program analyses from a natural semantics specification of the programming language. The technique is based on a particular kind of semantics called pretty-big-step semantics. We present a pretty-big-step semantics of a language with simple objects called O'While and specify...
2109.01904
Athanasios Vlontzos
Athanasios Vlontzos, Bernhard Kainz, Ciaran M. Gilligan-Lee
Estimating Categorical Counterfactuals via Deep Twin Networks
null
null
null
null
cs.LG cs.AI
http://creativecommons.org/licenses/by/4.0/
Counterfactual inference is a powerful tool, capable of solving challenging problems in high-profile sectors. To perform counterfactual inference, one requires knowledge of the underlying causal mechanisms. However, causal mechanisms cannot be uniquely determined from observations and interventions alone. This raises...
[ { "created": "Sat, 4 Sep 2021 17:11:43 GMT", "version": "v1" }, { "created": "Tue, 7 Sep 2021 08:19:15 GMT", "version": "v2" }, { "created": "Mon, 23 May 2022 12:33:53 GMT", "version": "v3" }, { "created": "Thu, 16 Jun 2022 08:46:47 GMT", "version": "v4" }, { "cre...
2023-01-23
[ [ "Vlontzos", "Athanasios", "" ], [ "Kainz", "Bernhard", "" ], [ "Gilligan-Lee", "Ciaran M.", "" ] ]
Counterfactual inference is a powerful tool, capable of solving challenging problems in high-profile sectors. To perform counterfactual inference, one requires knowledge of the underlying causal mechanisms. However, causal mechanisms cannot be uniquely determined from observations and interventions alone. This raises t...
1904.12622
Cory Cornelius
Cory Cornelius, Shang-Tse Chen, Jason Martin, Duen Horng Chau
Talk Proposal: Towards the Realistic Evaluation of Evasion Attacks using CARLA
Submitted as talk proposal to Dependable and Secure Machine Learning (DSML '19)
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this talk we describe our content-preserving attack on object detectors, ShapeShifter, and demonstrate how to evaluate this threat in realistic scenarios. We describe how we use CARLA, a realistic urban driving simulator, to create these scenarios, and how we use ShapeShifter to generate content-preserving attacks...
[ { "created": "Thu, 18 Apr 2019 22:01:53 GMT", "version": "v1" } ]
2019-04-30
[ [ "Cornelius", "Cory", "" ], [ "Chen", "Shang-Tse", "" ], [ "Martin", "Jason", "" ], [ "Chau", "Duen Horng", "" ] ]
In this talk we describe our content-preserving attack on object detectors, ShapeShifter, and demonstrate how to evaluate this threat in realistic scenarios. We describe how we use CARLA, a realistic urban driving simulator, to create these scenarios, and how we use ShapeShifter to generate content-preserving attacks a...
1804.08584
Kevin Xu
Ruthwik R. Junuthula, Kevin S. Xu, and Vijay K. Devabhaktuni
Leveraging Friendship Networks for Dynamic Link Prediction in Social Interaction Networks
To appear in ICWSM 2018. This version corrects some minor errors in Table 1. MATLAB code available at https://github.com/IdeasLabUT/Friendship-Interaction-Prediction
null
null
null
cs.SI physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
On-line social networks (OSNs) often contain many different types of relationships between users. When studying the structure of OSNs such as Facebook, two of the most commonly studied networks are friendship and interaction networks. The link prediction problem in friendship networks has been heavily studied. There ...
[ { "created": "Mon, 23 Apr 2018 17:23:19 GMT", "version": "v1" } ]
2018-04-24
[ [ "Junuthula", "Ruthwik R.", "" ], [ "Xu", "Kevin S.", "" ], [ "Devabhaktuni", "Vijay K.", "" ] ]
On-line social networks (OSNs) often contain many different types of relationships between users. When studying the structure of OSNs such as Facebook, two of the most commonly studied networks are friendship and interaction networks. The link prediction problem in friendship networks has been heavily studied. There ha...
2107.10474
Jung Hoon Lee
Junghoon Lee, Jounghee Kim, Pilsung Kang
Back-Translated Task Adaptive Pretraining: Improving Accuracy and Robustness on Text Classification
null
null
null
null
cs.CL cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Language models (LMs) pretrained on a large text corpus and fine-tuned on a downstream text corpus and fine-tuned on a downstream task becomes a de facto training strategy for several natural language processing (NLP) tasks. Recently, an adaptive pretraining method retraining the pretrained language model with task-r...
[ { "created": "Thu, 22 Jul 2021 06:27:35 GMT", "version": "v1" } ]
2021-07-23
[ [ "Lee", "Junghoon", "" ], [ "Kim", "Jounghee", "" ], [ "Kang", "Pilsung", "" ] ]
Language models (LMs) pretrained on a large text corpus and fine-tuned on a downstream text corpus and fine-tuned on a downstream task becomes a de facto training strategy for several natural language processing (NLP) tasks. Recently, an adaptive pretraining method retraining the pretrained language model with task-rel...
2401.02150
Mei Wang
Mei Wang, Weihong Deng, Sen Su
Marginal Debiased Network for Fair Visual Recognition
null
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Deep neural networks (DNNs) are often prone to learn the spurious correlations between target classes and bias attributes, like gender and race, inherent in a major portion of training data (bias-aligned samples), thus showing unfair behavior and arising controversy in the modern pluralistic and egalitarian society. ...
[ { "created": "Thu, 4 Jan 2024 08:57:09 GMT", "version": "v1" } ]
2024-01-05
[ [ "Wang", "Mei", "" ], [ "Deng", "Weihong", "" ], [ "Su", "Sen", "" ] ]
Deep neural networks (DNNs) are often prone to learn the spurious correlations between target classes and bias attributes, like gender and race, inherent in a major portion of training data (bias-aligned samples), thus showing unfair behavior and arising controversy in the modern pluralistic and egalitarian society. In...
1806.00920
Chih-Chieh Shao
Chih Chieh Shao, Trois Liu, Yuting Lai, Yiying Tseng and Sam Tsai
DRCD: a Chinese Machine Reading Comprehension Dataset
5 pages
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
In this paper, we introduce DRCD (Delta Reading Comprehension Dataset), an open domain traditional Chinese machine reading comprehension (MRC) dataset. This dataset aimed to be a standard Chinese machine reading comprehension dataset, which can be a source dataset in transfer learning. The dataset contains 10,014 par...
[ { "created": "Mon, 4 Jun 2018 01:50:21 GMT", "version": "v1" }, { "created": "Wed, 20 Jun 2018 02:55:38 GMT", "version": "v2" }, { "created": "Wed, 29 May 2019 02:55:39 GMT", "version": "v3" } ]
2019-05-30
[ [ "Shao", "Chih Chieh", "" ], [ "Liu", "Trois", "" ], [ "Lai", "Yuting", "" ], [ "Tseng", "Yiying", "" ], [ "Tsai", "Sam", "" ] ]
In this paper, we introduce DRCD (Delta Reading Comprehension Dataset), an open domain traditional Chinese machine reading comprehension (MRC) dataset. This dataset aimed to be a standard Chinese machine reading comprehension dataset, which can be a source dataset in transfer learning. The dataset contains 10,014 parag...
1301.1385
Michael Fink
Mario Alviano and Wolfgang Faber
Translating NP-SPEC into ASP
Proceedings of Answer Set Programming and Other Computing Paradigms (ASPOCP 2012), 5th International Workshop, September 4, 2012, Budapest, Hungary
null
null
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
NP-SPEC is a language for specifying problems in NP in a declarative way. Despite the fact that the semantics of the language was given by referring to Datalog with circumscription, which is very close to ASP, so far the only existing implementations are by means of ECLiPSe Prolog and via Boolean satisfiability solve...
[ { "created": "Tue, 8 Jan 2013 02:28:49 GMT", "version": "v1" } ]
2013-01-09
[ [ "Alviano", "Mario", "" ], [ "Faber", "Wolfgang", "" ] ]
NP-SPEC is a language for specifying problems in NP in a declarative way. Despite the fact that the semantics of the language was given by referring to Datalog with circumscription, which is very close to ASP, so far the only existing implementations are by means of ECLiPSe Prolog and via Boolean satisfiability solvers...
0906.3323
Andriy Myronenko
Andriy Myronenko, Xubo Song
Adaptive Regularization of Ill-Posed Problems: Application to Non-rigid Image Registration
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We introduce an adaptive regularization approach. In contrast to conventional Tikhonov regularization, which specifies a fixed regularization operator, we estimate it simultaneously with parameters. From a Bayesian perspective we estimate the prior distribution on parameters assuming that it is close to some given mo...
[ { "created": "Wed, 17 Jun 2009 23:24:38 GMT", "version": "v1" } ]
2009-06-19
[ [ "Myronenko", "Andriy", "" ], [ "Song", "Xubo", "" ] ]
We introduce an adaptive regularization approach. In contrast to conventional Tikhonov regularization, which specifies a fixed regularization operator, we estimate it simultaneously with parameters. From a Bayesian perspective we estimate the prior distribution on parameters assuming that it is close to some given mode...
2312.07991
Alon Mor
Alon Mor, Yonatan Belinkov, Benny Kimelfeld
Accelerating the Global Aggregation of Local Explanations
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Local explanation methods highlight the input tokens that have a considerable impact on the outcome of classifying the document at hand. For example, the Anchor algorithm applies a statistical analysis of the sensitivity of the classifier to changes in the token. Aggregating local explanations over a dataset provides...
[ { "created": "Wed, 13 Dec 2023 09:03:01 GMT", "version": "v1" }, { "created": "Sat, 23 Dec 2023 11:14:06 GMT", "version": "v2" }, { "created": "Fri, 12 Jan 2024 14:18:57 GMT", "version": "v3" } ]
2024-01-15
[ [ "Mor", "Alon", "" ], [ "Belinkov", "Yonatan", "" ], [ "Kimelfeld", "Benny", "" ] ]
Local explanation methods highlight the input tokens that have a considerable impact on the outcome of classifying the document at hand. For example, the Anchor algorithm applies a statistical analysis of the sensitivity of the classifier to changes in the token. Aggregating local explanations over a dataset provides a...
1303.3964
Mahyuddin K. M. Nasution
Mahyuddin K. M. Nasution
Simple Search Engine Model: Selective Properties
6 pages
null
null
null
cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper we study the relationship between query and search engine by exploring the selective properties based on a simple search engine. We used the set theory and utilized the words and terms for defining singleton and doubleton in the event spaces and then provided their implementation for proving the existen...
[ { "created": "Sat, 16 Mar 2013 10:21:33 GMT", "version": "v1" } ]
2013-03-19
[ [ "Nasution", "Mahyuddin K. M.", "" ] ]
In this paper we study the relationship between query and search engine by exploring the selective properties based on a simple search engine. We used the set theory and utilized the words and terms for defining singleton and doubleton in the event spaces and then provided their implementation for proving the existence...
1605.06296
Naresh Manwani
Aritra Ghosh, Naresh Manwani, P. S. Sastry
On the Robustness of Decision Tree Learning under Label Noise
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In most practical problems of classifier learning, the training data suffers from the label noise. Hence, it is important to understand how robust is a learning algorithm to such label noise. This paper presents some theoretical analysis to show that many popular decision tree algorithms are robust to symmetric label...
[ { "created": "Fri, 20 May 2016 11:31:26 GMT", "version": "v1" }, { "created": "Fri, 26 Aug 2016 08:58:06 GMT", "version": "v2" } ]
2016-08-29
[ [ "Ghosh", "Aritra", "" ], [ "Manwani", "Naresh", "" ], [ "Sastry", "P. S.", "" ] ]
In most practical problems of classifier learning, the training data suffers from the label noise. Hence, it is important to understand how robust is a learning algorithm to such label noise. This paper presents some theoretical analysis to show that many popular decision tree algorithms are robust to symmetric label n...
1911.08600
Artem Kaznatcheev
David A. Cohen, Martin C. Cooper, Artem Kaznatcheev, Mark Wallace
Steepest ascent can be exponential in bounded treewidth problems
8 pages main text, 4 pages appendix, 1 page references; fixed error in f(a,b) to match code
Operations Research Letters 48 (2020) 217-224
10.1016/j.orl.2020.02.010
null
cs.DM cs.DS cs.NE q-bio.PE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We investigate the complexity of local search based on steepest ascent. We show that even when all variables have domains of size two and the underlying constraint graph of variable interactions has bounded treewidth (in our construction, treewidth 7), there are fitness landscapes for which an exponential number of s...
