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1510.00651
Mark Scanlon
Jason Farina, M-Tahar Kechadi and Mark Scanlon
Project Maelstrom: Forensic Analysis of the BitTorrent-Powered Browser
null
Journal of Digital Forensics, Security and Law (Proc. of 10th International Conference on Systematic Approaches to Digital Forensic Engineering, SADFE 2015)
null
null
cs.CR
http://creativecommons.org/licenses/by-nc-sa/4.0/
In April 2015, BitTorrent Inc. released their distributed peer-to-peer powered browser, Project Maelstrom, into public beta. The browser facilitates a new alternative website distribution paradigm to the traditional HTTP-based, client-server model. This decentralised web is powered by each of the visitors accessing e...
[ { "created": "Fri, 2 Oct 2015 17:25:27 GMT", "version": "v1" } ]
2015-10-05
[ [ "Farina", "Jason", "" ], [ "Kechadi", "M-Tahar", "" ], [ "Scanlon", "Mark", "" ] ]
In April 2015, BitTorrent Inc. released their distributed peer-to-peer powered browser, Project Maelstrom, into public beta. The browser facilitates a new alternative website distribution paradigm to the traditional HTTP-based, client-server model. This decentralised web is powered by each of the visitors accessing eac...
2406.06236
Tahira Shehzadi
Talha Uddin Sheikh, Tahira Shehzadi, Khurram Azeem Hashmi, Didier Stricker, Muhammad Zeshan Afzal
UnSupDLA: Towards Unsupervised Document Layout Analysis
ICDAR 2024 - Workshop
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Document layout analysis is a key area in document research, involving techniques like text mining and visual analysis. Despite various methods developed to tackle layout analysis, a critical but frequently overlooked problem is the scarcity of labeled data needed for analyses. With the rise of internet use, an overw...
[ { "created": "Mon, 10 Jun 2024 13:06:28 GMT", "version": "v1" } ]
2024-06-11
[ [ "Sheikh", "Talha Uddin", "" ], [ "Shehzadi", "Tahira", "" ], [ "Hashmi", "Khurram Azeem", "" ], [ "Stricker", "Didier", "" ], [ "Afzal", "Muhammad Zeshan", "" ] ]
Document layout analysis is a key area in document research, involving techniques like text mining and visual analysis. Despite various methods developed to tackle layout analysis, a critical but frequently overlooked problem is the scarcity of labeled data needed for analyses. With the rise of internet use, an overwhe...
2312.16697
He Zhang
He Zhang, Robin Ananda, Xinyi Fu, Zhe Sun, Xiaoyu Wang, Keqi Chen, John M. Carroll
Multi-channel Sensor Network Construction, Data Fusion and Challenges for Smart Home
8 pages, accepted by CHCHI2023
null
null
null
cs.HC
http://creativecommons.org/licenses/by/4.0/
Both sensor networks and data fusion are essential foundations for developing the smart home Internet of Things (IoT) and related fields. We proposed a multi-channel sensor network construction method involving hardware, acquisition, and synchronization in the smart home environment and a smart home data fusion metho...
[ { "created": "Wed, 27 Dec 2023 19:30:43 GMT", "version": "v1" } ]
2023-12-29
[ [ "Zhang", "He", "" ], [ "Ananda", "Robin", "" ], [ "Fu", "Xinyi", "" ], [ "Sun", "Zhe", "" ], [ "Wang", "Xiaoyu", "" ], [ "Chen", "Keqi", "" ], [ "Carroll", "John M.", "" ] ]
Both sensor networks and data fusion are essential foundations for developing the smart home Internet of Things (IoT) and related fields. We proposed a multi-channel sensor network construction method involving hardware, acquisition, and synchronization in the smart home environment and a smart home data fusion method ...
1312.1961
Christian Lavault
Marc Bui (CHART), Franck Butelle (LIPN), Christian Lavault (LIPN)
A Distributed Algorithm for Constructing a Minimum Diameter Spanning Tree
Comments: 11 pages LaTeX, 2 figures; International Journal with referees article; New version (full paper design): results added in Section 2.2 and 2.2; typos removed
Journal of Parallel and Distributed Computing 64, 5 (2004) 571-577
null
null
cs.DC cs.DS cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present a new algorithm, which solves the problem of distributively finding a minimum diameter spanning tree of any (non-negatively) real-weighted graph $G = (V,E,\omega)$. As an intermediate step, we use a new, fast, linear-time all-pairs shortest paths distributed algorithm to find an absolute center of $G$. The...
[ { "created": "Fri, 6 Dec 2013 19:04:02 GMT", "version": "v1" }, { "created": "Wed, 11 Dec 2013 08:09:33 GMT", "version": "v2" } ]
2013-12-12
[ [ "Bui", "Marc", "", "CHART" ], [ "Butelle", "Franck", "", "LIPN" ], [ "Lavault", "Christian", "", "LIPN" ] ]
We present a new algorithm, which solves the problem of distributively finding a minimum diameter spanning tree of any (non-negatively) real-weighted graph $G = (V,E,\omega)$. As an intermediate step, we use a new, fast, linear-time all-pairs shortest paths distributed algorithm to find an absolute center of $G$. The r...
1906.12087
Zhangheng Li
Zhangheng Li, Jia-Xing Zhong, Jingjia Huang, Tao Zhang, Thomas Li and Ge Li
ARMIN: Towards a More Efficient and Light-weight Recurrent Memory Network
Published in IJCAI 2019
null
null
null
cs.LG cs.NE stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In recent years, memory-augmented neural networks(MANNs) have shown promising power to enhance the memory ability of neural networks for sequential processing tasks. However, previous MANNs suffer from complex memory addressing mechanism, making them relatively hard to train and causing computational overheads. Moreo...
[ { "created": "Fri, 28 Jun 2019 08:21:49 GMT", "version": "v1" } ]
2019-07-01
[ [ "Li", "Zhangheng", "" ], [ "Zhong", "Jia-Xing", "" ], [ "Huang", "Jingjia", "" ], [ "Zhang", "Tao", "" ], [ "Li", "Thomas", "" ], [ "Li", "Ge", "" ] ]
In recent years, memory-augmented neural networks(MANNs) have shown promising power to enhance the memory ability of neural networks for sequential processing tasks. However, previous MANNs suffer from complex memory addressing mechanism, making them relatively hard to train and causing computational overheads. Moreove...
2004.02335
David Arnas
David Arnas and Carl Leake and Daniele Mortari
The n-dimensional k-vector and its application to orthogonal range searching
31 pages, 10 figures
Applied Mathematics and Computation, Vol. 372, 2020
10.1016/j.amc.2019.125010
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This work focuses on the definition and study of the n-dimensional k-vector, an algorithm devised to perform orthogonal range searching in static databases with multiple dimensions. The methodology first finds the order in which to search the dimensions, and then, performs the search using a modified projection metho...
[ { "created": "Sun, 5 Apr 2020 22:26:05 GMT", "version": "v1" } ]
2020-04-07
[ [ "Arnas", "David", "" ], [ "Leake", "Carl", "" ], [ "Mortari", "Daniele", "" ] ]
This work focuses on the definition and study of the n-dimensional k-vector, an algorithm devised to perform orthogonal range searching in static databases with multiple dimensions. The methodology first finds the order in which to search the dimensions, and then, performs the search using a modified projection method....
2402.00357
Yichen Zhu
Xin Liu, Yichen Zhu, Yunshi Lan, Chao Yang, Yu Qiao
Safety of Multimodal Large Language Models on Images and Texts
Accepted at IJCAI2024
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Attracted by the impressive power of Multimodal Large Language Models (MLLMs), the public is increasingly utilizing them to improve the efficiency of daily work. Nonetheless, the vulnerabilities of MLLMs to unsafe instructions bring huge safety risks when these models are deployed in real-world scenarios. In this pap...
[ { "created": "Thu, 1 Feb 2024 05:57:10 GMT", "version": "v1" }, { "created": "Sun, 25 Feb 2024 03:20:54 GMT", "version": "v2" }, { "created": "Thu, 20 Jun 2024 15:06:10 GMT", "version": "v3" } ]
2024-06-21
[ [ "Liu", "Xin", "" ], [ "Zhu", "Yichen", "" ], [ "Lan", "Yunshi", "" ], [ "Yang", "Chao", "" ], [ "Qiao", "Yu", "" ] ]
Attracted by the impressive power of Multimodal Large Language Models (MLLMs), the public is increasingly utilizing them to improve the efficiency of daily work. Nonetheless, the vulnerabilities of MLLMs to unsafe instructions bring huge safety risks when these models are deployed in real-world scenarios. In this paper...
1809.04898
Michele Colledanchise
Michele Colledanchise and Lorenzo Natale
Improving the Parallel Execution of Behavior Trees
null
2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
10.1109/IROS.2018.8593504
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Behavior Trees (BTs) have become a popular framework for designing controllers of autonomous agents in the computer game and in the robotics industry. One of the key advantages of BTs lies in their modularity, where independent modules can be composed to create more complex ones. In the classical formulation of BTs, ...
[ { "created": "Thu, 13 Sep 2018 11:58:31 GMT", "version": "v1" } ]
2021-08-25
[ [ "Colledanchise", "Michele", "" ], [ "Natale", "Lorenzo", "" ] ]
Behavior Trees (BTs) have become a popular framework for designing controllers of autonomous agents in the computer game and in the robotics industry. One of the key advantages of BTs lies in their modularity, where independent modules can be composed to create more complex ones. In the classical formulation of BTs, mo...
2107.02308
Joseph Ortiz
Joseph Ortiz, Talfan Evans, Andrew J. Davison
A visual introduction to Gaussian Belief Propagation
See online version of this article: https://gaussianbp.github.io/
null
null
null
cs.AI cs.CV cs.LG cs.RO
http://creativecommons.org/licenses/by/4.0/
In this article, we present a visual introduction to Gaussian Belief Propagation (GBP), an approximate probabilistic inference algorithm that operates by passing messages between the nodes of arbitrarily structured factor graphs. A special case of loopy belief propagation, GBP updates rely only on local information a...
[ { "created": "Mon, 5 Jul 2021 22:43:27 GMT", "version": "v1" } ]
2021-07-07
[ [ "Ortiz", "Joseph", "" ], [ "Evans", "Talfan", "" ], [ "Davison", "Andrew J.", "" ] ]
In this article, we present a visual introduction to Gaussian Belief Propagation (GBP), an approximate probabilistic inference algorithm that operates by passing messages between the nodes of arbitrarily structured factor graphs. A special case of loopy belief propagation, GBP updates rely only on local information and...
1012.5929
Joel Goossens
Jo\"el Goossens (1), Patrick Meumeu Yomsi (2) ((1) Brussels University, U.L.B., Brussels, Belgium., (2) F.N.R.S, Belgium.)
Exact Schedulability Test for global-EDF Scheduling of Periodic Hard Real-Time Tasks on Identical Multiprocessors
null
null
null
null
cs.OS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper we consider the scheduling problem of hard real-time systems composed of periodic constrained-deadline tasks upon identical multiprocessor platforms. We assume that tasks are scheduled by using the global-EDF scheduler. We establish an exact schedulability test for this scheduler by exploiting on the on...
[ { "created": "Wed, 29 Dec 2010 12:41:13 GMT", "version": "v1" } ]
2010-12-30
[ [ "Goossens", "Joël", "" ], [ "Yomsi", "Patrick Meumeu", "" ] ]
In this paper we consider the scheduling problem of hard real-time systems composed of periodic constrained-deadline tasks upon identical multiprocessor platforms. We assume that tasks are scheduled by using the global-EDF scheduler. We establish an exact schedulability test for this scheduler by exploiting on the one ...
2310.06125
William Ravenscroft
William Ravenscroft and Stefan Goetze and Thomas Hain
On Time Domain Conformer Models for Monaural Speech Separation in Noisy Reverberant Acoustic Environments
Accepted at ASRU Workshop 2023
null
null
null
cs.SD cs.AI cs.LG eess.AS
http://creativecommons.org/licenses/by/4.0/
Speech separation remains an important topic for multi-speaker technology researchers. Convolution augmented transformers (conformers) have performed well for many speech processing tasks but have been under-researched for speech separation. Most recent state-of-the-art (SOTA) separation models have been time-domain ...
[ { "created": "Mon, 9 Oct 2023 20:02:11 GMT", "version": "v1" } ]
2023-10-11
[ [ "Ravenscroft", "William", "" ], [ "Goetze", "Stefan", "" ], [ "Hain", "Thomas", "" ] ]
Speech separation remains an important topic for multi-speaker technology researchers. Convolution augmented transformers (conformers) have performed well for many speech processing tasks but have been under-researched for speech separation. Most recent state-of-the-art (SOTA) separation models have been time-domain au...
2401.01752
Zheng Yuan
Zheng Yuan, Jie Zhang, Shiguang Shan
FullLoRA-AT: Efficiently Boosting the Robustness of Pretrained Vision Transformers
10 pages, 2 figures, 6 tables
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In recent years, the Vision Transformer (ViT) model has gradually become mainstream in various computer vision tasks, and the robustness of the model has received increasing attention. However, existing large models tend to prioritize performance during training, potentially neglecting the robustness, which may lead ...
[ { "created": "Wed, 3 Jan 2024 14:08:39 GMT", "version": "v1" } ]
2024-01-04
[ [ "Yuan", "Zheng", "" ], [ "Zhang", "Jie", "" ], [ "Shan", "Shiguang", "" ] ]
In recent years, the Vision Transformer (ViT) model has gradually become mainstream in various computer vision tasks, and the robustness of the model has received increasing attention. However, existing large models tend to prioritize performance during training, potentially neglecting the robustness, which may lead to...
2402.18927
Jiayuan Chen
Xiang Chen, Wenjie Zhu, Jiayuan Chen, Tong Zhang, Changyan Yi, Jun Cai
Edge Computing Enabled Real-Time Video Analysis via Adaptive Spatial-Temporal Semantic Filtering
null
null
null
null
cs.CV cs.MM cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper proposes a novel edge computing enabled real-time video analysis system for intelligent visual devices. The proposed system consists of a tracking-assisted object detection module (TAODM) and a region of interesting module (ROIM). TAODM adaptively determines the offloading decision to process each video fr...
[ { "created": "Thu, 29 Feb 2024 07:42:03 GMT", "version": "v1" } ]
2024-03-01
[ [ "Chen", "Xiang", "" ], [ "Zhu", "Wenjie", "" ], [ "Chen", "Jiayuan", "" ], [ "Zhang", "Tong", "" ], [ "Yi", "Changyan", "" ], [ "Cai", "Jun", "" ] ]
This paper proposes a novel edge computing enabled real-time video analysis system for intelligent visual devices. The proposed system consists of a tracking-assisted object detection module (TAODM) and a region of interesting module (ROIM). TAODM adaptively determines the offloading decision to process each video fram...
2201.13348
Stefan H\"oppner
Stefan H\"oppner, Yves Haas, Matthias Tichy, Katharina Juhnke
Advantages and Disadvantages of (Dedicated) Model Transformation Languages A Qualitative Interview Study
null
null
10.1007/s10664-022-10194-7
null
cs.SE
http://creativecommons.org/licenses/by/4.0/
Model driven development envisages the use of model transformations to evolve models. Model transformation languages, developed for this task, are touted with many benefits over general purpose programming languages. However, a large number of these claims have not yet been substantiated. They are also made without t...
[ { "created": "Mon, 31 Jan 2022 16:52:59 GMT", "version": "v1" }, { "created": "Thu, 5 May 2022 16:51:40 GMT", "version": "v2" }, { "created": "Mon, 4 Jul 2022 10:42:13 GMT", "version": "v3" } ]
2022-08-19
[ [ "Höppner", "Stefan", "" ], [ "Haas", "Yves", "" ], [ "Tichy", "Matthias", "" ], [ "Juhnke", "Katharina", "" ] ]
Model driven development envisages the use of model transformations to evolve models. Model transformation languages, developed for this task, are touted with many benefits over general purpose programming languages. However, a large number of these claims have not yet been substantiated. They are also made without the...
1806.07815
Nicolas Robinson-Garcia
Nicolas Robinson-Garcia, Cassidy R. Sugimoto, Dakota Murray, Alfredo Yegros-Yegros, Vincent Larivi\`ere and Rodrigo Costas
Scientific mobility indicators in practice: International mobility profiles at the country level
null
Robinson-Garcia, N. et al. Scientific mobility indicators in practice: International mobility profiles at the country level. El profesional de la informaci\'on, 27(3), 511-520. doi:10.3145/epi.2018.may.05
10.3145/epi.2018.may.05
null
cs.DL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper presents and describes the methodological opportunities offered by bibliometric data to produce indicators of scientific mobility. Large bibliographic datasets of disambiguated authors and their affiliations allow for the possibility of tracking the affiliation changes of scientists. Using the Web of Scien...
[ { "created": "Wed, 20 Jun 2018 16:13:37 GMT", "version": "v1" } ]
2018-06-21
[ [ "Robinson-Garcia", "Nicolas", "" ], [ "Sugimoto", "Cassidy R.", "" ], [ "Murray", "Dakota", "" ], [ "Yegros-Yegros", "Alfredo", "" ], [ "Larivière", "Vincent", "" ], [ "Costas", "Rodrigo", "" ] ]
This paper presents and describes the methodological opportunities offered by bibliometric data to produce indicators of scientific mobility. Large bibliographic datasets of disambiguated authors and their affiliations allow for the possibility of tracking the affiliation changes of scientists. Using the Web of Science...
2010.01160
Aditi Chaudhary
Aditi Chaudhary, Antonios Anastasopoulos, Adithya Pratapa, David R. Mortensen, Zaid Sheikh, Yulia Tsvetkov, Graham Neubig
Automatic Extraction of Rules Governing Morphological Agreement
Accepted at EMNLP 2020
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Creating a descriptive grammar of a language is an indispensable step for language documentation and preservation. However, at the same time it is a tedious, time-consuming task. In this paper, we take steps towards automating this process by devising an automated framework for extracting a first-pass grammatical spe...
[ { "created": "Fri, 2 Oct 2020 18:31:45 GMT", "version": "v1" }, { "created": "Tue, 6 Oct 2020 03:30:27 GMT", "version": "v2" } ]
2020-10-07
[ [ "Chaudhary", "Aditi", "" ], [ "Anastasopoulos", "Antonios", "" ], [ "Pratapa", "Adithya", "" ], [ "Mortensen", "David R.", "" ], [ "Sheikh", "Zaid", "" ], [ "Tsvetkov", "Yulia", "" ], [ "Neubig", "Graham", ...
Creating a descriptive grammar of a language is an indispensable step for language documentation and preservation. However, at the same time it is a tedious, time-consuming task. In this paper, we take steps towards automating this process by devising an automated framework for extracting a first-pass grammatical speci...
2305.15725
Fangwei Zhu
Fangwei Zhu, Jifan Yu, Hailong Jin, Juanzi Li, Lei Hou, Zhifang Sui
Learn to Not Link: Exploring NIL Prediction in Entity Linking
ACL Findings 2023
null
null
null
cs.CL
http://creativecommons.org/licenses/by-sa/4.0/
Entity linking models have achieved significant success via utilizing pretrained language models to capture semantic features. However, the NIL prediction problem, which aims to identify mentions without a corresponding entity in the knowledge base, has received insufficient attention. We categorize mentions linking ...
[ { "created": "Thu, 25 May 2023 05:12:33 GMT", "version": "v1" } ]
2023-05-26
[ [ "Zhu", "Fangwei", "" ], [ "Yu", "Jifan", "" ], [ "Jin", "Hailong", "" ], [ "Li", "Juanzi", "" ], [ "Hou", "Lei", "" ], [ "Sui", "Zhifang", "" ] ]
Entity linking models have achieved significant success via utilizing pretrained language models to capture semantic features. However, the NIL prediction problem, which aims to identify mentions without a corresponding entity in the knowledge base, has received insufficient attention. We categorize mentions linking to...
1506.06006
Srinivas S S Kruthiventi
Srinivas S. S. Kruthiventi and R. Venkatesh Babu
Crowd Flow Segmentation in Compressed Domain using CRF
In IEEE International Conference on Image Processing (ICIP), 2015
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Crowd flow segmentation is an important step in many video surveillance tasks. In this work, we propose an algorithm for segmenting flows in H.264 compressed videos in a completely unsupervised manner. Our algorithm works on motion vectors which can be obtained by partially decoding the compressed video without extra...
[ { "created": "Fri, 19 Jun 2015 14:01:24 GMT", "version": "v1" } ]
2015-06-22
[ [ "Kruthiventi", "Srinivas S. S.", "" ], [ "Babu", "R. Venkatesh", "" ] ]
Crowd flow segmentation is an important step in many video surveillance tasks. In this work, we propose an algorithm for segmenting flows in H.264 compressed videos in a completely unsupervised manner. Our algorithm works on motion vectors which can be obtained by partially decoding the compressed video without extract...
1305.3671
Marcus Hutter
Marcus Hutter
Sparse Adaptive Dirichlet-Multinomial-like Processes
32 LaTeX pages, 5 figures
null
null
null
cs.IT math.IT math.ST stat.TH
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Online estimation and modelling of i.i.d. data for short sequences over large or complex "alphabets" is a ubiquitous (sub)problem in machine learning, information theory, data compression, statistical language processing, and document analysis. The Dirichlet-Multinomial distribution (also called Polya urn scheme) and...
[ { "created": "Thu, 16 May 2013 02:35:42 GMT", "version": "v1" } ]
2013-05-17
[ [ "Hutter", "Marcus", "" ] ]
Online estimation and modelling of i.i.d. data for short sequences over large or complex "alphabets" is a ubiquitous (sub)problem in machine learning, information theory, data compression, statistical language processing, and document analysis. The Dirichlet-Multinomial distribution (also called Polya urn scheme) and e...
2407.06823
Luca Lanzend\"orfer
Giulia Arg\"uello, Luca A. Lanzend\"orfer, Roger Wattenhofer
Cue Point Estimation using Object Detection
null
null
null
null
cs.AI
http://creativecommons.org/licenses/by/4.0/
Cue points indicate possible temporal boundaries in a transition between two pieces of music in DJ mixing and constitute a crucial element in autonomous DJ systems as well as for live mixing. In this work, we present a novel method for automatic cue point estimation, interpreted as a computer vision object detection ...
[ { "created": "Tue, 9 Jul 2024 12:56:30 GMT", "version": "v1" } ]
2024-07-10
[ [ "Argüello", "Giulia", "" ], [ "Lanzendörfer", "Luca A.", "" ], [ "Wattenhofer", "Roger", "" ] ]
Cue points indicate possible temporal boundaries in a transition between two pieces of music in DJ mixing and constitute a crucial element in autonomous DJ systems as well as for live mixing. In this work, we present a novel method for automatic cue point estimation, interpreted as a computer vision object detection ta...
1302.4970
Paul J. Krause
Paul J. Krause, John Fox, Philip Judson
Is There a Role for Qualitative Risk Assessment?
Appears in Proceedings of the Eleventh Conference on Uncertainty in Artificial Intelligence (UAI1995)
null
null
UAI-P-1995-PG-386-393
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Classically, risk is characterized by a point value probability indicating the likelihood of occurrence of an adverse effect. However, there are domains where the attainability of objective numerical risk characterizations is increasingly being questioned. This paper reviews the arguments in favour of extending class...
[ { "created": "Wed, 20 Feb 2013 15:22:31 GMT", "version": "v1" } ]
2013-02-21
[ [ "Krause", "Paul J.", "" ], [ "Fox", "John", "" ], [ "Judson", "Philip", "" ] ]
Classically, risk is characterized by a point value probability indicating the likelihood of occurrence of an adverse effect. However, there are domains where the attainability of objective numerical risk characterizations is increasingly being questioned. This paper reviews the arguments in favour of extending classic...
2304.05512
Taner Arsan
Taner Arsan, Sehnaz Sismanoglu Simsek, Onder Pekcan
Mathematical and Linguistic Characterization of Orhan Pamuk's Nobel Works
null
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
In this study, Nobel Laureate Orhan Pamuk's works are chosen as examples of Turkish literature. By counting the number of letters and words in his texts, we find it possible to study his works statistically. It has been known that there is a geometrical order in text structures. Here the method based on the basic ass...
[ { "created": "Tue, 11 Apr 2023 21:37:50 GMT", "version": "v1" } ]
2023-04-13
[ [ "Arsan", "Taner", "" ], [ "Simsek", "Sehnaz Sismanoglu", "" ], [ "Pekcan", "Onder", "" ] ]
In this study, Nobel Laureate Orhan Pamuk's works are chosen as examples of Turkish literature. By counting the number of letters and words in his texts, we find it possible to study his works statistically. It has been known that there is a geometrical order in text structures. Here the method based on the basic assum...
2102.08098
Chen Zhu
Chen Zhu, Renkun Ni, Zheng Xu, Kezhi Kong, W. Ronny Huang, Tom Goldstein
GradInit: Learning to Initialize Neural Networks for Stable and Efficient Training
NeurIPS 2021, fixing typos
null
null
null
cs.LG cs.CL cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Innovations in neural architectures have fostered significant breakthroughs in language modeling and computer vision. Unfortunately, novel architectures often result in challenging hyper-parameter choices and training instability if the network parameters are not properly initialized. A number of architecture-specifi...
[ { "created": "Tue, 16 Feb 2021 11:45:35 GMT", "version": "v1" }, { "created": "Wed, 27 Oct 2021 05:52:41 GMT", "version": "v2" }, { "created": "Wed, 24 Nov 2021 09:13:08 GMT", "version": "v3" } ]
2021-11-25
[ [ "Zhu", "Chen", "" ], [ "Ni", "Renkun", "" ], [ "Xu", "Zheng", "" ], [ "Kong", "Kezhi", "" ], [ "Huang", "W. Ronny", "" ], [ "Goldstein", "Tom", "" ] ]
Innovations in neural architectures have fostered significant breakthroughs in language modeling and computer vision. Unfortunately, novel architectures often result in challenging hyper-parameter choices and training instability if the network parameters are not properly initialized. A number of architecture-specific ...
1708.02096
Raghavendra Selvan
Raghavendra Selvan, Jens Petersen, Jesper H. Pedersen, Marleen de Bruijne
Extraction of Airways with Probabilistic State-space Models and Bayesian Smoothing
10 pages. Pre-print of the paper accepted at Workshop on Graphs in Biomedical Image Analysis. MICCAI 2017. Quebec City
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Segmenting tree structures is common in several image processing applications. In medical image analysis, reliable segmentations of airways, vessels, neurons and other tree structures can enable important clinical applications. We present a framework for tracking tree structures comprising of elongated branches using...
[ { "created": "Mon, 7 Aug 2017 12:43:26 GMT", "version": "v1" } ]
2017-08-08
[ [ "Selvan", "Raghavendra", "" ], [ "Petersen", "Jens", "" ], [ "Pedersen", "Jesper H.", "" ], [ "de Bruijne", "Marleen", "" ] ]
Segmenting tree structures is common in several image processing applications. In medical image analysis, reliable segmentations of airways, vessels, neurons and other tree structures can enable important clinical applications. We present a framework for tracking tree structures comprising of elongated branches using p...
1410.5105
Chaitanya Swamy
Guru Guruganesh, Laura Sanita, and Chaitanya Swamy
Improved Region-Growing and Combinatorial Algorithms for $k$-Route Cut Problems
null
null
null
null
cs.DS cs.DM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We study the {\em $k$-route} generalizations of various cut problems, the most general of which is \emph{$k$-route multicut} ($k$-MC) problem, wherein we have $r$ source-sink pairs and the goal is to delete a minimum-cost set of edges to reduce the edge-connectivity of every source-sink pair to below $k$. The $k$-rou...
[ { "created": "Sun, 19 Oct 2014 19:23:24 GMT", "version": "v1" } ]
2014-10-21
[ [ "Guruganesh", "Guru", "" ], [ "Sanita", "Laura", "" ], [ "Swamy", "Chaitanya", "" ] ]
We study the {\em $k$-route} generalizations of various cut problems, the most general of which is \emph{$k$-route multicut} ($k$-MC) problem, wherein we have $r$ source-sink pairs and the goal is to delete a minimum-cost set of edges to reduce the edge-connectivity of every source-sink pair to below $k$. The $k$-route...