[ { "created": "Tue, 19 Nov 2019 21:42:08 GMT", "version": "v1" }, { "created": "Mon, 2 Dec 2019 14:42:33 GMT", "version": "v2" } ]
2020-05-18
[ [ "Cohen", "David A.", "" ], [ "Cooper", "Martin C.", "" ], [ "Kaznatcheev", "Artem", "" ], [ "Wallace", "Mark", "" ] ]
We investigate the complexity of local search based on steepest ascent. We show that even when all variables have domains of size two and the underlying constraint graph of variable interactions has bounded treewidth (in our construction, treewidth 7), there are fitness landscapes for which an exponential number of ste...
2210.05174
Tianheng Cheng
Tianheng Cheng and Xinggang Wang and Shaoyu Chen and Qian Zhang and Wenyu Liu
BoxTeacher: Exploring High-Quality Pseudo Labels for Weakly Supervised Instance Segmentation
Accepted to CVPR 2023. Code and models: https://github.com/hustvl/BoxTeacher
null
null
null
cs.CV
http://creativecommons.org/licenses/by-nc-nd/4.0/
Labeling objects with pixel-wise segmentation requires a huge amount of human labor compared to bounding boxes. Most existing methods for weakly supervised instance segmentation focus on designing heuristic losses with priors from bounding boxes. While, we find that box-supervised methods can produce some fine segmen...
[ { "created": "Tue, 11 Oct 2022 06:23:30 GMT", "version": "v1" }, { "created": "Fri, 17 Mar 2023 05:17:43 GMT", "version": "v2" } ]
2023-03-20
[ [ "Cheng", "Tianheng", "" ], [ "Wang", "Xinggang", "" ], [ "Chen", "Shaoyu", "" ], [ "Zhang", "Qian", "" ], [ "Liu", "Wenyu", "" ] ]
Labeling objects with pixel-wise segmentation requires a huge amount of human labor compared to bounding boxes. Most existing methods for weakly supervised instance segmentation focus on designing heuristic losses with priors from bounding boxes. While, we find that box-supervised methods can produce some fine segmenta...
2402.15121
Md Abdullah-Al Kaiser
Md Abdullah-Al Kaiser, Gourav Datta, Peter A. Beerel, and Akhilesh R. Jaiswal
Toward High Performance, Programmable Extreme-Edge Intelligence for Neuromorphic Vision Sensors utilizing Magnetic Domain Wall Motion-based MTJ
11 pages, 7 figures, 2 table
null
null
null
cs.AR cs.ET eess.IV
http://creativecommons.org/licenses/by/4.0/
The desire to empower resource-limited edge devices with computer vision (CV) must overcome the high energy consumption of collecting and processing vast sensory data. To address the challenge, this work proposes an energy-efficient non-von-Neumann in-pixel processing solution for neuromorphic vision sensors employin...
[ { "created": "Fri, 23 Feb 2024 06:13:15 GMT", "version": "v1" } ]
2024-02-26
[ [ "Kaiser", "Md Abdullah-Al", "" ], [ "Datta", "Gourav", "" ], [ "Beerel", "Peter A.", "" ], [ "Jaiswal", "Akhilesh R.", "" ] ]
The desire to empower resource-limited edge devices with computer vision (CV) must overcome the high energy consumption of collecting and processing vast sensory data. To address the challenge, this work proposes an energy-efficient non-von-Neumann in-pixel processing solution for neuromorphic vision sensors employing ...
2404.16848
Partha Protim Datta
Partha Protim Datta
Cyber Security issues and Blockchain-Deep Learning based solutions for UAV and Internet of Drones (FANETs)
null
null
null
null
cs.CR eess.SP
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Safety-critical systems such as automated embedded or industrial systems have a strong dependency on the trustworthiness of data collection. As sensors are the critical component for those systems, it is imperative to address the attack resilience of sensors
[ { "created": "Thu, 29 Feb 2024 01:14:59 GMT", "version": "v1" } ]
2024-04-29
[ [ "Datta", "Partha Protim", "" ] ]
Safety-critical systems such as automated embedded or industrial systems have a strong dependency on the trustworthiness of data collection. As sensors are the critical component for those systems, it is imperative to address the attack resilience of sensors
2406.05645
Jie Liu
Jie Liu, Yao Wu, Xiaotong Luo, Zongze Wu
Anomaly Multi-classification in Industrial Scenarios: Transferring Few-shot Learning to a New Task
null
null
null
null
cs.CV cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In industrial scenarios, it is crucial not only to identify anomalous items but also to classify the type of anomaly. However, research on anomaly multi-classification remains largely unexplored. This paper proposes a novel and valuable research task called anomaly multi-classification. Given the challenges in applyi...
[ { "created": "Sun, 9 Jun 2024 05:07:39 GMT", "version": "v1" } ]
2024-06-18
[ [ "Liu", "Jie", "" ], [ "Wu", "Yao", "" ], [ "Luo", "Xiaotong", "" ], [ "Wu", "Zongze", "" ] ]
In industrial scenarios, it is crucial not only to identify anomalous items but also to classify the type of anomaly. However, research on anomaly multi-classification remains largely unexplored. This paper proposes a novel and valuable research task called anomaly multi-classification. Given the challenges in applying...
2304.13302
Fuheng Wu
Fuheng Wu, Ivan Davchev, Jun Qian
HiQ -- A Declarative, Non-intrusive, Dynamic and Transparent Observability and Optimization System
7 pages, 12 figures, opensource
null
null
null
cs.DC cs.AI cs.LG cs.PF
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper proposes a non-intrusive, declarative, dynamic and transparent system called `HiQ` to track Python program runtime information without compromising on the run-time system performance and losing insight. HiQ can be used for monolithic and distributed systems, offline and online applications. HiQ is develope...
[ { "created": "Wed, 26 Apr 2023 06:11:26 GMT", "version": "v1" } ]
2023-04-27
[ [ "Wu", "Fuheng", "" ], [ "Davchev", "Ivan", "" ], [ "Qian", "Jun", "" ] ]
This paper proposes a non-intrusive, declarative, dynamic and transparent system called `HiQ` to track Python program runtime information without compromising on the run-time system performance and losing insight. HiQ can be used for monolithic and distributed systems, offline and online applications. HiQ is developed ...
1609.07008
Edgar Solomonik
Edgar Solomonik, Maciej Besta, Flavio Vella, and Torsten Hoefler
Scaling betweenness centrality using communication-efficient sparse matrix multiplication
null
null
null
null
cs.DC cs.DM cs.MS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Betweenness centrality (BC) is a crucial graph problem that measures the significance of a vertex by the number of shortest paths leading through it. We propose Maximal Frontier Betweenness Centrality (MFBC): a succinct BC algorithm based on novel sparse matrix multiplication routines that performs a factor of $p^{1/...
[ { "created": "Thu, 22 Sep 2016 15:01:30 GMT", "version": "v1" }, { "created": "Wed, 9 Aug 2017 15:30:00 GMT", "version": "v2" } ]
2017-08-10
[ [ "Solomonik", "Edgar", "" ], [ "Besta", "Maciej", "" ], [ "Vella", "Flavio", "" ], [ "Hoefler", "Torsten", "" ] ]
Betweenness centrality (BC) is a crucial graph problem that measures the significance of a vertex by the number of shortest paths leading through it. We propose Maximal Frontier Betweenness Centrality (MFBC): a succinct BC algorithm based on novel sparse matrix multiplication routines that performs a factor of $p^{1/3}...
2405.09911
Robert Hogan
Robert Hogan, Sean R. Mathieson, Aurel Luca, Soraia Ventura, Sean Griffin, Geraldine B. Boylan, and John M. O'Toole
Scaling convolutional neural networks achieves expert-level seizure detection in neonatal EEG
null
null
null
null
cs.LG eess.SP physics.med-ph
http://creativecommons.org/licenses/by-nc-nd/4.0/
Background: Neonatal seizures are a neurological emergency that require urgent treatment. They are hard to diagnose clinically and can go undetected if EEG monitoring is unavailable. EEG interpretation requires specialised expertise which is not widely available. Algorithms to detect EEG seizures can address this lim...
[ { "created": "Thu, 16 May 2024 08:59:20 GMT", "version": "v1" } ]
2024-05-17
[ [ "Hogan", "Robert", "" ], [ "Mathieson", "Sean R.", "" ], [ "Luca", "Aurel", "" ], [ "Ventura", "Soraia", "" ], [ "Griffin", "Sean", "" ], [ "Boylan", "Geraldine B.", "" ], [ "O'Toole", "John M.", "" ] ]
Background: Neonatal seizures are a neurological emergency that require urgent treatment. They are hard to diagnose clinically and can go undetected if EEG monitoring is unavailable. EEG interpretation requires specialised expertise which is not widely available. Algorithms to detect EEG seizures can address this limit...
2311.18440
Zeeshan Rasheed Mr
Zeeshan Rasheed, Muhammad Waseem, Kai-Kristian Kemell, Wang Xiaofeng, Anh Nguyen Duc, Kari Syst\"a, Pekka Abrahamsson
Autonomous Agents in Software Development: A Vision Paper
5 pages, 1 figure
null
null
null
cs.SE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Large Language Models (LLM) and Generative Pre-trained Transformers (GPT), are reshaping the field of Software Engineering (SE). They enable innovative methods for executing many software engineering tasks, including automated code generation, debugging, maintenance, etc. However, only a limited number of existing wo...
[ { "created": "Thu, 30 Nov 2023 10:42:43 GMT", "version": "v1" } ]
2023-12-01
[ [ "Rasheed", "Zeeshan", "" ], [ "Waseem", "Muhammad", "" ], [ "Kemell", "Kai-Kristian", "" ], [ "Xiaofeng", "Wang", "" ], [ "Duc", "Anh Nguyen", "" ], [ "Systä", "Kari", "" ], [ "Abrahamsson", "Pekka", "" ]...
Large Language Models (LLM) and Generative Pre-trained Transformers (GPT), are reshaping the field of Software Engineering (SE). They enable innovative methods for executing many software engineering tasks, including automated code generation, debugging, maintenance, etc. However, only a limited number of existing work...
2303.08021
Mai A. Shaaban
Mai A. Shaaban, Mariam Kashkash, Maryam Alghfeli, Adham Ibrahim
OptBA: Optimizing Hyperparameters with the Bees Algorithm for Improved Medical Text Classification
null
null
null
null
cs.CL cs.AI
http://creativecommons.org/licenses/by/4.0/
One of the main challenges in the field of deep learning is obtaining the optimal model hyperparameters. The search for optimal hyperparameters usually hinders the progress of solutions to real-world problems such as healthcare. Previous solutions have been proposed, but they can still get stuck in local optima. To o...
[ { "created": "Tue, 14 Mar 2023 16:04:13 GMT", "version": "v1" }, { "created": "Sun, 8 Oct 2023 05:30:33 GMT", "version": "v2" }, { "created": "Sat, 29 Jun 2024 15:40:27 GMT", "version": "v3" } ]
2024-07-02
[ [ "Shaaban", "Mai A.", "" ], [ "Kashkash", "Mariam", "" ], [ "Alghfeli", "Maryam", "" ], [ "Ibrahim", "Adham", "" ] ]
One of the main challenges in the field of deep learning is obtaining the optimal model hyperparameters. The search for optimal hyperparameters usually hinders the progress of solutions to real-world problems such as healthcare. Previous solutions have been proposed, but they can still get stuck in local optima. To ove...
1205.0561
Gildas Morvan
Gildas Morvan
Multi-level agent-based modeling - A literature survey
v2. Ref 102 added. v3-4 Many refs and text added v5-6 bibliographic statistics updated. v7 Change of the name of the paper to reflect what it became, many refs and text added, bibliographic statistics updated
null
null
null
cs.MA
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
During last decade, multi-level agent-based modeling has received significant and dramatically increasing interest. In this article we present a comprehensive and structured review of literature on the subject. We present the main theoretical contributions and application domains of this concept, with an emphasis on ...
[ { "created": "Wed, 2 May 2012 20:13:59 GMT", "version": "v1" }, { "created": "Fri, 4 May 2012 15:19:10 GMT", "version": "v2" }, { "created": "Mon, 11 Jun 2012 08:58:41 GMT", "version": "v3" }, { "created": "Wed, 12 Dec 2012 14:19:42 GMT", "version": "v4" }, { "cre...
2013-11-18
[ [ "Morvan", "Gildas", "" ] ]
During last decade, multi-level agent-based modeling has received significant and dramatically increasing interest. In this article we present a comprehensive and structured review of literature on the subject. We present the main theoretical contributions and application domains of this concept, with an emphasis on so...