2306.08620
John Thickstun
John Thickstun, David Hall, Chris Donahue, Percy Liang
Anticipatory Music Transformer
TMLR accepted version
null
null
null
cs.SD cs.LG eess.AS stat.ML
http://creativecommons.org/licenses/by/4.0/
We introduce anticipation: a method for constructing a controllable generative model of a temporal point process (the event process) conditioned asynchronously on realizations of a second, correlated process (the control process). We achieve this by interleaving sequences of events and controls, such that controls ap...
[ { "created": "Wed, 14 Jun 2023 16:27:53 GMT", "version": "v1" }, { "created": "Thu, 25 Jul 2024 18:35:33 GMT", "version": "v2" } ]
2024-07-29
[ [ "Thickstun", "John", "" ], [ "Hall", "David", "" ], [ "Donahue", "Chris", "" ], [ "Liang", "Percy", "" ] ]
We introduce anticipation: a method for constructing a controllable generative model of a temporal point process (the event process) conditioned asynchronously on realizations of a second, correlated process (the control process). We achieve this by interleaving sequences of events and controls, such that controls appe...
2010.16073
Zeeshan Ahmad
Zeeshan Ahmad and Naimul khan
CNN based Multistage Gated Average Fusion (MGAF) for Human Action Recognition Using Depth and Inertial Sensors
arXiv admin note: text overlap with arXiv:1910.11482
null
null
null
cs.CV cs.LG cs.MM eess.IV
http://creativecommons.org/licenses/by/4.0/
Convolutional Neural Network (CNN) provides leverage to extract and fuse features from all layers of its architecture. However, extracting and fusing intermediate features from different layers of CNN structure is still uninvestigated for Human Action Recognition (HAR) using depth and inertial sensors. To get maximum...
[ { "created": "Thu, 29 Oct 2020 11:49:13 GMT", "version": "v1" } ]
2020-11-02
[ [ "Ahmad", "Zeeshan", "" ], [ "khan", "Naimul", "" ] ]
Convolutional Neural Network (CNN) provides leverage to extract and fuse features from all layers of its architecture. However, extracting and fusing intermediate features from different layers of CNN structure is still uninvestigated for Human Action Recognition (HAR) using depth and inertial sensors. To get maximum b...
2311.03774
Cheng Cheng
Cheng Cheng, Lin Song, Ruoyi Xue, Hang Wang, Hongbin Sun, Yixiao Ge, Ying Shan
Meta-Adapter: An Online Few-shot Learner for Vision-Language Model
Accepted by NeurIPS 2023
null
null
null
cs.CV
http://creativecommons.org/publicdomain/zero/1.0/
The contrastive vision-language pre-training, known as CLIP, demonstrates remarkable potential in perceiving open-world visual concepts, enabling effective zero-shot image recognition. Nevertheless, few-shot learning methods based on CLIP typically require offline fine-tuning of the parameters on few-shot samples, re...
[ { "created": "Tue, 7 Nov 2023 07:27:16 GMT", "version": "v1" }, { "created": "Thu, 11 Jan 2024 06:03:56 GMT", "version": "v2" } ]
2024-01-12
[ [ "Cheng", "Cheng", "" ], [ "Song", "Lin", "" ], [ "Xue", "Ruoyi", "" ], [ "Wang", "Hang", "" ], [ "Sun", "Hongbin", "" ], [ "Ge", "Yixiao", "" ], [ "Shan", "Ying", "" ] ]
The contrastive vision-language pre-training, known as CLIP, demonstrates remarkable potential in perceiving open-world visual concepts, enabling effective zero-shot image recognition. Nevertheless, few-shot learning methods based on CLIP typically require offline fine-tuning of the parameters on few-shot samples, resu...
1912.05362
Sylvain Cherrier
Hantanirina Felixie, Jean Razafindramintsa, Sylvain Cherrier (LIGM), Thomas Mahatody, Laurent George (LIGM), Victor Manantsoa
Jason-RS, a Collaboration between Agents and an IoT Platform
null
International Workshop on Networking for Smart Living, Dec 2019, Paris, France
null
null
cs.MA cs.CY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this article we start from the observation that REST services are the most used as tools of interoperability and orchestration in the Internet of Things (IoT). But REST does not make it possible to inject artificial intelligence into connected objects, ie it cannot allow autonomy and decision-making by the objects...
[ { "created": "Wed, 11 Dec 2019 14:43:22 GMT", "version": "v1" } ]
2019-12-12
[ [ "Felixie", "Hantanirina", "", "LIGM" ], [ "Razafindramintsa", "Jean", "", "LIGM" ], [ "Cherrier", "Sylvain", "", "LIGM" ], [ "Mahatody", "Thomas", "", "LIGM" ], [ "George", "Laurent", "", "LIGM" ], [ "Manantsoa...
In this article we start from the observation that REST services are the most used as tools of interoperability and orchestration in the Internet of Things (IoT). But REST does not make it possible to inject artificial intelligence into connected objects, ie it cannot allow autonomy and decision-making by the objects t...
2209.03910
Prajwal Chidananda
Prajwal Chidananda, Saurabh Nair, Douglas Lee, Adrian Kaehler
PixTrack: Precise 6DoF Object Pose Tracking using NeRF Templates and Feature-metric Alignment
null
null
null
null
cs.CV cs.AI cs.LG cs.RO
http://creativecommons.org/licenses/by-nc-sa/4.0/
We present PixTrack, a vision based object pose tracking framework using novel view synthesis and deep feature-metric alignment. We follow an SfM-based relocalization paradigm where we use a Neural Radiance Field to canonically represent the tracked object. Our evaluations demonstrate that our method produces highly ...
[ { "created": "Thu, 8 Sep 2022 16:36:24 GMT", "version": "v1" }, { "created": "Wed, 14 Feb 2024 09:43:01 GMT", "version": "v2" } ]
2024-02-16
[ [ "Chidananda", "Prajwal", "" ], [ "Nair", "Saurabh", "" ], [ "Lee", "Douglas", "" ], [ "Kaehler", "Adrian", "" ] ]
We present PixTrack, a vision based object pose tracking framework using novel view synthesis and deep feature-metric alignment. We follow an SfM-based relocalization paradigm where we use a Neural Radiance Field to canonically represent the tracked object. Our evaluations demonstrate that our method produces highly ac...
2212.03795
Idit Diamant
Idit Diamant, Roy H. Jennings, Oranit Dror, Hai Victor Habi, Arnon Netzer
Reconciling a Centroid-Hypothesis Conflict in Source-Free Domain Adaptation
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Source-free domain adaptation (SFDA) aims to transfer knowledge learned from a source domain to an unlabeled target domain, where the source data is unavailable during adaptation. Existing approaches for SFDA focus on self-training usually including well-established entropy minimization techniques. One of the main ch...
[ { "created": "Wed, 7 Dec 2022 17:23:49 GMT", "version": "v1" } ]
2022-12-08
[ [ "Diamant", "Idit", "" ], [ "Jennings", "Roy H.", "" ], [ "Dror", "Oranit", "" ], [ "Habi", "Hai Victor", "" ], [ "Netzer", "Arnon", "" ] ]
Source-free domain adaptation (SFDA) aims to transfer knowledge learned from a source domain to an unlabeled target domain, where the source data is unavailable during adaptation. Existing approaches for SFDA focus on self-training usually including well-established entropy minimization techniques. One of the main chal...
1303.3636
Rodrigo de Lamare
Lei Wang and Rodrigo C. de Lamare
Low-Complexity Adaptive Set-Membership Reduced-rank LCMV Beamforming
2 figures, 5 pages
ISWCS 2010
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper proposes a new adaptive algorithm for the implementation of the linearly constrained minimum variance (LCMV) beamformer. The proposed algorithm utilizes the set-membership filtering (SMF) framework and the reduced-rank joint iterative optimization (JIO) scheme. We develop a stochastic gradient (SG) based a...
[ { "created": "Thu, 14 Mar 2013 22:56:15 GMT", "version": "v1" } ]
2013-03-18
[ [ "Wang", "Lei", "" ], [ "de Lamare", "Rodrigo C.", "" ] ]
This paper proposes a new adaptive algorithm for the implementation of the linearly constrained minimum variance (LCMV) beamformer. The proposed algorithm utilizes the set-membership filtering (SMF) framework and the reduced-rank joint iterative optimization (JIO) scheme. We develop a stochastic gradient (SG) based alg...
0901.2804
Li Chia Choo
Li-Chia Choo and Kai-Kit Wong
The Secrecy Capacity for a 3-Receiver Broadcast Channel with Degraded Message Sets
This paper has been withdrawn by the author
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper has been withdrawn by the author due to some errors.
[ { "created": "Mon, 19 Jan 2009 10:36:33 GMT", "version": "v1" }, { "created": "Thu, 5 Feb 2009 16:04:22 GMT", "version": "v2" }, { "created": "Tue, 3 Mar 2009 15:08:26 GMT", "version": "v3" }, { "created": "Thu, 11 Jun 2009 09:53:16 GMT", "version": "v4" } ]
2009-06-11
[ [ "Choo", "Li-Chia", "" ], [ "Wong", "Kai-Kit", "" ] ]
This paper has been withdrawn by the author due to some errors.
2408.00882
Emily Wenger
Emily Wenger, Eshika Saxena, Mohamed Malhou, Ellie Thieu, Kristin Lauter
Benchmarking Attacks on Learning with Errors
null
null
null
null
cs.CR
http://creativecommons.org/licenses/by/4.0/
Lattice cryptography schemes based on the learning with errors (LWE) hardness assumption have been standardized by NIST for use as post-quantum cryptosystems, and by HomomorphicEncryption.org for encrypted compute on sensitive data. Thus, understanding their concrete security is critical. Most work on LWE security fo...
[ { "created": "Thu, 1 Aug 2024 19:21:20 GMT", "version": "v1" } ]
2024-08-05
[ [ "Wenger", "Emily", "" ], [ "Saxena", "Eshika", "" ], [ "Malhou", "Mohamed", "" ], [ "Thieu", "Ellie", "" ], [ "Lauter", "Kristin", "" ] ]
Lattice cryptography schemes based on the learning with errors (LWE) hardness assumption have been standardized by NIST for use as post-quantum cryptosystems, and by HomomorphicEncryption.org for encrypted compute on sensitive data. Thus, understanding their concrete security is critical. Most work on LWE security focu...
2101.06232
Yuzhou Lin
Yuzhou Lin, Xiaolin Chang
Towards interpreting ML-based automated malware detection models: a survey
null
null
null
null
cs.CR cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Malware is being increasingly threatening and malware detectors based on traditional signature-based analysis are no longer suitable for current malware detection. Recently, the models based on machine learning (ML) are developed for predicting unknown malware variants and saving human strength. However, most of the ...
[ { "created": "Fri, 15 Jan 2021 17:34:40 GMT", "version": "v1" } ]
2021-01-18
[ [ "Lin", "Yuzhou", "" ], [ "Chang", "Xiaolin", "" ] ]
Malware is being increasingly threatening and malware detectors based on traditional signature-based analysis are no longer suitable for current malware detection. Recently, the models based on machine learning (ML) are developed for predicting unknown malware variants and saving human strength. However, most of the ex...
2312.09963
Matteo Cardellini
Matteo Cardellini, Enrico Giunchiglia, and Marco Maratea
Symbolic Numeric Planning with Patterns
Accepted at AAAI24
null
10.1609/aaai.v38i18.29985
null
cs.AI
http://creativecommons.org/licenses/by/4.0/
In this paper, we propose a novel approach for solving linear numeric planning problems, called Symbolic Pattern Planning. Given a planning problem $\Pi$, a bound $n$ and a pattern -- defined as an arbitrary sequence of actions -- we encode the problem of finding a plan for $\Pi$ with bound $n$ as a formula with fewe...
[ { "created": "Fri, 15 Dec 2023 17:20:25 GMT", "version": "v1" }, { "created": "Sun, 7 Jan 2024 14:44:18 GMT", "version": "v2" }, { "created": "Mon, 12 Feb 2024 09:52:37 GMT", "version": "v3" } ]
2024-03-28
[ [ "Cardellini", "Matteo", "" ], [ "Giunchiglia", "Enrico", "" ], [ "Maratea", "Marco", "" ] ]
In this paper, we propose a novel approach for solving linear numeric planning problems, called Symbolic Pattern Planning. Given a planning problem $\Pi$, a bound $n$ and a pattern -- defined as an arbitrary sequence of actions -- we encode the problem of finding a plan for $\Pi$ with bound $n$ as a formula with fewer ...
1901.08728
Rishabh Agarwal
Rishabh Agarwal
Evaluation Function Approximation for Scrabble
null
null
null
null
cs.AI
http://creativecommons.org/licenses/by/4.0/
The current state-of-the-art Scrabble agents are not learning-based but depend on truncated Monte Carlo simulations and the quality of such agents is contingent upon the time available for running the simulations. This thesis takes steps towards building a learning-based Scrabble agent using self-play. Specifically, ...
[ { "created": "Fri, 25 Jan 2019 04:05:52 GMT", "version": "v1" } ]
2019-01-28
[ [ "Agarwal", "Rishabh", "" ] ]
The current state-of-the-art Scrabble agents are not learning-based but depend on truncated Monte Carlo simulations and the quality of such agents is contingent upon the time available for running the simulations. This thesis takes steps towards building a learning-based Scrabble agent using self-play. Specifically, we...
1911.10150
Alex Lang
Sourabh Vora, Alex H. Lang, Bassam Helou, and Oscar Beijbom
PointPainting: Sequential Fusion for 3D Object Detection
11 pages, 6 figures, 8 tables. v1 is initial submission to CVPR 2020. v2 is final version accepted for publication at CVPR 2020
null
null
null
cs.CV cs.LG eess.IV stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Camera and lidar are important sensor modalities for robotics in general and self-driving cars in particular. The sensors provide complementary information offering an opportunity for tight sensor-fusion. Surprisingly, lidar-only methods outperform fusion methods on the main benchmark datasets, suggesting a gap in th...
[ { "created": "Fri, 22 Nov 2019 17:19:50 GMT", "version": "v1" }, { "created": "Wed, 6 May 2020 17:17:18 GMT", "version": "v2" } ]
2020-05-07
[ [ "Vora", "Sourabh", "" ], [ "Lang", "Alex H.", "" ], [ "Helou", "Bassam", "" ], [ "Beijbom", "Oscar", "" ] ]
Camera and lidar are important sensor modalities for robotics in general and self-driving cars in particular. The sensors provide complementary information offering an opportunity for tight sensor-fusion. Surprisingly, lidar-only methods outperform fusion methods on the main benchmark datasets, suggesting a gap in the ...