2309.08946
Seyedkazem Shekofteh
S.-Kazem Shekofteh, Christian Alles, Holger Fr\"oning
Reducing Memory Requirements for the IPU using Butterfly Factorizations
null
null
null
null
cs.DC cs.ET cs.LG
http://creativecommons.org/licenses/by-nc-nd/4.0/
High Performance Computing (HPC) benefits from different improvements during last decades, specially in terms of hardware platforms to provide more processing power while maintaining the power consumption at a reasonable level. The Intelligence Processing Unit (IPU) is a new type of massively parallel processor, desi...
[ { "created": "Sat, 16 Sep 2023 10:38:38 GMT", "version": "v1" } ]
2023-09-19
[ [ "Shekofteh", "S. -Kazem", "" ], [ "Alles", "Christian", "" ], [ "Fröning", "Holger", "" ] ]
High Performance Computing (HPC) benefits from different improvements during last decades, specially in terms of hardware platforms to provide more processing power while maintaining the power consumption at a reasonable level. The Intelligence Processing Unit (IPU) is a new type of massively parallel processor, design...
2403.10408
Vidminas Vizgirda
Vidminas Vizgirda (1), Rui Zhao (2), and Naman Goel (2) ((1) University of Edinburgh, (2) University of Oxford)
SocialGenPod: Privacy-Friendly Generative AI Social Web Applications with Decentralised Personal Data Stores
Demo paper accepted in Companion Proceedings of the ACM Web Conference 2024
null
10.1145/3589335.3651251
null
cs.CR cs.CY cs.IR cs.LG cs.SI
http://creativecommons.org/licenses/by/4.0/
We present SocialGenPod, a decentralised and privacy-friendly way of deploying generative AI Web applications. Unlike centralised Web and data architectures that keep user data tied to application and service providers, we show how one can use Solid -- a decentralised Web specification -- to decouple user data from g...
[ { "created": "Fri, 15 Mar 2024 15:43:02 GMT", "version": "v1" } ]
2024-03-18
[ [ "Vizgirda", "Vidminas", "" ], [ "Zhao", "Rui", "" ], [ "Goel", "Naman", "" ] ]
We present SocialGenPod, a decentralised and privacy-friendly way of deploying generative AI Web applications. Unlike centralised Web and data architectures that keep user data tied to application and service providers, we show how one can use Solid -- a decentralised Web specification -- to decouple user data from gen...
1509.01608
Emilio Ferrara
Santa Agreste, Salvatore Catanese, Pasquale De Meo, Emilio Ferrara, Giacomo Fiumara
Network Structure and Resilience of Mafia Syndicates
22 pages, 10 figures, 1 table
Information Sciences, 351, 30-47. 2016
10.1016/j.ins.2016.02.027
null
cs.SI cs.CY physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper we present the results of the study of Sicilian Mafia organization by using Social Network Analysis. The study investigates the network structure of a Mafia organization, describing its evolution and highlighting its plasticity to interventions targeting membership and its resilience to disruption cause...
[ { "created": "Fri, 4 Sep 2015 21:13:16 GMT", "version": "v1" } ]
2017-03-07
[ [ "Agreste", "Santa", "" ], [ "Catanese", "Salvatore", "" ], [ "De Meo", "Pasquale", "" ], [ "Ferrara", "Emilio", "" ], [ "Fiumara", "Giacomo", "" ] ]
In this paper we present the results of the study of Sicilian Mafia organization by using Social Network Analysis. The study investigates the network structure of a Mafia organization, describing its evolution and highlighting its plasticity to interventions targeting membership and its resilience to disruption caused ...
2009.02114
Alexander Barabanov
Alexander Barabanov, Denis Makrushin
Authentication and authorization in microservice-based systems: survey of architecture patterns
The work was done in Advanced Software Technology Laboratory, Huawei. It is planned to be published in "Voprosy kiberbezopasnosti"
null
null
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Context. Service-oriented architecture and its microservice-based approach increase an attack surface of applications. Exposed microservices become a pivot point for advanced persistent threats and completely change the threat landscape. Correctly implemented authentication and authorization architecture patterns are...
[ { "created": "Fri, 4 Sep 2020 11:19:54 GMT", "version": "v1" } ]
2020-09-07
[ [ "Barabanov", "Alexander", "" ], [ "Makrushin", "Denis", "" ] ]
Context. Service-oriented architecture and its microservice-based approach increase an attack surface of applications. Exposed microservices become a pivot point for advanced persistent threats and completely change the threat landscape. Correctly implemented authentication and authorization architecture patterns are b...
2010.03266
Xingbo Liu
Xiao Kang, Xingbo Liu, Xiushan Nie, Yilong Yin
Learning Binary Semantic Embedding for Histology Image Classification and Retrieval
null
null
null
null
cs.CV cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
With the development of medical imaging technology and machine learning, computer-assisted diagnosis which can provide impressive reference to pathologists, attracts extensive research interests. The exponential growth of medical images and uninterpretability of traditional classification models have hindered the app...
[ { "created": "Wed, 7 Oct 2020 08:36:44 GMT", "version": "v1" } ]
2020-10-08
[ [ "Kang", "Xiao", "" ], [ "Liu", "Xingbo", "" ], [ "Nie", "Xiushan", "" ], [ "Yin", "Yilong", "" ] ]
With the development of medical imaging technology and machine learning, computer-assisted diagnosis which can provide impressive reference to pathologists, attracts extensive research interests. The exponential growth of medical images and uninterpretability of traditional classification models have hindered the appli...
1703.03856
Laurel Orr
Laurel Orr, Magda Balazinska, and Dan Suciu
Probabilistic Database Summarization for Interactive Data Exploration
To appear VLDB 2017
null
null
null
cs.DB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present a probabilistic approach to generate a small, query-able summary of a dataset for interactive data exploration. Departing from traditional summarization techniques, we use the Principle of Maximum Entropy to generate a probabilistic representation of the data that can be used to give approximate query answ...
[ { "created": "Fri, 10 Mar 2017 22:17:22 GMT", "version": "v1" }, { "created": "Tue, 23 May 2017 20:44:53 GMT", "version": "v2" } ]
2017-05-25
[ [ "Orr", "Laurel", "" ], [ "Balazinska", "Magda", "" ], [ "Suciu", "Dan", "" ] ]
We present a probabilistic approach to generate a small, query-able summary of a dataset for interactive data exploration. Departing from traditional summarization techniques, we use the Principle of Maximum Entropy to generate a probabilistic representation of the data that can be used to give approximate query answer...
2402.11773
Kohei Obata
Kohei Obata, Koki Kawabata, Yasuko Matsubara, Yasushi Sakurai
Dynamic Multi-Network Mining of Tensor Time Series
Accepted by WWW 2024
null
null
null
cs.LG cs.AI cs.IT math.IT
http://creativecommons.org/licenses/by/4.0/
Subsequence clustering of time series is an essential task in data mining, and interpreting the resulting clusters is also crucial since we generally do not have prior knowledge of the data. Thus, given a large collection of tensor time series consisting of multiple modes, including timestamps, how can we achieve sub...
[ { "created": "Mon, 19 Feb 2024 02:06:04 GMT", "version": "v1" }, { "created": "Thu, 22 Feb 2024 01:17:29 GMT", "version": "v2" } ]
2024-02-23
[ [ "Obata", "Kohei", "" ], [ "Kawabata", "Koki", "" ], [ "Matsubara", "Yasuko", "" ], [ "Sakurai", "Yasushi", "" ] ]
Subsequence clustering of time series is an essential task in data mining, and interpreting the resulting clusters is also crucial since we generally do not have prior knowledge of the data. Thus, given a large collection of tensor time series consisting of multiple modes, including timestamps, how can we achieve subse...
2305.14690
Tongtong Fang
Tongtong Fang, Nan Lu, Gang Niu, Masashi Sugiyama
Generalizing Importance Weighting to A Universal Solver for Distribution Shift Problems
NeurIPS 2023 camera-ready version (this paper was selected for spotlight presentation)
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Distribution shift (DS) may have two levels: the distribution itself changes, and the support (i.e., the set where the probability density is non-zero) also changes. When considering the support change between the training and test distributions, there can be four cases: (i) they exactly match; (ii) the training supp...
[ { "created": "Wed, 24 May 2023 03:53:15 GMT", "version": "v1" }, { "created": "Thu, 2 Nov 2023 00:33:35 GMT", "version": "v2" } ]
2023-11-03
[ [ "Fang", "Tongtong", "" ], [ "Lu", "Nan", "" ], [ "Niu", "Gang", "" ], [ "Sugiyama", "Masashi", "" ] ]
Distribution shift (DS) may have two levels: the distribution itself changes, and the support (i.e., the set where the probability density is non-zero) also changes. When considering the support change between the training and test distributions, there can be four cases: (i) they exactly match; (ii) the training suppor...
0801.1718
Milan Derpich
Milan S. Derpich, Jan Ostergaard and Daniel E. Quevedo
Achieving the Quadratic Gaussian Rate-Distortion Function for Source Uncorrelated Distortions
Technical report, January 2008. Other papers available from http://msderpich.no-ip.org
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We prove achievability of the recently characterized quadratic Gaussian rate-distortion function (RDF) subject to the constraint that the distortion is uncorrelated to the source. This result is based on shaped dithered lattice quantization in the limit as the lattice dimension tends to infinity and holds for all pos...
[ { "created": "Fri, 11 Jan 2008 04:08:07 GMT", "version": "v1" }, { "created": "Sun, 13 Jan 2008 04:48:14 GMT", "version": "v2" }, { "created": "Thu, 24 Jul 2008 10:02:42 GMT", "version": "v3" } ]
2008-07-24
[ [ "Derpich", "Milan S.", "" ], [ "Ostergaard", "Jan", "" ], [ "Quevedo", "Daniel E.", "" ] ]
We prove achievability of the recently characterized quadratic Gaussian rate-distortion function (RDF) subject to the constraint that the distortion is uncorrelated to the source. This result is based on shaped dithered lattice quantization in the limit as the lattice dimension tends to infinity and holds for all posit...
2203.06246
Fernando Delgado
Fernando Delgado, Solon Barocas, and Karen Levy
An Uncommon Task: Participatory Design in Legal AI
null
In Proceedings of the ACM on Human-Computer Interaction, 6, CSCW1, Article 51 (April 2022), 23 pages
10.1145/3512898
null
cs.CY cs.AI cs.HC cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Despite growing calls for participation in AI design, there are to date few empirical studies of what these processes look like and how they can be structured for meaningful engagement with domain experts. In this paper, we examine a notable yet understudied AI design process in the legal domain that took place over ...
[ { "created": "Tue, 8 Mar 2022 15:46:52 GMT", "version": "v1" } ]
2022-03-15
[ [ "Delgado", "Fernando", "" ], [ "Barocas", "Solon", "" ], [ "Levy", "Karen", "" ] ]
Despite growing calls for participation in AI design, there are to date few empirical studies of what these processes look like and how they can be structured for meaningful engagement with domain experts. In this paper, we examine a notable yet understudied AI design process in the legal domain that took place over a ...
1909.00543
Aria Rezaei
Aria Rezaei, Jie Gao
On Privacy of Socially Contagious Attributes
10 pages, ICDM 2019
null
null
null
cs.SI physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A commonly used method to protect user privacy in data collection is to perform randomized perturbation on user's real data before collection so that aggregated statistics can still be inferred without endangering secrets held by individuals. In this paper, we take a closer look at the validity of Differential Privac...
[ { "created": "Mon, 2 Sep 2019 04:41:15 GMT", "version": "v1" } ]
2019-09-04
[ [ "Rezaei", "Aria", "" ], [ "Gao", "Jie", "" ] ]
A commonly used method to protect user privacy in data collection is to perform randomized perturbation on user's real data before collection so that aggregated statistics can still be inferred without endangering secrets held by individuals. In this paper, we take a closer look at the validity of Differential Privacy ...
2203.08308
Kuan-Hao Huang
Kuan-Hao Huang, I-Hung Hsu, Premkumar Natarajan, Kai-Wei Chang, Nanyun Peng
Multilingual Generative Language Models for Zero-Shot Cross-Lingual Event Argument Extraction
ACL 2022. Our code is available at https://github.com/PlusLabNLP/X-Gear
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present a study on leveraging multilingual pre-trained generative language models for zero-shot cross-lingual event argument extraction (EAE). By formulating EAE as a language generation task, our method effectively encodes event structures and captures the dependencies between arguments. We design language-agnost...
[ { "created": "Tue, 15 Mar 2022 23:00:32 GMT", "version": "v1" } ]
2022-03-17
[ [ "Huang", "Kuan-Hao", "" ], [ "Hsu", "I-Hung", "" ], [ "Natarajan", "Premkumar", "" ], [ "Chang", "Kai-Wei", "" ], [ "Peng", "Nanyun", "" ] ]
We present a study on leveraging multilingual pre-trained generative language models for zero-shot cross-lingual event argument extraction (EAE). By formulating EAE as a language generation task, our method effectively encodes event structures and captures the dependencies between arguments. We design language-agnostic...
2001.03272
Kaushik Chakrabarti
Kaushik Chakrabarti, Zhimin Chen, Siamak Shakeri, Guihong Cao
Open Domain Question Answering Using Web Tables
null
null
null
null
cs.IR cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Tables extracted from web documents can be used to directly answer many web search queries. Previous works on question answering (QA) using web tables have focused on factoid queries, i.e., those answerable with a short string like person name or a number. However, many queries answerable using tables are non-factoid...
[ { "created": "Fri, 10 Jan 2020 01:25:04 GMT", "version": "v1" } ]
2020-01-13
[ [ "Chakrabarti", "Kaushik", "" ], [ "Chen", "Zhimin", "" ], [ "Shakeri", "Siamak", "" ], [ "Cao", "Guihong", "" ] ]
Tables extracted from web documents can be used to directly answer many web search queries. Previous works on question answering (QA) using web tables have focused on factoid queries, i.e., those answerable with a short string like person name or a number. However, many queries answerable using tables are non-factoid i...
2404.08408
Hongtao Wang
Hongtao Wang, Li Long, Jiangshe Zhang, Xiaoli Wei, Chunxia Zhang, Zhenbo Guo
Seismic First Break Picking in a Higher Dimension Using Deep Graph Learning
null
null
null
null
cs.LG cs.AI eess.SP physics.geo-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Contemporary automatic first break (FB) picking methods typically analyze 1D signals, 2D source gathers, or 3D source-receiver gathers. Utilizing higher-dimensional data, such as 2D or 3D, incorporates global features, improving the stability of local picking. Despite the benefits, high-dimensional data requires stru...
[ { "created": "Fri, 12 Apr 2024 11:36:24 GMT", "version": "v1" } ]
2024-04-15
[ [ "Wang", "Hongtao", "" ], [ "Long", "Li", "" ], [ "Zhang", "Jiangshe", "" ], [ "Wei", "Xiaoli", "" ], [ "Zhang", "Chunxia", "" ], [ "Guo", "Zhenbo", "" ] ]
Contemporary automatic first break (FB) picking methods typically analyze 1D signals, 2D source gathers, or 3D source-receiver gathers. Utilizing higher-dimensional data, such as 2D or 3D, incorporates global features, improving the stability of local picking. Despite the benefits, high-dimensional data requires struct...
2010.00163
Yayi Zou
Yayi Zou, Zhiwei Qin
Bayesian Meta-reinforcement Learning for Traffic Signal Control
null
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In recent years, there has been increasing amount of interest around meta reinforcement learning methods for traffic signal control, which have achieved better performance compared with traditional control methods. However, previous methods lack robustness in adaptation and stability in training process in complex si...
[ { "created": "Thu, 1 Oct 2020 01:15:17 GMT", "version": "v1" }, { "created": "Fri, 22 Oct 2021 23:56:55 GMT", "version": "v2" } ]
2021-10-26
[ [ "Zou", "Yayi", "" ], [ "Qin", "Zhiwei", "" ] ]
In recent years, there has been increasing amount of interest around meta reinforcement learning methods for traffic signal control, which have achieved better performance compared with traditional control methods. However, previous methods lack robustness in adaptation and stability in training process in complex situ...
2312.13716
Yuanfu Wang
Yuanfu Wang, Chao Yang, Ying Wen, Yu Liu, Yu Qiao
Critic-Guided Decision Transformer for Offline Reinforcement Learning
Accepted at AAAI 2024
null
null
null
cs.LG cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recent advancements in offline reinforcement learning (RL) have underscored the capabilities of Return-Conditioned Supervised Learning (RCSL), a paradigm that learns the action distribution based on target returns for each state in a supervised manner. However, prevailing RCSL methods largely focus on deterministic t...
[ { "created": "Thu, 21 Dec 2023 10:29:17 GMT", "version": "v1" } ]
2023-12-22
[ [ "Wang", "Yuanfu", "" ], [ "Yang", "Chao", "" ], [ "Wen", "Ying", "" ], [ "Liu", "Yu", "" ], [ "Qiao", "Yu", "" ] ]
Recent advancements in offline reinforcement learning (RL) have underscored the capabilities of Return-Conditioned Supervised Learning (RCSL), a paradigm that learns the action distribution based on target returns for each state in a supervised manner. However, prevailing RCSL methods largely focus on deterministic tra...
2102.08430
Xiumin Shang
Xiumin Shang and Jinping Yang and Bingquan Zhu and Lin Ye and Jing Zhang, Jianping Xu and Qin Lyu and Ruisheng Diao
Multi-Stage Transmission Line Flow Control Using Centralized and Decentralized Reinforcement Learning Agents
This work is accepted by NeurIPS ML4Eng workshop 2020, please refer to https://ml4eng.github.io/camera_readys/56.pdf
null
null
null
cs.LG cs.SY eess.SY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Planning future operational scenarios of bulk power systems that meet security and economic constraints typically requires intensive labor efforts in performing massive simulations. To automate this process and relieve engineers' burden, a novel multi-stage control approach is presented in this paper to train central...
[ { "created": "Tue, 16 Feb 2021 19:54:30 GMT", "version": "v1" } ]
2021-02-18
[ [ "Shang", "Xiumin", "" ], [ "Yang", "Jinping", "" ], [ "Zhu", "Bingquan", "" ], [ "Ye", "Lin", "" ], [ "Zhang", "Jing", "" ], [ "Xu", "Jianping", "" ], [ "Lyu", "Qin", "" ], [ "Diao", "Ruisheng",...
Planning future operational scenarios of bulk power systems that meet security and economic constraints typically requires intensive labor efforts in performing massive simulations. To automate this process and relieve engineers' burden, a novel multi-stage control approach is presented in this paper to train centraliz...
2401.15854
Phat Lam
Phat Lam, Lam Pham, Tin Nguyen, Hieu Tang, Michael Seidl, Medina Andresel, Alexander Schindler
LSTM-based Deep Neural Network With A Focus on Sentence Representation for Sequential Sentence Classification in Medical Scientific Abstracts
Submitted to FedCSIS 2024
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
The Sequential Sentence Classification task within the domain of medical abstracts, termed as SSC, involves the categorization of sentences into pre-defined headings based on their roles in conveying critical information in the abstract. In the SSC task, sentences are sequentially related to each other. For this reas...
[ { "created": "Mon, 29 Jan 2024 03:05:35 GMT", "version": "v1" }, { "created": "Fri, 31 May 2024 08:37:04 GMT", "version": "v2" } ]
2024-06-03
[ [ "Lam", "Phat", "" ], [ "Pham", "Lam", "" ], [ "Nguyen", "Tin", "" ], [ "Tang", "Hieu", "" ], [ "Seidl", "Michael", "" ], [ "Andresel", "Medina", "" ], [ "Schindler", "Alexander", "" ] ]
The Sequential Sentence Classification task within the domain of medical abstracts, termed as SSC, involves the categorization of sentences into pre-defined headings based on their roles in conveying critical information in the abstract. In the SSC task, sentences are sequentially related to each other. For this reason...
1704.00571
Richard La
Richard J. La
Effects of Degree Correlations in Interdependent Security: Good or Bad?
14 pages, 3 figures
null
null
null
cs.SI physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We study the influence of degree correlations or network mixing in interdependent security. We model the interdependence in security among agents using a dependence graph and employ a population game model to capture the interaction among many agents when they are strategic and have various security measures they can...
[ { "created": "Mon, 3 Apr 2017 13:24:36 GMT", "version": "v1" } ]
2017-04-04
[ [ "La", "Richard J.", "" ] ]
We study the influence of degree correlations or network mixing in interdependent security. We model the interdependence in security among agents using a dependence graph and employ a population game model to capture the interaction among many agents when they are strategic and have various security measures they can c...
2403.14649
Nicolas Jullien
Nicolas Jullien (IMT Atlantique - LUSSI, MARSOUIN, LEGO)
The economic value of scientific software
in French language
Revue Lamy Droit de l'immat{\'e}riel, 2024, 210
null
null
cs.CY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Academic institutions and their staff use, adapt and create software. We're thinking of business tools used to carry out their mission: teaching management (Moodle) or subject teaching support (such as Maxima for formal calculus), for example. We're talking about software resulting from research work, designed by a r...
[ { "created": "Fri, 23 Feb 2024 08:20:19 GMT", "version": "v1" } ]
2024-03-25
[ [ "Jullien", "Nicolas", "", "IMT Atlantique - LUSSI, MARSOUIN, LEGO" ] ]
Academic institutions and their staff use, adapt and create software. We're thinking of business tools used to carry out their mission: teaching management (Moodle) or subject teaching support (such as Maxima for formal calculus), for example. We're talking about software resulting from research work, designed by a res...
1807.07878
Ibrahim Issa
Ibrahim Issa, Aaron B. Wagner, and Sudeep Kamath
An Operational Approach to Information Leakage
Submitted to IEEE Transactions on Information Theory (appeared in part in CISS 2016, ISIT 2016 & 2017)
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Given two random variables $X$ and $Y$, an operational approach is undertaken to quantify the ``leakage'' of information from $X$ to $Y$. The resulting measure $\mathcal{L}(X \!\! \to \!\! Y)$ is called \emph{maximal leakage}, and is defined as the multiplicative increase, upon observing $Y$, of the probability of co...
[ { "created": "Fri, 20 Jul 2018 14:55:31 GMT", "version": "v1" } ]
2018-07-23
[ [ "Issa", "Ibrahim", "" ], [ "Wagner", "Aaron B.", "" ], [ "Kamath", "Sudeep", "" ] ]
Given two random variables $X$ and $Y$, an operational approach is undertaken to quantify the ``leakage'' of information from $X$ to $Y$. The resulting measure $\mathcal{L}(X \!\! \to \!\! Y)$ is called \emph{maximal leakage}, and is defined as the multiplicative increase, upon observing $Y$, of the probability of corr...
1701.02601
Harishchandra Dubey
Rabindra K. Barik, Harishchandra Dubey, Arun B. Samaddar, Rajan D. Gupta, Prakash K. Ray
FogGIS: Fog Computing for Geospatial Big Data Analytics
6 pages, 4 figures, 1 table, 3rd IEEE Uttar Pradesh Section International Conference on Electrical, Computer and Electronics (09-11 December, 2016) Indian Institute of Technology (Banaras Hindu University) Varanasi, India
null
null
null
cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Cloud Geographic Information Systems (GIS) has emerged as a tool for analysis, processing and transmission of geospatial data. The Fog computing is a paradigm where Fog devices help to increase throughput and reduce latency at the edge of the client. This paper developed a Fog-based framework named Fog GIS for mining...
[ { "created": "Sat, 10 Dec 2016 12:59:54 GMT", "version": "v1" } ]
2017-01-11
[ [ "Barik", "Rabindra K.", "" ], [ "Dubey", "Harishchandra", "" ], [ "Samaddar", "Arun B.", "" ], [ "Gupta", "Rajan D.", "" ], [ "Ray", "Prakash K.", "" ] ]
Cloud Geographic Information Systems (GIS) has emerged as a tool for analysis, processing and transmission of geospatial data. The Fog computing is a paradigm where Fog devices help to increase throughput and reduce latency at the edge of the client. This paper developed a Fog-based framework named Fog GIS for mining a...
1501.04478
Reevana Balmahoon
R Balmahoon and L Cheng
Information Leakage of Heterogeneous Encoded Correlated Sequences over Eavesdropped Channel
arXiv admin note: substantial text overlap with arXiv:1410.8805
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Correlated sources are present in communication systems where protocols ensure that there is some predetermined information for sources. Here correlated sources across an eavesdropped channel that incorporate a heterogeneous encoding scheme and their effect on the information leakage when some channel information and...