2402.00591
Nicolas Lazzari
Nicolas Lazzari, Stefano De Giorgis, Aldo Gangemi, Valentina Presutti
Sandra -- A Neuro-Symbolic Reasoner Based On Descriptions And Situations
null
null
null
null
cs.AI
http://creativecommons.org/licenses/by/4.0/
This paper presents sandra, a neuro-symbolic reasoner combining vectorial representations with deductive reasoning. Sandra builds a vector space constrained by an ontology and performs reasoning over it. The geometric nature of the reasoner allows its combination with neural networks, bridging the gap with symbolic k...
[ { "created": "Thu, 1 Feb 2024 13:37:53 GMT", "version": "v1" }, { "created": "Fri, 2 Feb 2024 08:58:41 GMT", "version": "v2" }, { "created": "Mon, 25 Mar 2024 10:52:20 GMT", "version": "v3" } ]
2024-03-26
[ [ "Lazzari", "Nicolas", "" ], [ "De Giorgis", "Stefano", "" ], [ "Gangemi", "Aldo", "" ], [ "Presutti", "Valentina", "" ] ]
This paper presents sandra, a neuro-symbolic reasoner combining vectorial representations with deductive reasoning. Sandra builds a vector space constrained by an ontology and performs reasoning over it. The geometric nature of the reasoner allows its combination with neural networks, bridging the gap with symbolic kno...
2209.09635
Yuxuan Du
Ruohua Zhou, Yuxuan Du, Chenlei Hu
The BUCEA Speaker Diarization System for the VoxCeleb Speaker Recognition Challenge 2022
null
null
null
null
cs.SD eess.AS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper describes the BUCEA speaker diarization system for the 2022 VoxCeleb Speaker Recognition Challenge. Voxsrc-22 provides the development set and test set of VoxConverse, and we mainly use the test set of VoxConverse for parameter adjustment. Our system consists of several modules, including speech activity d...
[ { "created": "Tue, 20 Sep 2022 11:33:58 GMT", "version": "v1" } ]
2022-09-21
[ [ "Zhou", "Ruohua", "" ], [ "Du", "Yuxuan", "" ], [ "Hu", "Chenlei", "" ] ]
This paper describes the BUCEA speaker diarization system for the 2022 VoxCeleb Speaker Recognition Challenge. Voxsrc-22 provides the development set and test set of VoxConverse, and we mainly use the test set of VoxConverse for parameter adjustment. Our system consists of several modules, including speech activity det...
1210.6636
Jan Bergstra
Jan A. Bergstra
Informaticology: combining Computer Science, Data Science, and Fiction Science
null
null
null
null
cs.SE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Motivated by an intention to remedy current complications with Dutch terminology concerning informatics, the term informaticology is positioned to denote an academic counterpart of informatics where informatics is conceived of as a container for a coherent family of practical disciplines ranging from computer enginee...
[ { "created": "Wed, 24 Oct 2012 19:24:59 GMT", "version": "v1" } ]
2012-10-25
[ [ "Bergstra", "Jan A.", "" ] ]
Motivated by an intention to remedy current complications with Dutch terminology concerning informatics, the term informaticology is positioned to denote an academic counterpart of informatics where informatics is conceived of as a container for a coherent family of practical disciplines ranging from computer engineeri...
2305.11487
Guangyan Chen
Guangyan Chen, Meiling Wang, Yi Yang, Kai Yu, Li Yuan, Yufeng Yue
PointGPT: Auto-regressively Generative Pre-training from Point Clouds
9 pages, 2 figures
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Large language models (LLMs) based on the generative pre-training transformer (GPT) have demonstrated remarkable effectiveness across a diverse range of downstream tasks. Inspired by the advancements of the GPT, we present PointGPT, a novel approach that extends the concept of GPT to point clouds, addressing the chal...
[ { "created": "Fri, 19 May 2023 07:39:04 GMT", "version": "v1" }, { "created": "Tue, 23 May 2023 02:38:26 GMT", "version": "v2" } ]
2023-05-24
[ [ "Chen", "Guangyan", "" ], [ "Wang", "Meiling", "" ], [ "Yang", "Yi", "" ], [ "Yu", "Kai", "" ], [ "Yuan", "Li", "" ], [ "Yue", "Yufeng", "" ] ]
Large language models (LLMs) based on the generative pre-training transformer (GPT) have demonstrated remarkable effectiveness across a diverse range of downstream tasks. Inspired by the advancements of the GPT, we present PointGPT, a novel approach that extends the concept of GPT to point clouds, addressing the challe...
2109.09105
Ayush Kumar
Ayush Kumar, Mukuntha Narayanan Sundararaman, Jithendra Vepa
What BERT Based Language Models Learn in Spoken Transcripts: An Empirical Study
BlackboxNLP @ EMNLP 2021 (15 pages, includes Appendix)
null
null
null
cs.CL cs.AI cs.LG eess.AS
http://creativecommons.org/licenses/by/4.0/
Language Models (LMs) have been ubiquitously leveraged in various tasks including spoken language understanding (SLU). Spoken language requires careful understanding of speaker interactions, dialog states and speech induced multimodal behaviors to generate a meaningful representation of the conversation. In this work...
[ { "created": "Sun, 19 Sep 2021 11:23:50 GMT", "version": "v1" }, { "created": "Tue, 21 Sep 2021 05:24:51 GMT", "version": "v2" } ]
2021-09-22
[ [ "Kumar", "Ayush", "" ], [ "Sundararaman", "Mukuntha Narayanan", "" ], [ "Vepa", "Jithendra", "" ] ]
Language Models (LMs) have been ubiquitously leveraged in various tasks including spoken language understanding (SLU). Spoken language requires careful understanding of speaker interactions, dialog states and speech induced multimodal behaviors to generate a meaningful representation of the conversation. In this work, ...
1603.06665
Richard Kiehl
Richard A. Kiehl
Information Processing by Nonlinear Phase Dynamics in Locally Connected Arrays
null
null
null
null
cs.NE cs.ET
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Research toward powerful information processing systems that circumvent the interconnect bottleneck by exploiting the nonlinear evolution of multiple phase dynamics in locally connected arrays is discussed. We focus on a scheme in which logic states are defined by the electrical phase of a dynamic process and informa...
[ { "created": "Tue, 22 Mar 2016 03:14:00 GMT", "version": "v1" } ]
2016-03-23
[ [ "Kiehl", "Richard A.", "" ] ]
Research toward powerful information processing systems that circumvent the interconnect bottleneck by exploiting the nonlinear evolution of multiple phase dynamics in locally connected arrays is discussed. We focus on a scheme in which logic states are defined by the electrical phase of a dynamic process and informati...
2401.02152
Yo Kobayashi Dr.
Yo Kobayashi, Yoshihiro Katagi
Estimating continuous data of wrist joint angles using ultrasound images
null
null
null
null
cs.HC cs.RO eess.SP
http://creativecommons.org/licenses/by/4.0/
Ultrasound imaging has recently been introduced as a sensing interface for joint motion estimation. The use of ultrasound images as an estimation method is expected to improve the control performance of assistive devices and human--machine interfaces. This study aimed to estimate continuous wrist joint angles using u...
[ { "created": "Thu, 4 Jan 2024 09:04:16 GMT", "version": "v1" } ]
2024-01-05
[ [ "Kobayashi", "Yo", "" ], [ "Katagi", "Yoshihiro", "" ] ]
Ultrasound imaging has recently been introduced as a sensing interface for joint motion estimation. The use of ultrasound images as an estimation method is expected to improve the control performance of assistive devices and human--machine interfaces. This study aimed to estimate continuous wrist joint angles using ult...
2306.10042
Fan Yang
Fan Yang, Mian Zhang, Gongzhen Hu and Xiabing Zhou
A Pairing Enhancement Approach for Aspect Sentiment Triplet Extraction
12 pages, 4 figures
null
null
null
cs.IR cs.AI cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Aspect Sentiment Triplet Extraction (ASTE) aims to extract the triplet of an aspect term, an opinion term, and their corresponding sentiment polarity from the review texts. Due to the complexity of language and the existence of multiple aspect terms and opinion terms in a single sentence, current models often confuse...
[ { "created": "Sun, 11 Jun 2023 07:32:10 GMT", "version": "v1" } ]
2023-06-21
[ [ "Yang", "Fan", "" ], [ "Zhang", "Mian", "" ], [ "Hu", "Gongzhen", "" ], [ "Zhou", "Xiabing", "" ] ]
Aspect Sentiment Triplet Extraction (ASTE) aims to extract the triplet of an aspect term, an opinion term, and their corresponding sentiment polarity from the review texts. Due to the complexity of language and the existence of multiple aspect terms and opinion terms in a single sentence, current models often confuse t...
2106.00906
Daniel McKenzie
Daniel McKenzie, Howard Heaton, Qiuwei Li, Samy Wu Fung, Stanley Osher, Wotao Yin
Operator Splitting for Learning to Predict Equilibria in Convex Games
To appear in SIMODS
null
null
null
cs.LG cs.GT math.OC
http://creativecommons.org/licenses/by/4.0/
Systems of competing agents can often be modeled as games. Assuming rationality, the most likely outcomes are given by an equilibrium (e.g. a Nash equilibrium). In many practical settings, games are influenced by context, i.e. additional data beyond the control of any agent (e.g. weather for traffic and fiscal policy...
[ { "created": "Wed, 2 Jun 2021 02:55:46 GMT", "version": "v1" }, { "created": "Thu, 3 Feb 2022 20:40:23 GMT", "version": "v2" }, { "created": "Wed, 8 Nov 2023 22:00:48 GMT", "version": "v3" }, { "created": "Tue, 11 Jun 2024 23:32:53 GMT", "version": "v4" } ]
2024-06-13
[ [ "McKenzie", "Daniel", "" ], [ "Heaton", "Howard", "" ], [ "Li", "Qiuwei", "" ], [ "Fung", "Samy Wu", "" ], [ "Osher", "Stanley", "" ], [ "Yin", "Wotao", "" ] ]
Systems of competing agents can often be modeled as games. Assuming rationality, the most likely outcomes are given by an equilibrium (e.g. a Nash equilibrium). In many practical settings, games are influenced by context, i.e. additional data beyond the control of any agent (e.g. weather for traffic and fiscal policy f...
2001.02981
Laura Titolo
Laura Titolo, Mariano Moscato, Cesar A. Mu\~noz
Automatic generation and verification of test-stable floating-point code
32 pages. arXiv admin note: text overlap with arXiv:1808.04289
null
null
null
cs.PL cs.NA math.NA
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Test instability in a floating-point program occurs when the control flow of the program diverges from its ideal execution assuming real arithmetic. This phenomenon is caused by the presence of round-off errors that affect the evaluation of arithmetic expressions occurring in conditional statements. Unstable tests ma...
[ { "created": "Tue, 7 Jan 2020 19:46:42 GMT", "version": "v1" } ]
2020-01-10
[ [ "Titolo", "Laura", "" ], [ "Moscato", "Mariano", "" ], [ "Muñoz", "Cesar A.", "" ] ]
Test instability in a floating-point program occurs when the control flow of the program diverges from its ideal execution assuming real arithmetic. This phenomenon is caused by the presence of round-off errors that affect the evaluation of arithmetic expressions occurring in conditional statements. Unstable tests may ...
2212.10460
Hao Wang
Hao Wang
PoissonMat: Remodeling Matrix Factorization using Poisson Distribution and Solving the Cold Start Problem without Input Data
null
null
10.1109/MLISE57402.2022.00055
null
cs.IR cs.AI cs.LG
http://creativecommons.org/licenses/by/4.0/
Matrix Factorization is one of the most successful recommender system techniques over the past decade. However, the classic probabilistic theory framework for matrix factorization is modeled using normal distributions. To find better probabilistic models, algorithms such as RankMat, ZeroMat and DotMat have been inven...
[ { "created": "Tue, 6 Dec 2022 01:20:26 GMT", "version": "v1" } ]
2022-12-21
[ [ "Wang", "Hao", "" ] ]
Matrix Factorization is one of the most successful recommender system techniques over the past decade. However, the classic probabilistic theory framework for matrix factorization is modeled using normal distributions. To find better probabilistic models, algorithms such as RankMat, ZeroMat and DotMat have been invente...
1506.04356
Milan Rajkovic
Milan Rajkovi\'c and Milo\v{s} Milovanovi\'c
The Artists who Forged Themselves: Detecting Creativity in Art
26 pages, 8 figures
null
null
null
cs.CV q-bio.NC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Creativity and the understanding of cognitive processes involved in the creative process are relevant to all of human activities. Comprehension of creativity in the arts is of special interest due to the involvement of many scientific and non scientific disciplines. Using digital representation of paintings, we show ...
[ { "created": "Sun, 14 Jun 2015 06:44:34 GMT", "version": "v1" } ]
2015-06-16
[ [ "Rajković", "Milan", "" ], [ "Milovanović", "Miloš", "" ] ]
Creativity and the understanding of cognitive processes involved in the creative process are relevant to all of human activities. Comprehension of creativity in the arts is of special interest due to the involvement of many scientific and non scientific disciplines. Using digital representation of paintings, we show th...
1312.7442
Jamil Hamodi Mr.
Jamil Hamodi, Khaled Salah, Ravindra Thool
Evaluating the Performance of IPTV over Fixed WiMAX
9 Pages, 9 Figures. arXiv admin note: substantial text overlap with other internet sources by other authors
International Journal of Computer Applications 84(6):35-43, December 2013. Published by Foundation of Computer Science, New York, USA
10.5120/14582-2812
null
cs.MM cs.NI
http://creativecommons.org/licenses/by/3.0/
IEEE specifies different modulation techniques for WiMAX; namely, BPSK, QPSK, 16 QAM and 64 QAM. This paper studies the performance of Internet Protocol Television (IPTV) over Fixed WiMAX system considering different combinations of digital modulation. The performance is studied taking into account a number of key sy...