[ { "created": "Mon, 19 Jan 2015 12:58:19 GMT", "version": "v1" }, { "created": "Fri, 23 Jan 2015 08:00:27 GMT", "version": "v2" } ]
2015-01-26
[ [ "Balmahoon", "R", "" ], [ "Cheng", "L", "" ] ]
Correlated sources are present in communication systems where protocols ensure that there is some predetermined information for sources. Here correlated sources across an eavesdropped channel that incorporate a heterogeneous encoding scheme and their effect on the information leakage when some channel information and a...
1705.07237
Mustafa Kishk
Mustafa A. Kishk and Harpreet S. Dhillon
Coexistence of RF-powered IoT and a Primary Wireless Network with Secrecy Guard Zones
null
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper studies the secrecy performance of a wireless network (primary network) overlaid with an ambient RF energy harvesting IoT network (secondary network). The nodes in the secondary network are assumed to be solely powered by ambient RF energy harvested from the transmissions of the primary network. We assume ...
[ { "created": "Sat, 20 May 2017 00:45:53 GMT", "version": "v1" } ]
2017-05-23
[ [ "Kishk", "Mustafa A.", "" ], [ "Dhillon", "Harpreet S.", "" ] ]
This paper studies the secrecy performance of a wireless network (primary network) overlaid with an ambient RF energy harvesting IoT network (secondary network). The nodes in the secondary network are assumed to be solely powered by ambient RF energy harvested from the transmissions of the primary network. We assume th...
1607.01679
Manuel Blanco Valentin Eng.
Manuel Blanco Valentin, Clecio Roque De Bom, Marcio Portes de Albuquerque, Marcelo Portes de Albuquerque, Elisangela Faria, Maury Duarte Correia, Rodrigo Surmas
On a method for Rock Classification using Textural Features and Genetic Optimization
13 pages, 3 figures, 1 appendix. Replaced to match the published version
Notas Tecnicas do CBPF, v.7, n.1 (2017)
10.7437/NT2236-7640/2017.01.003
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this work we present a method to classify a set of rock textures based on a Spectral Analysis and the extraction of the texture Features of the resulted images. Up to 520 features were tested using 4 different filters and all 31 different combinations were verified. The classification process relies on a Naive Bay...
[ { "created": "Wed, 6 Jul 2016 15:45:21 GMT", "version": "v1" }, { "created": "Thu, 17 Aug 2017 19:16:31 GMT", "version": "v2" } ]
2017-08-21
[ [ "Valentin", "Manuel Blanco", "" ], [ "De Bom", "Clecio Roque", "" ], [ "de Albuquerque", "Marcio Portes", "" ], [ "de Albuquerque", "Marcelo Portes", "" ], [ "Faria", "Elisangela", "" ], [ "Correia", "Maury Duarte", "" ]...
In this work we present a method to classify a set of rock textures based on a Spectral Analysis and the extraction of the texture Features of the resulted images. Up to 520 features were tested using 4 different filters and all 31 different combinations were verified. The classification process relies on a Naive Bayes...
2302.00623
Antonio De Domenico
Fadhel Ayed, Antonio De Domenico, Adrian Garcia-Rodriguez, David Lopez-Perez
Accordion: A Communication-Aware Machine Learning Framework for Next Generation Networks
null
null
null
null
cs.NI cs.LG eess.SP
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this article, we advocate for the design of ad hoc artificial intelligence (AI)/machine learning (ML) models to facilitate their usage in future smart infrastructures based on communication networks. To motivate this, we first review key operations identified by the 3GPP for transferring AI/ML models through 5G ne...
[ { "created": "Thu, 12 Jan 2023 10:30:43 GMT", "version": "v1" } ]
2023-02-02
[ [ "Ayed", "Fadhel", "" ], [ "De Domenico", "Antonio", "" ], [ "Garcia-Rodriguez", "Adrian", "" ], [ "Lopez-Perez", "David", "" ] ]
In this article, we advocate for the design of ad hoc artificial intelligence (AI)/machine learning (ML) models to facilitate their usage in future smart infrastructures based on communication networks. To motivate this, we first review key operations identified by the 3GPP for transferring AI/ML models through 5G netw...
2110.09624
Eric Horvitz
Eric Horvitz and John Breese
Ideal Partition of Resources for Metareasoning
12 pages, 5 figures. January 1990 technical report on principles of metareasoning and bounded optimality
null
null
Report-no: KSL-90-26, Computer Science Department, Stanford University
cs.AI
http://creativecommons.org/licenses/by-sa/4.0/
We can achieve significant gains in the value of computation by metareasoning about the nature or extent of base-level problem solving before executing a solution. However, resources that are irrevocably committed to metareasoning are not available for executing a solution. Thus, it is important to determine the port...
[ { "created": "Mon, 18 Oct 2021 21:20:26 GMT", "version": "v1" } ]
2021-10-20
[ [ "Horvitz", "Eric", "" ], [ "Breese", "John", "" ] ]
We can achieve significant gains in the value of computation by metareasoning about the nature or extent of base-level problem solving before executing a solution. However, resources that are irrevocably committed to metareasoning are not available for executing a solution. Thus, it is important to determine the portio...
2007.02798
Sam Bond-Taylor
Sam Bond-Taylor and Chris G. Willcocks
Gradient Origin Networks
16 pages, 17 figures, accepted at ICLR 2021, camera-ready version
null
null
null
cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper proposes a new type of generative model that is able to quickly learn a latent representation without an encoder. This is achieved using empirical Bayes to calculate the expectation of the posterior, which is implemented by initialising a latent vector with zeros, then using the gradient of the log-likelih...
[ { "created": "Mon, 6 Jul 2020 15:00:11 GMT", "version": "v1" }, { "created": "Wed, 8 Jul 2020 08:44:05 GMT", "version": "v2" }, { "created": "Thu, 30 Jul 2020 17:18:20 GMT", "version": "v3" }, { "created": "Thu, 21 Jan 2021 15:38:55 GMT", "version": "v4" }, { "cre...
2021-03-25
[ [ "Bond-Taylor", "Sam", "" ], [ "Willcocks", "Chris G.", "" ] ]
This paper proposes a new type of generative model that is able to quickly learn a latent representation without an encoder. This is achieved using empirical Bayes to calculate the expectation of the posterior, which is implemented by initialising a latent vector with zeros, then using the gradient of the log-likelihoo...
2106.15318
Dimitrios Kollias
Dimitrios Kollias and Irene Kotsia and Elnar Hajiyev and Stefanos Zafeiriou
Analysing Affective Behavior in the second ABAW2 Competition
arXiv admin note: substantial text overlap with arXiv:2001.11409
null
null
null
cs.CV
http://creativecommons.org/licenses/by-nc-sa/4.0/
The Affective Behavior Analysis in-the-wild (ABAW2) 2021 Competition is the second -- following the first very successful ABAW Competition held in conjunction with IEEE FG 2020- Competition that aims at automatically analyzing affect. ABAW2 is split into three Challenges, each one addressing one of the three main beh...
[ { "created": "Mon, 14 Jun 2021 11:30:19 GMT", "version": "v1" }, { "created": "Sat, 3 Jul 2021 19:33:22 GMT", "version": "v2" } ]
2021-07-06
[ [ "Kollias", "Dimitrios", "" ], [ "Kotsia", "Irene", "" ], [ "Hajiyev", "Elnar", "" ], [ "Zafeiriou", "Stefanos", "" ] ]
The Affective Behavior Analysis in-the-wild (ABAW2) 2021 Competition is the second -- following the first very successful ABAW Competition held in conjunction with IEEE FG 2020- Competition that aims at automatically analyzing affect. ABAW2 is split into three Challenges, each one addressing one of the three main behav...
2101.02486
Leonardo Maria Millefiori
Samuele Capobianco, Leonardo M. Millefiori, Nicola Forti, Paolo Braca, and Peter Willett
Deep Learning Methods for Vessel Trajectory Prediction based on Recurrent Neural Networks
Accepted for publications in IEEE Transactions on Aerospace and Electronic Systems, 17 pages, 9 figures
IEEE Transactions on Aerospace and Electronic Systems, vol. 57, no. 6, pp. 4329-4346, 2021
10.1109/TAES.2021.3096873
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Data-driven methods open up unprecedented possibilities for maritime surveillance using Automatic Identification System (AIS) data. In this work, we explore deep learning strategies using historical AIS observations to address the problem of predicting future vessel trajectories with a prediction horizon of several h...
[ { "created": "Thu, 7 Jan 2021 11:05:47 GMT", "version": "v1" }, { "created": "Fri, 4 Jun 2021 11:49:02 GMT", "version": "v2" } ]
2023-01-18
[ [ "Capobianco", "Samuele", "" ], [ "Millefiori", "Leonardo M.", "" ], [ "Forti", "Nicola", "" ], [ "Braca", "Paolo", "" ], [ "Willett", "Peter", "" ] ]
Data-driven methods open up unprecedented possibilities for maritime surveillance using Automatic Identification System (AIS) data. In this work, we explore deep learning strategies using historical AIS observations to address the problem of predicting future vessel trajectories with a prediction horizon of several hou...
1905.09107
Michael Schaub
Michael T. Schaub and Santiago Segarra and John N. Tsitsiklis
Blind identification of stochastic block models from dynamical observations
33 pages; 4 figures
SIAM Journal on Mathematics of Data Science 2020 2:2, 335-367
10.1137/19M1263340
null
cs.LG cs.SI physics.soc-ph stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We consider a blind identification problem in which we aim to recover a statistical model of a network without knowledge of the network's edges, but based solely on nodal observations of a certain process. More concretely, we focus on observations that consist of single snapshots taken from multiple trajectories of a...
[ { "created": "Wed, 22 May 2019 12:45:04 GMT", "version": "v1" }, { "created": "Tue, 3 Dec 2019 12:28:04 GMT", "version": "v2" } ]
2020-05-08
[ [ "Schaub", "Michael T.", "" ], [ "Segarra", "Santiago", "" ], [ "Tsitsiklis", "John N.", "" ] ]
We consider a blind identification problem in which we aim to recover a statistical model of a network without knowledge of the network's edges, but based solely on nodal observations of a certain process. More concretely, we focus on observations that consist of single snapshots taken from multiple trajectories of a d...
1806.07039
Linkai Luo
Linkai Luo, Haiqing Yang and Francis Y. L. Chin
EmotionX-DLC: Self-Attentive BiLSTM for Detecting Sequential Emotions in Dialogue
9 pages, 3 figures
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we propose a self-attentive bidirectional long short-term memory (SA-BiLSTM) network to predict multiple emotions for the EmotionX challenge. The BiLSTM exhibits the power of modeling the word dependencies, and extracting the most relevant features for emotion classification. Building on top of BiLSTM,...
[ { "created": "Tue, 19 Jun 2018 05:03:23 GMT", "version": "v1" }, { "created": "Wed, 20 Jun 2018 07:07:53 GMT", "version": "v2" } ]
2018-06-21
[ [ "Luo", "Linkai", "" ], [ "Yang", "Haiqing", "" ], [ "Chin", "Francis Y. L.", "" ] ]
In this paper, we propose a self-attentive bidirectional long short-term memory (SA-BiLSTM) network to predict multiple emotions for the EmotionX challenge. The BiLSTM exhibits the power of modeling the word dependencies, and extracting the most relevant features for emotion classification. Building on top of BiLSTM, t...
2403.03558
Zhangyue Yin
Yuhong Sun, Zhangyue Yin, Qipeng Guo, Jiawen Wu, Xipeng Qiu, Hui Zhao
Benchmarking Hallucination in Large Language Models based on Unanswerable Math Word Problem
11 pages, 8 figures, accepted by LREC-Coling 2024
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Large language models (LLMs) are highly effective in various natural language processing (NLP) tasks. However, they are susceptible to producing unreliable conjectures in ambiguous contexts called hallucination. This paper presents a new method for evaluating LLM hallucination in Question Answering (QA) based on the ...
[ { "created": "Wed, 6 Mar 2024 09:06:34 GMT", "version": "v1" } ]
2024-03-07
[ [ "Sun", "Yuhong", "" ], [ "Yin", "Zhangyue", "" ], [ "Guo", "Qipeng", "" ], [ "Wu", "Jiawen", "" ], [ "Qiu", "Xipeng", "" ], [ "Zhao", "Hui", "" ] ]
Large language models (LLMs) are highly effective in various natural language processing (NLP) tasks. However, they are susceptible to producing unreliable conjectures in ambiguous contexts called hallucination. This paper presents a new method for evaluating LLM hallucination in Question Answering (QA) based on the un...
2306.06672
William Chen
William Chen, Xuankai Chang, Yifan Peng, Zhaoheng Ni, Soumi Maiti, Shinji Watanabe
Reducing Barriers to Self-Supervised Learning: HuBERT Pre-training with Academic Compute
Accepted at INTERSPEECH 2023
null
null
null
cs.CL cs.AI eess.AS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Self-supervised learning (SSL) has led to great strides in speech processing. However, the resources needed to train these models has become prohibitively large as they continue to scale. Currently, only a few groups with substantial resources are capable of creating SSL models, which harms reproducibility. In this w...
[ { "created": "Sun, 11 Jun 2023 12:53:46 GMT", "version": "v1" } ]
2023-06-13
[ [ "Chen", "William", "" ], [ "Chang", "Xuankai", "" ], [ "Peng", "Yifan", "" ], [ "Ni", "Zhaoheng", "" ], [ "Maiti", "Soumi", "" ], [ "Watanabe", "Shinji", "" ] ]
Self-supervised learning (SSL) has led to great strides in speech processing. However, the resources needed to train these models has become prohibitively large as they continue to scale. Currently, only a few groups with substantial resources are capable of creating SSL models, which harms reproducibility. In this wor...
cs/0510030
Amin Mobasher
Amin Mobasher, Mahmoud Taherzadeh, Renata Sotirov, and Amir K. Khandani
A Near Maximum Likelihood Decoding Algorithm for MIMO Systems Based on Semi-Definite Programming
Submitted to IEEE Trans. on Info. Theory, Revised
null
null
UW-E&CE#2005-12
cs.IT math.IT
null
In Multi-Input Multi-Output (MIMO) systems, Maximum-Likelihood (ML) decoding is equivalent to finding the closest lattice point in an N-dimensional complex space. In general, this problem is known to be NP hard. In this paper, we propose a quasi-maximum likelihood algorithm based on Semi-Definite Programming (SDP). W...
[ { "created": "Wed, 12 Oct 2005 00:35:23 GMT", "version": "v1" }, { "created": "Thu, 31 May 2007 15:03:45 GMT", "version": "v2" } ]
2007-07-13
[ [ "Mobasher", "Amin", "" ], [ "Taherzadeh", "Mahmoud", "" ], [ "Sotirov", "Renata", "" ], [ "Khandani", "Amir K.", "" ] ]
In Multi-Input Multi-Output (MIMO) systems, Maximum-Likelihood (ML) decoding is equivalent to finding the closest lattice point in an N-dimensional complex space. In general, this problem is known to be NP hard. In this paper, we propose a quasi-maximum likelihood algorithm based on Semi-Definite Programming (SDP). We ...
2111.10672
Adarsh Kumar
Adarsh Kumar, Kausik Subramanian, Shivaram Venkataraman, Aditya Akella
Doing More by Doing Less: How Structured Partial Backpropagation Improves Deep Learning Clusters
Accepted at DistributedML-2021
null
null
null
cs.DC cs.LG
http://creativecommons.org/licenses/by/4.0/
Many organizations employ compute clusters equipped with accelerators such as GPUs and TPUs for training deep learning models in a distributed fashion. Training is resource-intensive, consuming significant compute, memory, and network resources. Many prior works explore how to reduce training resource footprint witho...
[ { "created": "Sat, 20 Nov 2021 20:34:26 GMT", "version": "v1" } ]
2021-11-23
[ [ "Kumar", "Adarsh", "" ], [ "Subramanian", "Kausik", "" ], [ "Venkataraman", "Shivaram", "" ], [ "Akella", "Aditya", "" ] ]
Many organizations employ compute clusters equipped with accelerators such as GPUs and TPUs for training deep learning models in a distributed fashion. Training is resource-intensive, consuming significant compute, memory, and network resources. Many prior works explore how to reduce training resource footprint without...
2011.12563
Shan Lin
Shan Lin, Chang-Tsun Li, Alex C. Kot
Multi-Domain Adversarial Feature Generalization for Person Re-Identification
TIP (Accept with Mandatory Minor Revisions)
null
10.1109/TIP.2020.3046864
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
With the assistance of sophisticated training methods applied to single labeled datasets, the performance of fully-supervised person re-identification (Person Re-ID) has been improved significantly in recent years. However, these models trained on a single dataset usually suffer from considerable performance degradat...
[ { "created": "Wed, 25 Nov 2020 08:03:15 GMT", "version": "v1" } ]
2021-02-03
[ [ "Lin", "Shan", "" ], [ "Li", "Chang-Tsun", "" ], [ "Kot", "Alex C.", "" ] ]
With the assistance of sophisticated training methods applied to single labeled datasets, the performance of fully-supervised person re-identification (Person Re-ID) has been improved significantly in recent years. However, these models trained on a single dataset usually suffer from considerable performance degradatio...
1803.04360
Viktor Larsson
Viktor Larsson, Magnus Oskarsson, Kalle {\AA}str\"om, Alge Wallis, Zuzana Kukelova, Tomas Pajdla
Beyond Gr\"obner Bases: Basis Selection for Minimal Solvers
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Many computer vision applications require robust estimation of the underlying geometry, in terms of camera motion and 3D structure of the scene. These robust methods often rely on running minimal solvers in a RANSAC framework. In this paper we show how we can make polynomial solvers based on the action matrix method ...
[ { "created": "Mon, 12 Mar 2018 16:36:13 GMT", "version": "v1" } ]
2018-03-13
[ [ "Larsson", "Viktor", "" ], [ "Oskarsson", "Magnus", "" ], [ "Åström", "Kalle", "" ], [ "Wallis", "Alge", "" ], [ "Kukelova", "Zuzana", "" ], [ "Pajdla", "Tomas", "" ] ]
Many computer vision applications require robust estimation of the underlying geometry, in terms of camera motion and 3D structure of the scene. These robust methods often rely on running minimal solvers in a RANSAC framework. In this paper we show how we can make polynomial solvers based on the action matrix method fa...
2012.04456
Yingfan Wang
Yingfan Wang, Haiyang Huang, Cynthia Rudin, Yaron Shaposhnik
Understanding How Dimension Reduction Tools Work: An Empirical Approach to Deciphering t-SNE, UMAP, TriMAP, and PaCMAP for Data Visualization
null
Journal of Machine Learning Research 22(2021) 1-73
null
null
cs.LG stat.ML
http://creativecommons.org/licenses/by-sa/4.0/
Dimension reduction (DR) techniques such as t-SNE, UMAP, and TriMAP have demonstrated impressive visualization performance on many real world datasets. One tension that has always faced these methods is the trade-off between preservation of global structure and preservation of local structure: these methods can eithe...
[ { "created": "Tue, 8 Dec 2020 14:50:45 GMT", "version": "v1" }, { "created": "Tue, 24 Aug 2021 14:06:36 GMT", "version": "v2" } ]
2021-08-27
[ [ "Wang", "Yingfan", "" ], [ "Huang", "Haiyang", "" ], [ "Rudin", "Cynthia", "" ], [ "Shaposhnik", "Yaron", "" ] ]
Dimension reduction (DR) techniques such as t-SNE, UMAP, and TriMAP have demonstrated impressive visualization performance on many real world datasets. One tension that has always faced these methods is the trade-off between preservation of global structure and preservation of local structure: these methods can either ...
2308.06621
Richard Sattel
Richard Sattel, Christoph Spang, Carsten Heinz and Andreas Koch
PQC-HA: A Framework for Prototyping and In-Hardware Evaluation of Post-Quantum Cryptography Hardware Accelerators
20 pages, 6 figures, Open Source Software available
null
null
null
cs.CR cs.AR
http://creativecommons.org/licenses/by-sa/4.0/
In the third round of the NIST Post-Quantum Cryptography standardization project, the focus is on optimizing software and hardware implementations of candidate schemes. The winning schemes are CRYSTALS Kyber and CRYSTALS Dilithium, which serve as a Key Encapsulation Mechanism (KEM) and Digital Signature Algorithm (DS...
[ { "created": "Sat, 12 Aug 2023 17:35:39 GMT", "version": "v1" } ]
2023-08-15
[ [ "Sattel", "Richard", "" ], [ "Spang", "Christoph", "" ], [ "Heinz", "Carsten", "" ], [ "Koch", "Andreas", "" ] ]
In the third round of the NIST Post-Quantum Cryptography standardization project, the focus is on optimizing software and hardware implementations of candidate schemes. The winning schemes are CRYSTALS Kyber and CRYSTALS Dilithium, which serve as a Key Encapsulation Mechanism (KEM) and Digital Signature Algorithm (DSA)...
2103.16597
Pratik Mazumder
Pravendra Singh, Pratik Mazumder, Piyush Rai, Vinay P. Namboodiri
Rectification-based Knowledge Retention for Continual Learning
Accepted in CVPR 2021
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Deep learning models suffer from catastrophic forgetting when trained in an incremental learning setting. In this work, we propose a novel approach to address the task incremental learning problem, which involves training a model on new tasks that arrive in an incremental manner. The task incremental learning problem...
[ { "created": "Tue, 30 Mar 2021 18:11:30 GMT", "version": "v1" } ]
2021-04-01
[ [ "Singh", "Pravendra", "" ], [ "Mazumder", "Pratik", "" ], [ "Rai", "Piyush", "" ], [ "Namboodiri", "Vinay P.", "" ] ]
Deep learning models suffer from catastrophic forgetting when trained in an incremental learning setting. In this work, we propose a novel approach to address the task incremental learning problem, which involves training a model on new tasks that arrive in an incremental manner. The task incremental learning problem b...
1608.03960
Martin Kleppmann
Martin Kleppmann, Alastair R. Beresford
A Conflict-Free Replicated JSON Datatype
null
null
10.1109/TPDS.2017.2697382
null
cs.DC cs.DB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Many applications model their data in a general-purpose storage format such as JSON. This data structure is modified by the application as a result of user input. Such modifications are well understood if performed sequentially on a single copy of the data, but if the data is replicated and modified concurrently on m...
[ { "created": "Sat, 13 Aug 2016 09:48:35 GMT", "version": "v1" }, { "created": "Wed, 22 Mar 2017 10:32:25 GMT", "version": "v2" }, { "created": "Tue, 15 Aug 2017 15:00:24 GMT", "version": "v3" } ]
2017-08-16
[ [ "Kleppmann", "Martin", "" ], [ "Beresford", "Alastair R.", "" ] ]
Many applications model their data in a general-purpose storage format such as JSON. This data structure is modified by the application as a result of user input. Such modifications are well understood if performed sequentially on a single copy of the data, but if the data is replicated and modified concurrently on mul...
2106.03269
Rahul Aralikatte
Rahul Aralikatte, Miryam de Lhoneux, Anoop Kunchukuttan, Anders S{\o}gaard
Itihasa: A large-scale corpus for Sanskrit to English translation
Fixed typo
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This work introduces Itihasa, a large-scale translation dataset containing 93,000 pairs of Sanskrit shlokas and their English translations. The shlokas are extracted from two Indian epics viz., The Ramayana and The Mahabharata. We first describe the motivation behind the curation of such a dataset and follow up with ...
[ { "created": "Sun, 6 Jun 2021 22:58:13 GMT", "version": "v1" }, { "created": "Tue, 8 Jun 2021 16:48:17 GMT", "version": "v2" }, { "created": "Tue, 5 Oct 2021 20:13:42 GMT", "version": "v3" } ]
2021-10-07
[ [ "Aralikatte", "Rahul", "" ], [ "de Lhoneux", "Miryam", "" ], [ "Kunchukuttan", "Anoop", "" ], [ "Søgaard", "Anders", "" ] ]
This work introduces Itihasa, a large-scale translation dataset containing 93,000 pairs of Sanskrit shlokas and their English translations. The shlokas are extracted from two Indian epics viz., The Ramayana and The Mahabharata. We first describe the motivation behind the curation of such a dataset and follow up with em...
2401.10279
Sean Tucker
Sean Tucker
A systematic review of geospatial location embedding approaches in large language models: A path to spatial AI systems
20 pages, 11 figures, 3 appendices
null
null
null
cs.IR cs.AI cs.CL
http://creativecommons.org/licenses/by/4.0/
Geospatial Location Embedding (GLE) helps a Large Language Model (LLM) assimilate and analyze spatial data. GLE emergence in Geospatial Artificial Intelligence (GeoAI) is precipitated by the need for deeper geospatial awareness in our complex contemporary spaces and the success of LLMs in extracting deep meaning in G...