[ { "created": "Sat, 28 Dec 2013 15:19:09 GMT", "version": "v1" } ]
2016-01-13
[ [ "Hamodi", "Jamil", "" ], [ "Salah", "Khaled", "" ], [ "Thool", "Ravindra", "" ] ]
IEEE specifies different modulation techniques for WiMAX; namely, BPSK, QPSK, 16 QAM and 64 QAM. This paper studies the performance of Internet Protocol Television (IPTV) over Fixed WiMAX system considering different combinations of digital modulation. The performance is studied taking into account a number of key syst...
2305.04395
Yulin Shao
Runxin Zhang, Yulin Shao, Menghan Li, Lu Lu
Optical Integrated Sensing and Communication
null
null
null
null
cs.IT eess.SP math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper explores a new paradigm of optical integrated sensing and communication (O-ISAC). Our investigation reveals that optical communication and optical sensing are two inherently complementary technologies. On the one hand, optical communication provides the necessary illumination for optical sensing. On the ot...
[ { "created": "Mon, 8 May 2023 00:03:55 GMT", "version": "v1" }, { "created": "Wed, 24 May 2023 00:25:36 GMT", "version": "v2" } ]
2023-05-25
[ [ "Zhang", "Runxin", "" ], [ "Shao", "Yulin", "" ], [ "Li", "Menghan", "" ], [ "Lu", "Lu", "" ] ]
This paper explores a new paradigm of optical integrated sensing and communication (O-ISAC). Our investigation reveals that optical communication and optical sensing are two inherently complementary technologies. On the one hand, optical communication provides the necessary illumination for optical sensing. On the othe...
1803.05181
Rizwan Ahmed Khan
Muhammad Shoaib Jaliawala, Rizwan Ahmed Khan
Can Autism be Catered with Artificial Intelligence-Assisted Intervention Technology? A Literature Review
null
Artificial Intelligence Review 2019
10.1007/s10462-019-09686-8
null
cs.HC cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This article presents an extensive literature review of technology based intervention methodologies for individuals facing Autism Spectrum Disorder (ASD). Reviewed methodologies include: contemporary Computer Aided Systems (CAS), Computer Vision Assisted Technologies (CVAT) and Virtual Reality (VR) or Artificial Inte...
[ { "created": "Wed, 14 Mar 2018 09:56:39 GMT", "version": "v1" }, { "created": "Fri, 16 Mar 2018 04:37:12 GMT", "version": "v2" }, { "created": "Sat, 10 Nov 2018 18:54:34 GMT", "version": "v3" }, { "created": "Fri, 23 Nov 2018 05:15:02 GMT", "version": "v4" }, { "c...
2019-02-21
[ [ "Jaliawala", "Muhammad Shoaib", "" ], [ "Khan", "Rizwan Ahmed", "" ] ]
This article presents an extensive literature review of technology based intervention methodologies for individuals facing Autism Spectrum Disorder (ASD). Reviewed methodologies include: contemporary Computer Aided Systems (CAS), Computer Vision Assisted Technologies (CVAT) and Virtual Reality (VR) or Artificial Intell...
1003.2682
David Spivak
David I. Spivak
Table manipulation in simplicial databases
8 pages.
null
null
null
cs.DB cs.IR
http://creativecommons.org/licenses/by/3.0/
In \cite{Spi}, we developed a category of databases in which the schema of a database is represented as a simplicial set. Each simplex corresponds to a table in the database. There, our main concern was to find a categorical formulation of databases; the simplicial nature of the schemas was to some degree unexpected ...
[ { "created": "Sat, 13 Mar 2010 06:22:07 GMT", "version": "v1" } ]
2010-03-16
[ [ "Spivak", "David I.", "" ] ]
In \cite{Spi}, we developed a category of databases in which the schema of a database is represented as a simplicial set. Each simplex corresponds to a table in the database. There, our main concern was to find a categorical formulation of databases; the simplicial nature of the schemas was to some degree unexpected an...
1410.4672
Biju Issac
B. Issac, R. Chiong, S.M. Jacob
Analysis of Phishing Attacks and Countermeasures
8 pages
Issac, B., Chiong, R. & Jacob, S. M. (2006, June). Analysis of Phishing Attacks and Countermeasures. IBIMA, Bonn, Germany, ISBN 0-9753393-5-4, pp.339-346
null
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
One of the biggest problems with the Internet technology is the unwanted spam emails. The well disguised phishing email comes in as part of the spam and makes its entry into the inbox quite frequently nowadays. While phishing is normally considered a consumer issue, the fraudulent tactics the phishers use are now int...
[ { "created": "Fri, 17 Oct 2014 09:34:50 GMT", "version": "v1" } ]
2014-10-20
[ [ "Issac", "B.", "" ], [ "Chiong", "R.", "" ], [ "Jacob", "S. M.", "" ] ]
One of the biggest problems with the Internet technology is the unwanted spam emails. The well disguised phishing email comes in as part of the spam and makes its entry into the inbox quite frequently nowadays. While phishing is normally considered a consumer issue, the fraudulent tactics the phishers use are now intim...
2405.05109
Weijia Zhang
Weijia Zhang, Vaishali Pal, Jia-Hong Huang, Evangelos Kanoulas, Maarten de Rijke
QFMTS: Generating Query-Focused Summaries over Multi-Table Inputs
16 pages, 3 figures
null
null
null
cs.CL cs.AI
http://creativecommons.org/licenses/by/4.0/
Table summarization is a crucial task aimed at condensing information from tabular data into concise and comprehensible textual summaries. However, existing approaches often fall short of adequately meeting users' information and quality requirements and tend to overlook the complexities of real-world queries. In thi...
[ { "created": "Wed, 8 May 2024 15:05:55 GMT", "version": "v1" } ]
2024-05-09
[ [ "Zhang", "Weijia", "" ], [ "Pal", "Vaishali", "" ], [ "Huang", "Jia-Hong", "" ], [ "Kanoulas", "Evangelos", "" ], [ "de Rijke", "Maarten", "" ] ]
Table summarization is a crucial task aimed at condensing information from tabular data into concise and comprehensible textual summaries. However, existing approaches often fall short of adequately meeting users' information and quality requirements and tend to overlook the complexities of real-world queries. In this ...
2210.17017
Minkyu Jung
Minkyu Jung, Ohhyeok Kwon, Seunghyun Seo, Soonshin Seo
Blank Collapse: Compressing CTC emission for the faster decoding
Accepted in Interspeech 2023
null
null
null
cs.CL cs.SD eess.AS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Connectionist Temporal Classification (CTC) model is a very efficient method for modeling sequences, especially for speech data. In order to use CTC model as an Automatic Speech Recognition (ASR) task, the beam search decoding with an external language model like n-gram LM is necessary to obtain reasonable results. I...
[ { "created": "Mon, 31 Oct 2022 02:12:51 GMT", "version": "v1" }, { "created": "Tue, 27 Jun 2023 00:39:38 GMT", "version": "v2" } ]
2023-06-28
[ [ "Jung", "Minkyu", "" ], [ "Kwon", "Ohhyeok", "" ], [ "Seo", "Seunghyun", "" ], [ "Seo", "Soonshin", "" ] ]
Connectionist Temporal Classification (CTC) model is a very efficient method for modeling sequences, especially for speech data. In order to use CTC model as an Automatic Speech Recognition (ASR) task, the beam search decoding with an external language model like n-gram LM is necessary to obtain reasonable results. In ...
1108.5703
Sivakumar Madesan
Jeevan H E, Prashanth P P, Punith Kumar S N, Vinay Hegde
Web Pages Clustering: A New Approach
Clustering, concept mining, information retrieval, metasearch engine
null
null
null
cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The rapid growth of web has resulted in vast volume of information. Information availability at a rapid speed to the user is vital. English language (or any for that matter) has lot of ambiguity in the usage of words. So there is no guarantee that a keyword based search engine will provide the required results. This ...
[ { "created": "Fri, 26 Aug 2011 07:02:35 GMT", "version": "v1" } ]
2011-08-30
[ [ "E", "Jeevan H", "" ], [ "P", "Prashanth P", "" ], [ "N", "Punith Kumar S", "" ], [ "Hegde", "Vinay", "" ] ]
The rapid growth of web has resulted in vast volume of information. Information availability at a rapid speed to the user is vital. English language (or any for that matter) has lot of ambiguity in the usage of words. So there is no guarantee that a keyword based search engine will provide the required results. This pa...
2107.00934
Jiahui Li
Jiahui Li, Wen Chen, Xiaodi Huang, Zhiqiang Hu, Qi Duan, Hongsheng Li, Dimitris N. Metaxas, Shaoting Zhang
Hybrid Supervision Learning for Pathology Whole Slide Image Classification
Accepted in MICCAI2021
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Weak supervision learning on classification labels has demonstrated high performance in various tasks, while a few pixel-level fine annotations are also affordable. Naturally a question comes to us that whether the combination of pixel-level (e.g., segmentation) and image level (e.g., classification) annotation can i...
[ { "created": "Fri, 2 Jul 2021 09:46:06 GMT", "version": "v1" }, { "created": "Mon, 5 Jul 2021 03:09:33 GMT", "version": "v2" }, { "created": "Mon, 25 Oct 2021 06:45:28 GMT", "version": "v3" } ]
2021-10-26
[ [ "Li", "Jiahui", "" ], [ "Chen", "Wen", "" ], [ "Huang", "Xiaodi", "" ], [ "Hu", "Zhiqiang", "" ], [ "Duan", "Qi", "" ], [ "Li", "Hongsheng", "" ], [ "Metaxas", "Dimitris N.", "" ], [ "Zhang", "S...
Weak supervision learning on classification labels has demonstrated high performance in various tasks, while a few pixel-level fine annotations are also affordable. Naturally a question comes to us that whether the combination of pixel-level (e.g., segmentation) and image level (e.g., classification) annotation can int...
2010.16336
Ari Kobren
Naveen Jafer Nizar, Ari Kobren
Leveraging Extracted Model Adversaries for Improved Black Box Attacks
null
Analyzing and interpreting neural networks for NLP, 2020
null
null
cs.LG cs.AI cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present a method for adversarial input generation against black box models for reading comprehension based question answering. Our approach is composed of two steps. First, we approximate a victim black box model via model extraction (Krishna et al., 2020). Second, we use our own white box method to generate input...
[ { "created": "Fri, 30 Oct 2020 15:53:50 GMT", "version": "v1" }, { "created": "Mon, 2 Nov 2020 16:38:30 GMT", "version": "v2" } ]
2020-11-03
[ [ "Nizar", "Naveen Jafer", "" ], [ "Kobren", "Ari", "" ] ]
We present a method for adversarial input generation against black box models for reading comprehension based question answering. Our approach is composed of two steps. First, we approximate a victim black box model via model extraction (Krishna et al., 2020). Second, we use our own white box method to generate input p...
1909.11015
Shiv Ram Dubey
Shiv Ram Dubey, Soumendu Chakraborty, Swalpa Kumar Roy, Snehasis Mukherjee, Satish Kumar Singh, Bidyut Baran Chaudhuri
diffGrad: An Optimization Method for Convolutional Neural Networks
null
IEEE Transactions on Neural Networks and Learning Systems, 2020
null
null
cs.LG cs.CV cs.NE math.OC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Stochastic Gradient Decent (SGD) is one of the core techniques behind the success of deep neural networks. The gradient provides information on the direction in which a function has the steepest rate of change. The main problem with basic SGD is to change by equal sized steps for all parameters, irrespective of gradi...
[ { "created": "Thu, 12 Sep 2019 06:20:05 GMT", "version": "v1" }, { "created": "Tue, 24 Dec 2019 06:11:50 GMT", "version": "v2" }, { "created": "Fri, 6 Mar 2020 06:51:39 GMT", "version": "v3" }, { "created": "Sat, 27 Nov 2021 01:58:07 GMT", "version": "v4" } ]
2021-11-30
[ [ "Dubey", "Shiv Ram", "" ], [ "Chakraborty", "Soumendu", "" ], [ "Roy", "Swalpa Kumar", "" ], [ "Mukherjee", "Snehasis", "" ], [ "Singh", "Satish Kumar", "" ], [ "Chaudhuri", "Bidyut Baran", "" ] ]
Stochastic Gradient Decent (SGD) is one of the core techniques behind the success of deep neural networks. The gradient provides information on the direction in which a function has the steepest rate of change. The main problem with basic SGD is to change by equal sized steps for all parameters, irrespective of gradien...
1906.09880
Federico Fusco
Shant Boodaghians, Federico Fusco, Stefano Leonardi, Yishay Mansour, Ruta Mehta
Online Revenue Maximization for Server Pricing
null
Auton Agent Multi-Agent Syst 36, 11 (2022)
10.1007/s10458-022-09544-y
null
cs.GT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Efficient and truthful mechanisms to price resources on remote servers/machines has been the subject of much work in recent years due to the importance of the cloud market. This paper considers revenue maximization in the online stochastic setting with non-preemptive jobs and a unit capacity server. One agent/job arr...
[ { "created": "Mon, 24 Jun 2019 12:26:13 GMT", "version": "v1" }, { "created": "Fri, 19 Jul 2019 10:50:31 GMT", "version": "v2" }, { "created": "Tue, 1 Oct 2019 12:32:43 GMT", "version": "v3" } ]
2024-02-20
[ [ "Boodaghians", "Shant", "" ], [ "Fusco", "Federico", "" ], [ "Leonardi", "Stefano", "" ], [ "Mansour", "Yishay", "" ], [ "Mehta", "Ruta", "" ] ]
Efficient and truthful mechanisms to price resources on remote servers/machines has been the subject of much work in recent years due to the importance of the cloud market. This paper considers revenue maximization in the online stochastic setting with non-preemptive jobs and a unit capacity server. One agent/job arriv...
2006.07503
Nicol\`o Campolongo
Nicol\`o Campolongo, Francesco Orabona
Temporal Variability in Implicit Online Learning
18 pages, 12 figures
null
null
null
cs.LG stat.ML
http://creativecommons.org/licenses/by-nc-sa/4.0/
In the setting of online learning, Implicit algorithms turn out to be highly successful from a practical standpoint. However, the tightest regret analyses only show marginal improvements over Online Mirror Descent. In this work, we shed light on this behavior carrying out a careful regret analysis. We prove a novel s...
[ { "created": "Fri, 12 Jun 2020 22:50:34 GMT", "version": "v1" }, { "created": "Fri, 6 Nov 2020 19:59:09 GMT", "version": "v2" } ]
2020-11-10
[ [ "Campolongo", "Nicolò", "" ], [ "Orabona", "Francesco", "" ] ]
In the setting of online learning, Implicit algorithms turn out to be highly successful from a practical standpoint. However, the tightest regret analyses only show marginal improvements over Online Mirror Descent. In this work, we shed light on this behavior carrying out a careful regret analysis. We prove a novel sta...
1408.4143
Mohammed Abdelsamea
Marghny H. Mohamed and Mohammed M. Abdelsamea
Self Organization Map based Texture Feature Extraction for Efficient Medical Image Categorization
In Proceedings of the 4th ACM International Conference on Intelligent Computing and Information Systems, ICICIS 2009, Cairo, Egypt 2009
null
null
null
cs.CV cs.NE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Texture is one of the most important properties of visual surface that helps in discriminating one object from another or an object from background. The self-organizing map (SOM) is an excellent tool in exploratory phase of data mining. It projects its input space on prototypes of a low-dimensional regular grid that ...
[ { "created": "Mon, 14 Jul 2014 13:43:19 GMT", "version": "v1" } ]
2014-08-20
[ [ "Mohamed", "Marghny H.", "" ], [ "Abdelsamea", "Mohammed M.", "" ] ]
Texture is one of the most important properties of visual surface that helps in discriminating one object from another or an object from background. The self-organizing map (SOM) is an excellent tool in exploratory phase of data mining. It projects its input space on prototypes of a low-dimensional regular grid that ca...
2205.15947
Michael Oberst
Nikolaj Thams, Michael Oberst, David Sontag
Evaluating Robustness to Dataset Shift via Parametric Robustness Sets
NeurIPS 2022; Equal Contribution by Nikolaj/Michael, order determined by coin flip
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We give a method for proactively identifying small, plausible shifts in distribution which lead to large differences in model performance. These shifts are defined via parametric changes in the causal mechanisms of observed variables, where constraints on parameters yield a "robustness set" of plausible distributions...
[ { "created": "Tue, 31 May 2022 16:44:18 GMT", "version": "v1" }, { "created": "Wed, 6 Jul 2022 15:11:48 GMT", "version": "v2" }, { "created": "Sun, 23 Oct 2022 16:27:18 GMT", "version": "v3" }, { "created": "Sun, 15 Jan 2023 05:43:40 GMT", "version": "v4" } ]
2023-01-18
[ [ "Thams", "Nikolaj", "" ], [ "Oberst", "Michael", "" ], [ "Sontag", "David", "" ] ]
We give a method for proactively identifying small, plausible shifts in distribution which lead to large differences in model performance. These shifts are defined via parametric changes in the causal mechanisms of observed variables, where constraints on parameters yield a "robustness set" of plausible distributions a...
1810.09878
Tara Salman
Deval Bhamare, Tara Salman, Mohammed Samaka, Aiman Erbad, Raj Jain
Feasibility of Supervised Machine Learning for Cloud Security
null
2016 International Conference on Information Science and Security (ICISS)
10.1109/ICISSEC.2016.7885853
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Cloud computing is gaining significant attention, however, security is the biggest hurdle in its wide acceptance. Users of cloud services are under constant fear of data loss, security threats and availability issues. Recently, learning-based methods for security applications are gaining popularity in the literature ...
[ { "created": "Tue, 23 Oct 2018 14:23:43 GMT", "version": "v1" } ]
2018-10-24
[ [ "Bhamare", "Deval", "" ], [ "Salman", "Tara", "" ], [ "Samaka", "Mohammed", "" ], [ "Erbad", "Aiman", "" ], [ "Jain", "Raj", "" ] ]
Cloud computing is gaining significant attention, however, security is the biggest hurdle in its wide acceptance. Users of cloud services are under constant fear of data loss, security threats and availability issues. Recently, learning-based methods for security applications are gaining popularity in the literature wi...
1210.6855
Michal \v{C}\'ap
Michal \v{C}\'ap and Peter Nov\'ak and Ji\v{r}\'i Vok\v{r}\'inek and Michal P\v{e}chou\v{c}ek
Asynchronous Decentralized Algorithm for Space-Time Cooperative Pathfinding
null
Spatio-Temporal Dynamics (STeDy 2012). Editors: Mehul Bhatt, Hans Guesgen, and Ernest Davis. Workshop Proceedings of the European Conference on Articial Intelligence (ECAI 2012), Montpellier, France
null
null
cs.AI cs.DC cs.RO
http://creativecommons.org/licenses/by-nc-sa/3.0/
Cooperative pathfinding is a multi-agent path planning problem where a group of vehicles searches for a corresponding set of non-conflicting space-time trajectories. Many of the practical methods for centralized solving of cooperative pathfinding problems are based on the prioritized planning strategy. However, in so...
[ { "created": "Thu, 25 Oct 2012 14:35:27 GMT", "version": "v1" } ]
2012-10-26
[ [ "Čáp", "Michal", "" ], [ "Novák", "Peter", "" ], [ "Vokřínek", "Jiří", "" ], [ "Pěchouček", "Michal", "" ] ]
Cooperative pathfinding is a multi-agent path planning problem where a group of vehicles searches for a corresponding set of non-conflicting space-time trajectories. Many of the practical methods for centralized solving of cooperative pathfinding problems are based on the prioritized planning strategy. However, in some...
1910.09036
Aude Genevay
Aude Genevay, Gabriel Dulac-Arnold, Jean-Philippe Vert
Differentiable Deep Clustering with Cluster Size Constraints
null
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Clustering is a fundamental unsupervised learning approach. Many clustering algorithms -- such as $k$-means -- rely on the euclidean distance as a similarity measure, which is often not the most relevant metric for high dimensional data such as images. Learning a lower-dimensional embedding that can better reflect th...
[ { "created": "Sun, 20 Oct 2019 17:54:45 GMT", "version": "v1" } ]
2019-10-22
[ [ "Genevay", "Aude", "" ], [ "Dulac-Arnold", "Gabriel", "" ], [ "Vert", "Jean-Philippe", "" ] ]
Clustering is a fundamental unsupervised learning approach. Many clustering algorithms -- such as $k$-means -- rely on the euclidean distance as a similarity measure, which is often not the most relevant metric for high dimensional data such as images. Learning a lower-dimensional embedding that can better reflect the ...
0704.1068
Leo Liberti
Giacomo Nannicini, Philippe Baptiste, Gilles Barbier, Daniel Krob, Leo Liberti
Fast paths in large-scale dynamic road networks
12 pages, 4 figures
null
null
null
cs.NI cs.DS
null
Efficiently computing fast paths in large scale dynamic road networks (where dynamic traffic information is known over a part of the network) is a practical problem faced by several traffic information service providers who wish to offer a realistic fast path computation to GPS terminal enabled vehicles. The heuristi...
[ { "created": "Mon, 9 Apr 2007 07:04:19 GMT", "version": "v1" }, { "created": "Wed, 27 Jun 2007 18:17:35 GMT", "version": "v2" } ]
2007-06-27
[ [ "Nannicini", "Giacomo", "" ], [ "Baptiste", "Philippe", "" ], [ "Barbier", "Gilles", "" ], [ "Krob", "Daniel", "" ], [ "Liberti", "Leo", "" ] ]
Efficiently computing fast paths in large scale dynamic road networks (where dynamic traffic information is known over a part of the network) is a practical problem faced by several traffic information service providers who wish to offer a realistic fast path computation to GPS terminal enabled vehicles. The heuristic ...
1112.2113
Varun Raj Kompella
Varun Raj Kompella, Matthew Luciw and Juergen Schmidhuber
Incremental Slow Feature Analysis: Adaptive and Episodic Learning from High-Dimensional Input Streams
null
Neural Computation, 2012, Vol. 24, No. 11, Pages 2994-3024
null
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Slow Feature Analysis (SFA) extracts features representing the underlying causes of changes within a temporally coherent high-dimensional raw sensory input signal. Our novel incremental version of SFA (IncSFA) combines incremental Principal Components Analysis and Minor Components Analysis. Unlike standard batch-base...
[ { "created": "Fri, 9 Dec 2011 15:01:25 GMT", "version": "v1" } ]
2012-10-11
[ [ "Kompella", "Varun Raj", "" ], [ "Luciw", "Matthew", "" ], [ "Schmidhuber", "Juergen", "" ] ]
Slow Feature Analysis (SFA) extracts features representing the underlying causes of changes within a temporally coherent high-dimensional raw sensory input signal. Our novel incremental version of SFA (IncSFA) combines incremental Principal Components Analysis and Minor Components Analysis. Unlike standard batch-based ...
1907.10247
Yijie Guo
Yijie Guo, Jongwook Choi, Marcin Moczulski, Shengyu Feng, Samy Bengio, Mohammad Norouzi, Honglak Lee
Memory Based Trajectory-conditioned Policies for Learning from Sparse Rewards
null
null
null
null
cs.LG cs.AI stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Reinforcement learning with sparse rewards is challenging because an agent can rarely obtain non-zero rewards and hence, gradient-based optimization of parameterized policies can be incremental and slow. Recent work demonstrated that using a memory buffer of previous successful trajectories can result in more effecti...
[ { "created": "Wed, 24 Jul 2019 05:46:27 GMT", "version": "v1" }, { "created": "Wed, 20 Nov 2019 00:41:38 GMT", "version": "v2" }, { "created": "Mon, 15 Feb 2021 03:53:20 GMT", "version": "v3" } ]
2021-02-16
[ [ "Guo", "Yijie", "" ], [ "Choi", "Jongwook", "" ], [ "Moczulski", "Marcin", "" ], [ "Feng", "Shengyu", "" ], [ "Bengio", "Samy", "" ], [ "Norouzi", "Mohammad", "" ], [ "Lee", "Honglak", "" ] ]
Reinforcement learning with sparse rewards is challenging because an agent can rarely obtain non-zero rewards and hence, gradient-based optimization of parameterized policies can be incremental and slow. Recent work demonstrated that using a memory buffer of previous successful trajectories can result in more effective...
2401.08930
Haorui Ji
Haorui Ji, Hongdong Li
3D Human Pose Analysis via Diffusion Synthesis
null
null
null
null
cs.CV cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Diffusion models have demonstrated remarkable success in generative modeling. In this paper, we propose PADS (Pose Analysis by Diffusion Synthesis), a novel framework designed to address various challenges in 3D human pose analysis through a unified pipeline. Central to PADS are two distinctive strategies: i) learnin...
[ { "created": "Wed, 17 Jan 2024 02:59:34 GMT", "version": "v1" } ]
2024-01-18
[ [ "Ji", "Haorui", "" ], [ "Li", "Hongdong", "" ] ]
Diffusion models have demonstrated remarkable success in generative modeling. In this paper, we propose PADS (Pose Analysis by Diffusion Synthesis), a novel framework designed to address various challenges in 3D human pose analysis through a unified pipeline. Central to PADS are two distinctive strategies: i) learning ...
2309.04802
Qingtian Bian
Qingtian Bian, Jiaxing Xu, Hui Fang, Yiping Ke
CPMR: Context-Aware Incremental Sequential Recommendation with Pseudo-Multi-Task Learning
Accepted by CIKM 2023. Alias: "Modeling Context-Aware Temporal Dynamics via Pseudo-Multi-Task Learning"
ACM International Conference on Information and Knowledge Management(CIKM '23), October 21-25,2023,Birmingham,United Kingdom
10.1145/3583780.3615512
null
cs.IR cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The motivations of users to make interactions can be divided into static preference and dynamic interest. To accurately model user representations over time, recent studies in sequential recommendation utilize information propagation and evolution to mine from batches of arriving interactions. However, they ignore th...
[ { "created": "Sat, 9 Sep 2023 14:07:11 GMT", "version": "v1" }, { "created": "Thu, 14 Sep 2023 02:31:12 GMT", "version": "v2" }, { "created": "Sat, 16 Sep 2023 08:52:00 GMT", "version": "v3" } ]
2023-09-19
[ [ "Bian", "Qingtian", "" ], [ "Xu", "Jiaxing", "" ], [ "Fang", "Hui", "" ], [ "Ke", "Yiping", "" ] ]
The motivations of users to make interactions can be divided into static preference and dynamic interest. To accurately model user representations over time, recent studies in sequential recommendation utilize information propagation and evolution to mine from batches of arriving interactions. However, they ignore the ...
2306.09244
Zijian Zhou
Zijian Zhou, Oluwatosin Alabi, Meng Wei, Tom Vercauteren, Miaojing Shi
Text Promptable Surgical Instrument Segmentation with Vision-Language Models
NeurIPS 2023
https://proceedings.neurips.cc/paper_files/paper/2023/hash/5af741d487c5f0b08bfe56e11d1883e4-Abstract-Conference.html
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
In this paper, we propose a novel text promptable surgical instrument segmentation approach to overcome challenges associated with diversity and differentiation of surgical instruments in minimally invasive surgeries. We redefine the task as text promptable, thereby enabling a more nuanced comprehension of surgical i...
[ { "created": "Thu, 15 Jun 2023 16:26:20 GMT", "version": "v1" }, { "created": "Sun, 29 Oct 2023 10:07:43 GMT", "version": "v2" }, { "created": "Wed, 8 Nov 2023 15:36:17 GMT", "version": "v3" } ]
2024-06-05
[ [ "Zhou", "Zijian", "" ], [ "Alabi", "Oluwatosin", "" ], [ "Wei", "Meng", "" ], [ "Vercauteren", "Tom", "" ], [ "Shi", "Miaojing", "" ] ]
In this paper, we propose a novel text promptable surgical instrument segmentation approach to overcome challenges associated with diversity and differentiation of surgical instruments in minimally invasive surgeries. We redefine the task as text promptable, thereby enabling a more nuanced comprehension of surgical ins...
2303.15198
Pengwei Liang
Pengwei Liang, Junjun Jiang, Xianming Liu, Jiayi Ma
Image Deblurring by Exploring In-depth Properties of Transformer
accept by IEEE Transactions on Neural Networks and Learning Systems
IEEE Transactions on Neural Networks and Learning Systems 2024
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Image deblurring continues to achieve impressive performance with the development of generative models. Nonetheless, there still remains a displeasing problem if one wants to improve perceptual quality and quantitative scores of recovered image at the same time. In this study, drawing inspiration from the research of...