[ { "created": "Fri, 12 Jan 2024 12:43:33 GMT", "version": "v1" } ]
2024-01-22
[ [ "Tucker", "Sean", "" ] ]
Geospatial Location Embedding (GLE) helps a Large Language Model (LLM) assimilate and analyze spatial data. GLE emergence in Geospatial Artificial Intelligence (GeoAI) is precipitated by the need for deeper geospatial awareness in our complex contemporary spaces and the success of LLMs in extracting deep meaning in Gen...
1010.0219
Anthony Labarre
Anthony Labarre and Josef Cibulka
Polynomial-time sortable stacks of burnt pancakes
Accepted pending minor revision
Theor. Comput. Sci. 412(8-10): 695-702 (2011)
10.1016/j.tcs.2010.11.004
null
cs.DS math.CO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Pancake flipping, a famous open problem in computer science, can be formalised as the problem of sorting a permutation of positive integers using as few prefix reversals as possible. In that context, a prefix reversal of length k reverses the order of the first k elements of the permutation. The burnt variant of panc...
[ { "created": "Fri, 1 Oct 2010 17:22:31 GMT", "version": "v1" } ]
2011-02-07
[ [ "Labarre", "Anthony", "" ], [ "Cibulka", "Josef", "" ] ]
Pancake flipping, a famous open problem in computer science, can be formalised as the problem of sorting a permutation of positive integers using as few prefix reversals as possible. In that context, a prefix reversal of length k reverses the order of the first k elements of the permutation. The burnt variant of pancak...
2311.01912
Mahdi Bagheri
Mahdi Bagheri, Farhad Piri, Hadi Digale, Saem Sattarzadeh, Mohammad Reza Mohammadi
End-to-End assessment of AR-assisted neurosurgery systems
14 pages, 8figures
null
null
null
cs.HC cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Augmented Reality (AR) has emerged as a significant advancement in surgical procedures, offering a solution to the challenges posed by traditional neuronavigation methods. These conventional techniques often necessitate surgeons to split their focus between the surgical site and a separate monitor that displays guidi...
[ { "created": "Fri, 3 Nov 2023 13:41:44 GMT", "version": "v1" } ]
2023-11-06
[ [ "Bagheri", "Mahdi", "" ], [ "Piri", "Farhad", "" ], [ "Digale", "Hadi", "" ], [ "Sattarzadeh", "Saem", "" ], [ "Mohammadi", "Mohammad Reza", "" ] ]
Augmented Reality (AR) has emerged as a significant advancement in surgical procedures, offering a solution to the challenges posed by traditional neuronavigation methods. These conventional techniques often necessitate surgeons to split their focus between the surgical site and a separate monitor that displays guiding...
2106.10760
Francesco D'Angelo
Francesco D'Angelo, Vincent Fortuin, Florian Wenzel
On Stein Variational Neural Network Ensembles
null
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Ensembles of deep neural networks have achieved great success recently, but they do not offer a proper Bayesian justification. Moreover, while they allow for averaging of predictions over several hypotheses, they do not provide any guarantees for their diversity, leading to redundant solutions in function space. In c...
[ { "created": "Sun, 20 Jun 2021 21:52:46 GMT", "version": "v1" }, { "created": "Tue, 22 Jun 2021 07:53:17 GMT", "version": "v2" } ]
2021-06-23
[ [ "D'Angelo", "Francesco", "" ], [ "Fortuin", "Vincent", "" ], [ "Wenzel", "Florian", "" ] ]
Ensembles of deep neural networks have achieved great success recently, but they do not offer a proper Bayesian justification. Moreover, while they allow for averaging of predictions over several hypotheses, they do not provide any guarantees for their diversity, leading to redundant solutions in function space. In con...
2305.06518
Yinbin Ma
Yinbin Ma, Daniela Tuninetti
Demand Privacy in Hotplug Caching Systems
null
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Coded caching, introduced by Maddah-Ali and Niesen (MAN), is a model where a server broadcasts multicast packets to users with a local cache that is leveraged so as to reduce the peak network communication load. The original MAN model does not consider missing demands (i.e., some users may not request a file) or priv...
[ { "created": "Thu, 11 May 2023 01:42:37 GMT", "version": "v1" } ]
2023-05-12
[ [ "Ma", "Yinbin", "" ], [ "Tuninetti", "Daniela", "" ] ]
Coded caching, introduced by Maddah-Ali and Niesen (MAN), is a model where a server broadcasts multicast packets to users with a local cache that is leveraged so as to reduce the peak network communication load. The original MAN model does not consider missing demands (i.e., some users may not request a file) or privac...
2204.08563
Kang Liao
Kang Liao, Xiangyu Xu, Chunyu Lin, Wenqi Ren, Yunchao Wei, Yao Zhao
Cylin-Painting: Seamless {360\textdegree} Panoramic Image Outpainting and Beyond
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Image outpainting gains increasing attention since it can generate the complete scene from a partial view, providing a valuable solution to construct {360\textdegree} panoramic images. As image outpainting suffers from the intrinsic issue of unidirectional completion flow, previous methods convert the original proble...
[ { "created": "Mon, 18 Apr 2022 21:18:49 GMT", "version": "v1" }, { "created": "Sat, 9 Dec 2023 11:47:36 GMT", "version": "v2" } ]
2023-12-12
[ [ "Liao", "Kang", "" ], [ "Xu", "Xiangyu", "" ], [ "Lin", "Chunyu", "" ], [ "Ren", "Wenqi", "" ], [ "Wei", "Yunchao", "" ], [ "Zhao", "Yao", "" ] ]
Image outpainting gains increasing attention since it can generate the complete scene from a partial view, providing a valuable solution to construct {360\textdegree} panoramic images. As image outpainting suffers from the intrinsic issue of unidirectional completion flow, previous methods convert the original problem ...
2406.06918
Dewu Zheng
Dewu Zheng, Yanlin Wang, Ensheng Shi, Ruikai Zhang, Yuchi Ma, Hongyu Zhang, Zibin Zheng
Towards more realistic evaluation of LLM-based code generation: an experimental study and beyond
null
null
null
null
cs.SE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
To evaluate the code generation capabilities of Large Language Models (LLMs) in complex real-world software development scenarios, many evaluation approaches have been developed. They typically leverage contextual code from the latest version of a project to facilitate LLMs in accurately generating the desired functi...
[ { "created": "Tue, 11 Jun 2024 03:19:18 GMT", "version": "v1" } ]
2024-06-12
[ [ "Zheng", "Dewu", "" ], [ "Wang", "Yanlin", "" ], [ "Shi", "Ensheng", "" ], [ "Zhang", "Ruikai", "" ], [ "Ma", "Yuchi", "" ], [ "Zhang", "Hongyu", "" ], [ "Zheng", "Zibin", "" ] ]
To evaluate the code generation capabilities of Large Language Models (LLMs) in complex real-world software development scenarios, many evaluation approaches have been developed. They typically leverage contextual code from the latest version of a project to facilitate LLMs in accurately generating the desired function...
1411.6836
Mircea Cimpoi
Mircea Cimpoi, Subhransu Maji, Andrea Vedaldi
Deep convolutional filter banks for texture recognition and segmentation
Accepted to CVPR15
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Research in texture recognition often concentrates on the problem of material recognition in uncluttered conditions, an assumption rarely met by applications. In this work we conduct a first study of material and describable texture at- tributes recognition in clutter, using a new dataset derived from the OpenSurface...
[ { "created": "Tue, 25 Nov 2014 12:36:23 GMT", "version": "v1" }, { "created": "Thu, 9 Jul 2015 18:25:43 GMT", "version": "v2" } ]
2015-07-10
[ [ "Cimpoi", "Mircea", "" ], [ "Maji", "Subhransu", "" ], [ "Vedaldi", "Andrea", "" ] ]
Research in texture recognition often concentrates on the problem of material recognition in uncluttered conditions, an assumption rarely met by applications. In this work we conduct a first study of material and describable texture at- tributes recognition in clutter, using a new dataset derived from the OpenSurface t...
1104.3219
Yi-Ling Chen
De-Nian Yang (Academia Sinica), Yi-Ling Chen (National Taiwan University), Wang-Chien Lee (The Penn State University), Ming-Syan Chen (National Taiwan University)
On Social-Temporal Group Query with Acquaintance Constraint
VLDB2011
Proceedings of the VLDB Endowment (PVLDB), Vol. 4, No. 6, pp. 397-408 (2011)
null
null
cs.SI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Three essential criteria are important for activity planning, including: (1) finding a group of attendees familiar with the initiator, (2) ensuring each attendee in the group to have tight social relations with most of the members in the group, and (3) selecting an activity period available for all attendees. Therefo...
[ { "created": "Sat, 16 Apr 2011 08:55:24 GMT", "version": "v1" } ]
2011-04-19
[ [ "Yang", "De-Nian", "", "Academia Sinica" ], [ "Chen", "Yi-Ling", "", "National Taiwan\n University" ], [ "Lee", "Wang-Chien", "", "The Penn State University" ], [ "Chen", "Ming-Syan", "", "National Taiwan University" ] ]
Three essential criteria are important for activity planning, including: (1) finding a group of attendees familiar with the initiator, (2) ensuring each attendee in the group to have tight social relations with most of the members in the group, and (3) selecting an activity period available for all attendees. Therefore...
2109.01688
Michael Correll
Gerrit J. Rijken, Rene Cutura, Frank Heyen, Michael Sedlmair, Michael Correll, Jason Dykes, Noeska Smit
Illegible Semantics: Exploring the Design Space of Metal Logos
null
null
null
null
cs.HC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The logos of metal bands can be by turns gaudy, uncouth, or nearly illegible. Yet, these logos work: they communicate sophisticated notions of genre and emotional affect. In this paper we use the design considerations of metal logos to explore the space of "illegible semantics": the ways that text can communicate inf...
[ { "created": "Fri, 3 Sep 2021 18:02:17 GMT", "version": "v1" } ]
2021-09-07
[ [ "Rijken", "Gerrit J.", "" ], [ "Cutura", "Rene", "" ], [ "Heyen", "Frank", "" ], [ "Sedlmair", "Michael", "" ], [ "Correll", "Michael", "" ], [ "Dykes", "Jason", "" ], [ "Smit", "Noeska", "" ] ]
The logos of metal bands can be by turns gaudy, uncouth, or nearly illegible. Yet, these logos work: they communicate sophisticated notions of genre and emotional affect. In this paper we use the design considerations of metal logos to explore the space of "illegible semantics": the ways that text can communicate infor...
2408.02680
David Gamez
Dionis Barcari, David Gamez and Aliya Grig
Recording First-person Experiences to Build a New Type of Foundation Model
5 pages, 5 figures, 3 tables. arXiv admin note: substantial text overlap with arXiv:2408.00030
null
null
null
cs.AI cs.HC cs.LG
http://creativecommons.org/licenses/by-nc-sa/4.0/
Foundation models have had a big impact in recent years and billions of dollars are being invested in them in the current AI boom. The more popular ones, such as Chat-GPT, are trained on large amounts of Internet data. However, it is becoming apparent that this data is likely to be exhausted soon, and technology comp...
[ { "created": "Wed, 31 Jul 2024 11:51:26 GMT", "version": "v1" } ]
2024-08-07
[ [ "Barcari", "Dionis", "" ], [ "Gamez", "David", "" ], [ "Grig", "Aliya", "" ] ]
Foundation models have had a big impact in recent years and billions of dollars are being invested in them in the current AI boom. The more popular ones, such as Chat-GPT, are trained on large amounts of Internet data. However, it is becoming apparent that this data is likely to be exhausted soon, and technology compan...
1807.05365
Bichuan Guo
Bichuan Guo, Yuxing Han, Jiangtao Wen
Fast Block Structure Determination in AV1-based Multiple Resolutions Video Encoding
published in IEEE International Conference on Multimedia and Expo, 2018
null
10.1109/ICME.2018.8486492
null
cs.MM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The widely used adaptive HTTP streaming requires an efficient algorithm to encode the same video to different resolutions. In this paper, we propose a fast block structure determination algorithm based on the AV1 codec that accelerates high resolution encoding, which is the bottle-neck of multiple resolutions encodin...
[ { "created": "Sat, 14 Jul 2018 09:29:57 GMT", "version": "v1" } ]
2018-10-17
[ [ "Guo", "Bichuan", "" ], [ "Han", "Yuxing", "" ], [ "Wen", "Jiangtao", "" ] ]
The widely used adaptive HTTP streaming requires an efficient algorithm to encode the same video to different resolutions. In this paper, we propose a fast block structure determination algorithm based on the AV1 codec that accelerates high resolution encoding, which is the bottle-neck of multiple resolutions encoding....