[ { "created": "Fri, 24 Mar 2023 14:14:25 GMT", "version": "v1" }, { "created": "Sat, 27 Jan 2024 05:47:40 GMT", "version": "v2" } ]
2024-01-30
[ [ "Liang", "Pengwei", "" ], [ "Jiang", "Junjun", "" ], [ "Liu", "Xianming", "" ], [ "Ma", "Jiayi", "" ] ]
Image deblurring continues to achieve impressive performance with the development of generative models. Nonetheless, there still remains a displeasing problem if one wants to improve perceptual quality and quantitative scores of recovered image at the same time. In this study, drawing inspiration from the research of t...
1601.07279
Mikko Lauri
Mikko Lauri, Nikolay Atanasov, George J. Pappas, Risto Ritala
Myopic Policy Bounds for Information Acquisition POMDPs
8 pages, 3 figures
null
null
null
cs.SY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper addresses the problem of optimal control of robotic sensing systems aimed at autonomous information gathering in scenarios such as environmental monitoring, search and rescue, and surveillance and reconnaissance. The information gathering problem is formulated as a partially observable Markov decision proc...
[ { "created": "Wed, 27 Jan 2016 07:10:06 GMT", "version": "v1" } ]
2016-01-28
[ [ "Lauri", "Mikko", "" ], [ "Atanasov", "Nikolay", "" ], [ "Pappas", "George J.", "" ], [ "Ritala", "Risto", "" ] ]
This paper addresses the problem of optimal control of robotic sensing systems aimed at autonomous information gathering in scenarios such as environmental monitoring, search and rescue, and surveillance and reconnaissance. The information gathering problem is formulated as a partially observable Markov decision proces...
2404.01701
Tristan Ratz
Marcel Nawrath, Agnieszka Nowak, Tristan Ratz, Danilo C. Walenta, Juri Opitz, Leonardo F. R. Ribeiro, Jo\~ao Sedoc, Daniel Deutsch, Simon Mille, Yixin Liu, Lining Zhang, Sebastian Gehrmann, Saad Mahamood, Miruna Clinciu, Khyathi Chandu, Yufang Hou
On the Role of Summary Content Units in Text Summarization Evaluation
10 Pages, 3 Figures, 3 Tables, camera ready version accepted at NAACL 2024
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
At the heart of the Pyramid evaluation method for text summarization lie human written summary content units (SCUs). These SCUs are concise sentences that decompose a summary into small facts. Such SCUs can be used to judge the quality of a candidate summary, possibly partially automated via natural language inferenc...
[ { "created": "Tue, 2 Apr 2024 07:09:44 GMT", "version": "v1" } ]
2024-04-03
[ [ "Nawrath", "Marcel", "" ], [ "Nowak", "Agnieszka", "" ], [ "Ratz", "Tristan", "" ], [ "Walenta", "Danilo C.", "" ], [ "Opitz", "Juri", "" ], [ "Ribeiro", "Leonardo F. R.", "" ], [ "Sedoc", "João", "" ], ...
At the heart of the Pyramid evaluation method for text summarization lie human written summary content units (SCUs). These SCUs are concise sentences that decompose a summary into small facts. Such SCUs can be used to judge the quality of a candidate summary, possibly partially automated via natural language inference ...
1909.06228
S VenkataKeerthy
S. VenkataKeerthy, Rohit Aggarwal, Shalini Jain, Maunendra Sankar Desarkar, Ramakrishna Upadrasta and Y. N. Srikant
IR2Vec: LLVM IR based Scalable Program Embeddings
Accepted in ACM TACO
null
10.1145/3418463
null
cs.PL cs.LG cs.NE cs.SE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We propose IR2Vec, a Concise and Scalable encoding infrastructure to represent programs as a distributed embedding in continuous space. This distributed embedding is obtained by combining representation learning methods with flow information to capture the syntax as well as the semantics of the input programs. As our...
[ { "created": "Fri, 13 Sep 2019 13:41:40 GMT", "version": "v1" }, { "created": "Wed, 1 Jan 2020 06:22:25 GMT", "version": "v2" }, { "created": "Tue, 1 Sep 2020 09:24:01 GMT", "version": "v3" } ]
2020-12-25
[ [ "VenkataKeerthy", "S.", "" ], [ "Aggarwal", "Rohit", "" ], [ "Jain", "Shalini", "" ], [ "Desarkar", "Maunendra Sankar", "" ], [ "Upadrasta", "Ramakrishna", "" ], [ "Srikant", "Y. N.", "" ] ]
We propose IR2Vec, a Concise and Scalable encoding infrastructure to represent programs as a distributed embedding in continuous space. This distributed embedding is obtained by combining representation learning methods with flow information to capture the syntax as well as the semantics of the input programs. As our i...
1903.01392
Sherif Abdulatif
Karim Armanious, Sherif Abdulatif, Fady Aziz, Urs Schneider, Bin Yang
An Adversarial Super-Resolution Remedy for Radar Design Trade-offs
Accepted in EUSIPCO 2019, 5 pages
null
10.23919/EUSIPCO.2019.8902510
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Radar is of vital importance in many fields, such as autonomous driving, safety and surveillance applications. However, it suffers from stringent constraints on its design parametrization leading to multiple trade-offs. For example, the bandwidth in FMCW radars is inversely proportional with both the maximum unambigu...
[ { "created": "Mon, 4 Mar 2019 17:41:26 GMT", "version": "v1" }, { "created": "Thu, 20 Jun 2019 16:23:55 GMT", "version": "v2" } ]
2019-11-26
[ [ "Armanious", "Karim", "" ], [ "Abdulatif", "Sherif", "" ], [ "Aziz", "Fady", "" ], [ "Schneider", "Urs", "" ], [ "Yang", "Bin", "" ] ]
Radar is of vital importance in many fields, such as autonomous driving, safety and surveillance applications. However, it suffers from stringent constraints on its design parametrization leading to multiple trade-offs. For example, the bandwidth in FMCW radars is inversely proportional with both the maximum unambiguou...
1004.4128
Emanuel Gluskin
Emanuel Gluskin
An approximate analytical (structural) superposition in terms of two, or more, "alfa"-circuits of the same topology: Pt.1 - description of the superposition
This is my old (2005-6) Ms.. The "f-connection" is new and thus the work seems to be too detailed, but some central proofs were difficult for me, and having to be sure in good precision of the "analytical superposition", I calculated different cases. See in http://www.ee.bgu.ac.il/~gluskin/ Article no 50 and th...
null
null
null
cs.OH
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
One-ports named "f-circuits", composed of similar conductors described by a monotonic polynomial, or quasi-polynomial (i.e. with positive but not necessarily integer, powers) characteristic i = f(v) are studied, focusing on the algebraic map f --> F. Here F(.) is the input conductivity characteristic; i.e., iin = F(v...
[ { "created": "Fri, 23 Apr 2010 13:26:34 GMT", "version": "v1" }, { "created": "Mon, 26 Apr 2010 06:36:05 GMT", "version": "v2" } ]
2010-04-28
[ [ "Gluskin", "Emanuel", "" ] ]
One-ports named "f-circuits", composed of similar conductors described by a monotonic polynomial, or quasi-polynomial (i.e. with positive but not necessarily integer, powers) characteristic i = f(v) are studied, focusing on the algebraic map f --> F. Here F(.) is the input conductivity characteristic; i.e., iin = F(vin...
cs/0501046
Tommaso Toffoli
Tommaso Toffoli
Thermodynamics of used punched tape: A weak and a strong equivalence principle
7 pages, 8 figures
null
null
null
cs.IT math.IT
null
We study the repeated use of a monotonic recording medium--such as punched tape or photographic plate--where marks can be added at any time but never erased. (For practical purposes, also the electromagnetic "ether" falls into this class.) Our emphasis is on the case where the successive users act independently and s...
[ { "created": "Fri, 21 Jan 2005 04:17:50 GMT", "version": "v1" } ]
2007-07-13
[ [ "Toffoli", "Tommaso", "" ] ]
We study the repeated use of a monotonic recording medium--such as punched tape or photographic plate--where marks can be added at any time but never erased. (For practical purposes, also the electromagnetic "ether" falls into this class.) Our emphasis is on the case where the successive users act independently and sel...
2010.12885
Tong Niu
Tong Niu, Semih Yavuz, Yingbo Zhou, Nitish Shirish Keskar, Huan Wang, Caiming Xiong
Unsupervised Paraphrasing with Pretrained Language Models
Accepted at EMNLP 2021 main conference
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Paraphrase generation has benefited extensively from recent progress in the designing of training objectives and model architectures. However, previous explorations have largely focused on supervised methods, which require a large amount of labeled data that is costly to collect. To address this drawback, we adopt a ...
[ { "created": "Sat, 24 Oct 2020 11:55:28 GMT", "version": "v1" }, { "created": "Fri, 10 Sep 2021 20:50:19 GMT", "version": "v2" } ]
2021-09-14
[ [ "Niu", "Tong", "" ], [ "Yavuz", "Semih", "" ], [ "Zhou", "Yingbo", "" ], [ "Keskar", "Nitish Shirish", "" ], [ "Wang", "Huan", "" ], [ "Xiong", "Caiming", "" ] ]
Paraphrase generation has benefited extensively from recent progress in the designing of training objectives and model architectures. However, previous explorations have largely focused on supervised methods, which require a large amount of labeled data that is costly to collect. To address this drawback, we adopt a tr...
1910.02830
Viraj Prabhu
Viraj Prabhu, Anitha Kannan, Geoffrey J. Tso, Namit Katariya, Manish Chablani, David Sontag, Xavier Amatriain
Open Set Medical Diagnosis
Abbreviated version to appear at Machine Learning for Healthcare (ML4H) Workshop at NeurIPS 2019
null
null
null
cs.LG cs.AI stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Machine-learned diagnosis models have shown promise as medical aides but are trained under a closed-set assumption, i.e. that models will only encounter conditions on which they have been trained. However, it is practically infeasible to obtain sufficient training data for every human condition, and once deployed suc...
[ { "created": "Mon, 7 Oct 2019 14:45:47 GMT", "version": "v1" } ]
2019-10-08
[ [ "Prabhu", "Viraj", "" ], [ "Kannan", "Anitha", "" ], [ "Tso", "Geoffrey J.", "" ], [ "Katariya", "Namit", "" ], [ "Chablani", "Manish", "" ], [ "Sontag", "David", "" ], [ "Amatriain", "Xavier", "" ] ]
Machine-learned diagnosis models have shown promise as medical aides but are trained under a closed-set assumption, i.e. that models will only encounter conditions on which they have been trained. However, it is practically infeasible to obtain sufficient training data for every human condition, and once deployed such ...
2006.10923
Amish Patel
Amish Patel and Aravind Varier
Hyperparameter Analysis for Image Captioning
10 pages, 9 figures, and 7 tables
null
null
null
cs.CV cs.LG
http://creativecommons.org/licenses/by/4.0/
In this paper, we perform a thorough sensitivity analysis on state-of-the-art image captioning approaches using two different architectures: CNN+LSTM and CNN+Transformer. Experiments were carried out using the Flickr8k dataset. The biggest takeaway from the experiments is that fine-tuning the CNN encoder outperforms ...
[ { "created": "Fri, 19 Jun 2020 01:49:37 GMT", "version": "v1" } ]
2020-06-22
[ [ "Patel", "Amish", "" ], [ "Varier", "Aravind", "" ] ]
In this paper, we perform a thorough sensitivity analysis on state-of-the-art image captioning approaches using two different architectures: CNN+LSTM and CNN+Transformer. Experiments were carried out using the Flickr8k dataset. The biggest takeaway from the experiments is that fine-tuning the CNN encoder outperforms th...
2101.02496
Manuel Lagunas
Manuel Lagunas, Ana Serrano, Diego Gutierrez, Belen Masia
The joint role of geometry and illumination on material recognition
15 pages, 16 figures, Accepted to the Journal of Vision, 2021
Journal of Vision February 2021, Vol.21, 2
10.1167/jov.21.2.2
null
cs.CV cs.AI cs.GR
http://creativecommons.org/licenses/by-nc-nd/4.0/
Observing and recognizing materials is a fundamental part of our daily life. Under typical viewing conditions, we are capable of effortlessly identifying the objects that surround us and recognizing the materials they are made of. Nevertheless, understanding the underlying perceptual processes that take place to accu...
[ { "created": "Thu, 7 Jan 2021 11:29:52 GMT", "version": "v1" }, { "created": "Thu, 4 Feb 2021 12:35:25 GMT", "version": "v2" } ]
2021-02-05
[ [ "Lagunas", "Manuel", "" ], [ "Serrano", "Ana", "" ], [ "Gutierrez", "Diego", "" ], [ "Masia", "Belen", "" ] ]
Observing and recognizing materials is a fundamental part of our daily life. Under typical viewing conditions, we are capable of effortlessly identifying the objects that surround us and recognizing the materials they are made of. Nevertheless, understanding the underlying perceptual processes that take place to accura...
1909.07208
Emna Rejaibi
Emna Rejaibi, Ali Komaty, Fabrice Meriaudeau, Said Agrebi, and Alice Othmani
MFCC-based Recurrent Neural Network for Automatic Clinical Depression Recognition and Assessment from Speech
14 pages, 7 figures, 9 tables
null
null
null
cs.HC cs.AI cs.LG eess.AS
http://creativecommons.org/licenses/by-nc-sa/4.0/
Clinical depression or Major Depressive Disorder (MDD) is a common and serious medical illness. In this paper, a deep recurrent neural network-based framework is presented to detect depression and to predict its severity level from speech. Low-level and high-level audio features are extracted from audio recordings to...
[ { "created": "Mon, 16 Sep 2019 14:03:01 GMT", "version": "v1" }, { "created": "Thu, 12 Mar 2020 13:09:24 GMT", "version": "v2" } ]
2020-03-13
[ [ "Rejaibi", "Emna", "" ], [ "Komaty", "Ali", "" ], [ "Meriaudeau", "Fabrice", "" ], [ "Agrebi", "Said", "" ], [ "Othmani", "Alice", "" ] ]
Clinical depression or Major Depressive Disorder (MDD) is a common and serious medical illness. In this paper, a deep recurrent neural network-based framework is presented to detect depression and to predict its severity level from speech. Low-level and high-level audio features are extracted from audio recordings to p...