2307.05219
David Rapado-Rincon
David Rapado-Rincon, Eldert J. van Henten, Gert Kootstra
MinkSORT: A 3D deep feature extractor using sparse convolutions to improve 3D multi-object tracking in greenhouse tomato plants
null
null
null
null
cs.RO
http://creativecommons.org/licenses/by/4.0/
The agro-food industry is turning to robots to address the challenge of labour shortage. However, agro-food environments pose difficulties for robots due to high variation and occlusions. In the presence of these challenges, accurate world models, with information about object location, shape, and properties, are cru...
[ { "created": "Tue, 11 Jul 2023 12:44:06 GMT", "version": "v1" } ]
2023-07-12
[ [ "Rapado-Rincon", "David", "" ], [ "van Henten", "Eldert J.", "" ], [ "Kootstra", "Gert", "" ] ]
The agro-food industry is turning to robots to address the challenge of labour shortage. However, agro-food environments pose difficulties for robots due to high variation and occlusions. In the presence of these challenges, accurate world models, with information about object location, shape, and properties, are cruci...
1803.05123
Derui Derek Wang
Derek Wang, Chaoran Li, Sheng Wen, Surya Nepal, Yang Xiang
Defending against Adversarial Attack towards Deep Neural Networks via Collaborative Multi-task Training
12 pages, 7 figures
null
null
null
cs.LG cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Deep neural networks (DNNs) are known to be vulnerable to adversarial examples which contain human-imperceptible perturbations. A series of defending methods, either proactive defence or reactive defence, have been proposed in the recent years. However, most of the methods can only handle specific attacks. For exampl...
[ { "created": "Wed, 14 Mar 2018 03:41:18 GMT", "version": "v1" }, { "created": "Tue, 3 Jul 2018 15:41:43 GMT", "version": "v2" }, { "created": "Wed, 5 Dec 2018 03:31:25 GMT", "version": "v3" }, { "created": "Fri, 24 Jul 2020 06:01:08 GMT", "version": "v4" } ]
2020-07-27
[ [ "Wang", "Derek", "" ], [ "Li", "Chaoran", "" ], [ "Wen", "Sheng", "" ], [ "Nepal", "Surya", "" ], [ "Xiang", "Yang", "" ] ]
Deep neural networks (DNNs) are known to be vulnerable to adversarial examples which contain human-imperceptible perturbations. A series of defending methods, either proactive defence or reactive defence, have been proposed in the recent years. However, most of the methods can only handle specific attacks. For example,...
2305.19512
Yiwei Lyu
Yiwei Lyu, Tiange Luo, Jiacheng Shi, Todd C. Hollon, Honglak Lee
Fine-grained Text Style Transfer with Diffusion-Based Language Models
Accepted at Repl4NLP workshop at ACL 2023
null
null
null
cs.CL cs.AI cs.LG
http://creativecommons.org/licenses/by/4.0/
Diffusion probabilistic models have shown great success in generating high-quality images controllably, and researchers have tried to utilize this controllability into text generation domain. Previous works on diffusion-based language models have shown that they can be trained without external knowledge (such as pre-...
[ { "created": "Wed, 31 May 2023 02:51:26 GMT", "version": "v1" }, { "created": "Mon, 12 Jun 2023 02:13:16 GMT", "version": "v2" } ]
2023-06-13
[ [ "Lyu", "Yiwei", "" ], [ "Luo", "Tiange", "" ], [ "Shi", "Jiacheng", "" ], [ "Hollon", "Todd C.", "" ], [ "Lee", "Honglak", "" ] ]
Diffusion probabilistic models have shown great success in generating high-quality images controllably, and researchers have tried to utilize this controllability into text generation domain. Previous works on diffusion-based language models have shown that they can be trained without external knowledge (such as pre-tr...
2109.14126
Andrew Berns
Andrew Berns
Network Scaffolding for Efficient Stabilization of the Chord Overlay Network
null
null
null
null
cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Overlay networks, where nodes communicate with neighbors over logical links consisting of zero or more physical links, have become an important part of modern networking. From data centers to IoT devices, overlay networks are used to organize a diverse set of processes for efficient operations like searching and rout...
[ { "created": "Wed, 29 Sep 2021 01:14:57 GMT", "version": "v1" } ]
2021-09-30
[ [ "Berns", "Andrew", "" ] ]
Overlay networks, where nodes communicate with neighbors over logical links consisting of zero or more physical links, have become an important part of modern networking. From data centers to IoT devices, overlay networks are used to organize a diverse set of processes for efficient operations like searching and routin...
2403.12223
Chinmaya Mishra
Chinmaya Mishra, Anuj Nandanwar and Sashikala Mishra
HRI in Indian Education: Challenges Opportunities
Presented at the Designing an Intro to HRI Course Workshop at HRI 2024 (arXiv:2403.05588)
null
null
HRI101/2024/9
cs.RO cs.HC
http://creativecommons.org/licenses/by/4.0/
With the recent advancements in the field of robotics and the increased focus on having general-purpose robots widely available to the general public, it has become increasingly necessary to pursue research into Human-robot interaction (HRI). While there have been a lot of works discussing frameworks for teaching HRI...
[ { "created": "Mon, 18 Mar 2024 20:11:02 GMT", "version": "v1" } ]
2024-03-20
[ [ "Mishra", "Chinmaya", "" ], [ "Nandanwar", "Anuj", "" ], [ "Mishra", "Sashikala", "" ] ]
With the recent advancements in the field of robotics and the increased focus on having general-purpose robots widely available to the general public, it has become increasingly necessary to pursue research into Human-robot interaction (HRI). While there have been a lot of works discussing frameworks for teaching HRI i...
2407.09493
Warmhold Jan Thomas Mollema
W.J.T. Mollema
Social AI and The Equation of Wittgenstein's Language User With Calvino's Literature Machine
null
International Review of Literary Studies, 6, no.1 (2024): 39-55
10.53057/irls/2024.6.1.4
null
cs.HC cs.AI
http://creativecommons.org/licenses/by/4.0/
Is it sensical to ascribe psychological predicates to AI systems like chatbots based on large language models (LLMs)? People have intuitively started ascribing emotions or consciousness to social AI ('affective artificial agents'), with consequences that range from love to suicide. The philosophical question of wheth...
[ { "created": "Thu, 23 May 2024 09:51:44 GMT", "version": "v1" } ]
2024-07-16
[ [ "Mollema", "W. J. T.", "" ] ]
Is it sensical to ascribe psychological predicates to AI systems like chatbots based on large language models (LLMs)? People have intuitively started ascribing emotions or consciousness to social AI ('affective artificial agents'), with consequences that range from love to suicide. The philosophical question of whether...
1006.0475
Alexey Chernov
Alexey Chernov and Vladimir Vovk
Prediction with Advice of Unknown Number of Experts
22 pages; draft version
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In the framework of prediction with expert advice, we consider a recently introduced kind of regret bounds: the bounds that depend on the effective instead of nominal number of experts. In contrast to the NormalHedge bound, which mainly depends on the effective number of experts and also weakly depends on the nominal...
[ { "created": "Wed, 2 Jun 2010 19:41:27 GMT", "version": "v1" } ]
2015-03-17
[ [ "Chernov", "Alexey", "" ], [ "Vovk", "Vladimir", "" ] ]
In the framework of prediction with expert advice, we consider a recently introduced kind of regret bounds: the bounds that depend on the effective instead of nominal number of experts. In contrast to the NormalHedge bound, which mainly depends on the effective number of experts and also weakly depends on the nominal o...
2003.00476
Jumabek Alikhanov
Azizjon Meliboev, Jumabek Alikhanov, Wooseong Kim
1D CNN Based Network Intrusion Detection with Normalization on Imbalanced Data
Need more polishing
IEEE ICAIIC 2020
null
null
cs.CR cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Intrusion detection system (IDS) plays an essential role in computer networks protecting computing resources and data from outside attacks. Recent IDS faces challenges improving flexibility and efficiency of the IDS for unexpected and unpredictable attacks. Deep neural network (DNN) is considered popularly for comple...
[ { "created": "Sun, 1 Mar 2020 12:23:46 GMT", "version": "v1" }, { "created": "Wed, 4 Mar 2020 09:44:56 GMT", "version": "v2" } ]
2020-03-05
[ [ "Meliboev", "Azizjon", "" ], [ "Alikhanov", "Jumabek", "" ], [ "Kim", "Wooseong", "" ] ]
Intrusion detection system (IDS) plays an essential role in computer networks protecting computing resources and data from outside attacks. Recent IDS faces challenges improving flexibility and efficiency of the IDS for unexpected and unpredictable attacks. Deep neural network (DNN) is considered popularly for complex ...
2211.01122
Feihu Huang
Feihu Huang
Fast Adaptive Federated Bilevel Optimization
49 pages. arXiv admin note: text overlap with arXiv:2106.11396
null
null
null
cs.LG math.OC
http://creativecommons.org/licenses/by-nc-sa/4.0/
Bilevel optimization is a popular hierarchical model in machine learning, and has been widely applied to many machine learning tasks such as meta learning, hyperparameter learning and policy optimization. Although many bilevel optimization algorithms recently have been developed, few adaptive algorithm focuses on the...
[ { "created": "Wed, 2 Nov 2022 13:55:47 GMT", "version": "v1" }, { "created": "Thu, 3 Nov 2022 15:12:55 GMT", "version": "v2" }, { "created": "Mon, 14 Nov 2022 12:27:06 GMT", "version": "v3" } ]
2022-11-15
[ [ "Huang", "Feihu", "" ] ]
Bilevel optimization is a popular hierarchical model in machine learning, and has been widely applied to many machine learning tasks such as meta learning, hyperparameter learning and policy optimization. Although many bilevel optimization algorithms recently have been developed, few adaptive algorithm focuses on the b...
2203.13947
Bingsheng Yao
Ying Xu, Dakuo Wang, Mo Yu, Daniel Ritchie, Bingsheng Yao, Tongshuang Wu, Zheng Zhang, Toby Jia-Jun Li, Nora Bradford, Branda Sun, Tran Bao Hoang, Yisi Sang, Yufang Hou, Xiaojuan Ma, Diyi Yang, Nanyun Peng, Zhou Yu, Mark Warschauer
Fantastic Questions and Where to Find Them: FairytaleQA -- An Authentic Dataset for Narrative Comprehension
Accepted to ACL 2022
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Question answering (QA) is a fundamental means to facilitate assessment and training of narrative comprehension skills for both machines and young children, yet there is scarcity of high-quality QA datasets carefully designed to serve this purpose. In particular, existing datasets rarely distinguish fine-grained read...
[ { "created": "Sat, 26 Mar 2022 00:20:05 GMT", "version": "v1" } ]
2022-03-29
[ [ "Xu", "Ying", "" ], [ "Wang", "Dakuo", "" ], [ "Yu", "Mo", "" ], [ "Ritchie", "Daniel", "" ], [ "Yao", "Bingsheng", "" ], [ "Wu", "Tongshuang", "" ], [ "Zhang", "Zheng", "" ], [ "Li", "Toby Jia-...
Question answering (QA) is a fundamental means to facilitate assessment and training of narrative comprehension skills for both machines and young children, yet there is scarcity of high-quality QA datasets carefully designed to serve this purpose. In particular, existing datasets rarely distinguish fine-grained readin...
1804.11191
Zhuwei Qin
Zhuwei Qin, Fuxun Yu, Chenchen Liu and Xiang Chen
How convolutional neural network see the world - A survey of convolutional neural network visualization methods
32 pages, 21 figures. Mathematical Foundations of Computing
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Nowadays, the Convolutional Neural Networks (CNNs) have achieved impressive performance on many computer vision related tasks, such as object detection, image recognition, image retrieval, etc. These achievements benefit from the CNNs outstanding capability to learn the input features with deep layers of neuron struc...
[ { "created": "Mon, 30 Apr 2018 13:47:11 GMT", "version": "v1" }, { "created": "Thu, 31 May 2018 20:12:43 GMT", "version": "v2" } ]
2018-06-04
[ [ "Qin", "Zhuwei", "" ], [ "Yu", "Fuxun", "" ], [ "Liu", "Chenchen", "" ], [ "Chen", "Xiang", "" ] ]
Nowadays, the Convolutional Neural Networks (CNNs) have achieved impressive performance on many computer vision related tasks, such as object detection, image recognition, image retrieval, etc. These achievements benefit from the CNNs outstanding capability to learn the input features with deep layers of neuron structu...