2012.10613
Piotr Antonik
Piotr Antonik, Marc Haelterman, Serge Massar
Online training for high-performance analogue readout layers in photonic reservoir computers
11 pages, 5 figures
Cognitive Computation (Volume: 9, Pages: 297-306, 11 March 2017)
10.1007/s12559-017-9459-3
null
cs.NE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Introduction. Reservoir Computing is a bio-inspired computing paradigm for processing time-dependent signals. The performance of its hardware implementation is comparable to state-of-the-art digital algorithms on a series of benchmark tasks. The major bottleneck of these implementation is the readout layer, based on ...
[ { "created": "Sat, 19 Dec 2020 07:12:26 GMT", "version": "v1" } ]
2020-12-22
[ [ "Antonik", "Piotr", "" ], [ "Haelterman", "Marc", "" ], [ "Massar", "Serge", "" ] ]
Introduction. Reservoir Computing is a bio-inspired computing paradigm for processing time-dependent signals. The performance of its hardware implementation is comparable to state-of-the-art digital algorithms on a series of benchmark tasks. The major bottleneck of these implementation is the readout layer, based on sl...
1602.01516
Sina Parhizi
Sina Parhizi and Amin Khodaei
Market-based Microgrid Optimal Scheduling
Appeared in 6th IEEE International Conference on Smart Grid Communications (SmartGridComm 2015)
null
null
null
cs.SY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper presents an optimal scheduling model for a microgrid participating in the electricity distribution market in interaction with the Distribution Market Operator (DMO). The DMO is a concept proposed here, which administers the established electricity market in the distribution level, i.e., similar to the role...
[ { "created": "Thu, 4 Feb 2016 00:49:07 GMT", "version": "v1" } ]
2016-02-05
[ [ "Parhizi", "Sina", "" ], [ "Khodaei", "Amin", "" ] ]
This paper presents an optimal scheduling model for a microgrid participating in the electricity distribution market in interaction with the Distribution Market Operator (DMO). The DMO is a concept proposed here, which administers the established electricity market in the distribution level, i.e., similar to the role o...
2303.01125
Xuechen Liu
Xuechen Liu, Md Sahidullah, Tomi Kinnunen
Distilling Multi-Level X-vector Knowledge for Small-footprint Speaker Verification
Submitted to Data & Knowledge Engineering at Dec. 2023. Copyright may be transferred without notice
null
null
null
cs.SD cs.LG eess.AS
http://creativecommons.org/licenses/by/4.0/
Even though deep speaker models have demonstrated impressive accuracy in speaker verification tasks, this often comes at the expense of increased model size and computation time, presenting challenges for deployment in resource-constrained environments. Our research focuses on addressing this limitation through the d...
[ { "created": "Thu, 2 Mar 2023 10:09:11 GMT", "version": "v1" }, { "created": "Fri, 15 Dec 2023 13:37:19 GMT", "version": "v2" }, { "created": "Tue, 19 Dec 2023 23:25:01 GMT", "version": "v3" } ]
2023-12-21
[ [ "Liu", "Xuechen", "" ], [ "Sahidullah", "Md", "" ], [ "Kinnunen", "Tomi", "" ] ]
Even though deep speaker models have demonstrated impressive accuracy in speaker verification tasks, this often comes at the expense of increased model size and computation time, presenting challenges for deployment in resource-constrained environments. Our research focuses on addressing this limitation through the dev...
1611.10305
Qunwei Li
Qunwei Li, Bhavya Kailkhura, Jayaraman J. Thiagarajan, Zhenliang Zhang, Pramod K. Varshney
Influential Node Detection in Implicit Social Networks using Multi-task Gaussian Copula Models
NIPS 2016 Workshop, JMLR: Workshop and Conference Proceedings
null
null
null
cs.SI cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Influential node detection is a central research topic in social network analysis. Many existing methods rely on the assumption that the network structure is completely known \textit{a priori}. However, in many applications, network structure is unavailable to explain the underlying information diffusion phenomenon. ...
[ { "created": "Wed, 30 Nov 2016 18:46:55 GMT", "version": "v1" } ]
2016-12-01
[ [ "Li", "Qunwei", "" ], [ "Kailkhura", "Bhavya", "" ], [ "Thiagarajan", "Jayaraman J.", "" ], [ "Zhang", "Zhenliang", "" ], [ "Varshney", "Pramod K.", "" ] ]
Influential node detection is a central research topic in social network analysis. Many existing methods rely on the assumption that the network structure is completely known \textit{a priori}. However, in many applications, network structure is unavailable to explain the underlying information diffusion phenomenon. To...
2402.01342
Zexi Li
Zexi Li, Zhiqi Li, Jie Lin, Tao Shen, Tao Lin, Chao Wu
Training-time Neuron Alignment through Permutation Subspace for Improving Linear Mode Connectivity and Model Fusion
preprint
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In deep learning, stochastic gradient descent often yields functionally similar yet widely scattered solutions in the weight space even under the same initialization, causing barriers in the Linear Mode Connectivity (LMC) landscape. Overcoming these barriers is crucial for understanding deep learning dynamics and enh...
[ { "created": "Fri, 2 Feb 2024 11:57:50 GMT", "version": "v1" } ]
2024-02-05
[ [ "Li", "Zexi", "" ], [ "Li", "Zhiqi", "" ], [ "Lin", "Jie", "" ], [ "Shen", "Tao", "" ], [ "Lin", "Tao", "" ], [ "Wu", "Chao", "" ] ]
In deep learning, stochastic gradient descent often yields functionally similar yet widely scattered solutions in the weight space even under the same initialization, causing barriers in the Linear Mode Connectivity (LMC) landscape. Overcoming these barriers is crucial for understanding deep learning dynamics and enhan...
1701.03041
Matthew Veres
Matthew Veres, Medhat Moussa, Graham W. Taylor
Modeling Grasp Motor Imagery through Deep Conditional Generative Models
Accepted for publication in Robotics and Automation Letters (RA-L)
null
null
null
cs.RO stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Grasping is a complex process involving knowledge of the object, the surroundings, and of oneself. While humans are able to integrate and process all of the sensory information required for performing this task, equipping machines with this capability is an extremely challenging endeavor. In this paper, we investigat...
[ { "created": "Wed, 11 Jan 2017 16:20:39 GMT", "version": "v1" } ]
2017-01-12
[ [ "Veres", "Matthew", "" ], [ "Moussa", "Medhat", "" ], [ "Taylor", "Graham W.", "" ] ]
Grasping is a complex process involving knowledge of the object, the surroundings, and of oneself. While humans are able to integrate and process all of the sensory information required for performing this task, equipping machines with this capability is an extremely challenging endeavor. In this paper, we investigate ...
2404.04531
Xianping Ma
Xianping Ma, Xiaokang Zhang, Xingchen Ding, Man-On Pun, Siwei Ma
Frequency Decomposition-Driven Unsupervised Domain Adaptation for Remote Sensing Image Semantic Segmentation
28 pages, 13 figures
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Cross-domain semantic segmentation of remote sensing (RS) imagery based on unsupervised domain adaptation (UDA) techniques has significantly advanced deep-learning applications in the geosciences. Recently, with its ingenious and versatile architecture, the Transformer model has been successfully applied in RS-UDA ta...
[ { "created": "Sat, 6 Apr 2024 07:13:49 GMT", "version": "v1" } ]
2024-04-09
[ [ "Ma", "Xianping", "" ], [ "Zhang", "Xiaokang", "" ], [ "Ding", "Xingchen", "" ], [ "Pun", "Man-On", "" ], [ "Ma", "Siwei", "" ] ]
Cross-domain semantic segmentation of remote sensing (RS) imagery based on unsupervised domain adaptation (UDA) techniques has significantly advanced deep-learning applications in the geosciences. Recently, with its ingenious and versatile architecture, the Transformer model has been successfully applied in RS-UDA task...
2401.17482
Workneh Yilma Ayele
Johan Sandell, Einar Asplund, Workneh Yilma Ayele, Martin Duneld
Performance Comparison Analysis of ArangoDB, MySQL, and Neo4j: An Experimental Study of Querying Connected Data
https://hdl.handle.net/10125/107319
2024, Proceedings of the 57th Hawaii International Conference on System Sciences
null
null
cs.DB
http://creativecommons.org/licenses/by-nc-nd/4.0/
Choosing and developing performant database solutions helps organizations optimize their operational practices and decision-making. Since graph data is becoming more common, it is crucial to develop and use them in big data with complex relationships with high and consistent performance. However, legacy database tech...
[ { "created": "Tue, 30 Jan 2024 22:35:26 GMT", "version": "v1" } ]
2024-02-01
[ [ "Sandell", "Johan", "" ], [ "Asplund", "Einar", "" ], [ "Ayele", "Workneh Yilma", "" ], [ "Duneld", "Martin", "" ] ]
Choosing and developing performant database solutions helps organizations optimize their operational practices and decision-making. Since graph data is becoming more common, it is crucial to develop and use them in big data with complex relationships with high and consistent performance. However, legacy database techno...
2007.01951
Liwei Wang
Liwei Wang, Jing Huang, Yin Li, Kun Xu, Zhengyuan Yang, Dong Yu
Improving Weakly Supervised Visual Grounding by Contrastive Knowledge Distillation
null
null
null
null
cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Weakly supervised phrase grounding aims at learning region-phrase correspondences using only image-sentence pairs. A major challenge thus lies in the missing links between image regions and sentence phrases during training. To address this challenge, we leverage a generic object detector at training time, and propose...
[ { "created": "Fri, 3 Jul 2020 22:02:00 GMT", "version": "v1" }, { "created": "Sun, 25 Apr 2021 05:11:11 GMT", "version": "v2" } ]
2021-04-27
[ [ "Wang", "Liwei", "" ], [ "Huang", "Jing", "" ], [ "Li", "Yin", "" ], [ "Xu", "Kun", "" ], [ "Yang", "Zhengyuan", "" ], [ "Yu", "Dong", "" ] ]
Weakly supervised phrase grounding aims at learning region-phrase correspondences using only image-sentence pairs. A major challenge thus lies in the missing links between image regions and sentence phrases during training. To address this challenge, we leverage a generic object detector at training time, and propose a...
2407.15787
Yike Zhang
Yike Zhang, Dingjie Su, Eduardo Davalos, Jack H. Noble
Unsupervised Mastoidectomy for Cochlear CT Mesh Reconstruction Using Highly Noisy Data
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Cochlear Implant (CI) procedures involve inserting an array of electrodes into the cochlea located inside the inner ear. Mastoidectomy is a surgical procedure that uses a high-speed drill to remove part of the mastoid region of the temporal bone, providing safe access to the cochlea through the middle and inner ear. ...
[ { "created": "Mon, 22 Jul 2024 16:47:29 GMT", "version": "v1" }, { "created": "Thu, 8 Aug 2024 14:33:12 GMT", "version": "v2" } ]
2024-08-09
[ [ "Zhang", "Yike", "" ], [ "Su", "Dingjie", "" ], [ "Davalos", "Eduardo", "" ], [ "Noble", "Jack H.", "" ] ]
Cochlear Implant (CI) procedures involve inserting an array of electrodes into the cochlea located inside the inner ear. Mastoidectomy is a surgical procedure that uses a high-speed drill to remove part of the mastoid region of the temporal bone, providing safe access to the cochlea through the middle and inner ear. We...
2403.00592
Zhaochong An
Zhaochong An, Guolei Sun, Yun Liu, Fayao Liu, Zongwei Wu, Dan Wang, Luc Van Gool, Serge Belongie
Rethinking Few-shot 3D Point Cloud Semantic Segmentation
Accepted to CVPR 2024
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper revisits few-shot 3D point cloud semantic segmentation (FS-PCS), with a focus on two significant issues in the state-of-the-art: foreground leakage and sparse point distribution. The former arises from non-uniform point sampling, allowing models to distinguish the density disparities between foreground and...
[ { "created": "Fri, 1 Mar 2024 15:14:47 GMT", "version": "v1" } ]
2024-03-04
[ [ "An", "Zhaochong", "" ], [ "Sun", "Guolei", "" ], [ "Liu", "Yun", "" ], [ "Liu", "Fayao", "" ], [ "Wu", "Zongwei", "" ], [ "Wang", "Dan", "" ], [ "Van Gool", "Luc", "" ], [ "Belongie", "Serge", ...
This paper revisits few-shot 3D point cloud semantic segmentation (FS-PCS), with a focus on two significant issues in the state-of-the-art: foreground leakage and sparse point distribution. The former arises from non-uniform point sampling, allowing models to distinguish the density disparities between foreground and b...
2311.17910
Muhammed Kocabas
Muhammed Kocabas, Jen-Hao Rick Chang, James Gabriel, Oncel Tuzel, Anurag Ranjan
HUGS: Human Gaussian Splats
null
null
null
null
cs.CV cs.GR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recent advances in neural rendering have improved both training and rendering times by orders of magnitude. While these methods demonstrate state-of-the-art quality and speed, they are designed for photogrammetry of static scenes and do not generalize well to freely moving humans in the environment. In this work, we ...
[ { "created": "Wed, 29 Nov 2023 18:56:32 GMT", "version": "v1" } ]
2023-11-30
[ [ "Kocabas", "Muhammed", "" ], [ "Chang", "Jen-Hao Rick", "" ], [ "Gabriel", "James", "" ], [ "Tuzel", "Oncel", "" ], [ "Ranjan", "Anurag", "" ] ]
Recent advances in neural rendering have improved both training and rendering times by orders of magnitude. While these methods demonstrate state-of-the-art quality and speed, they are designed for photogrammetry of static scenes and do not generalize well to freely moving humans in the environment. In this work, we in...
2308.00939
Xinze Li
Xinze Li, Kezhi Mao, Fanfan Lin, Zijian Feng
Feature-aware conditional GAN for category text generation
27 pages, 8 figures
null
10.1016/j.neucom.2023.126352
null
cs.CL cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Category text generation receives considerable attentions since it is beneficial for various natural language processing tasks. Recently, the generative adversarial network (GAN) has attained promising performance in text generation, attributed to its adversarial training process. However, there are several issues in...
[ { "created": "Wed, 2 Aug 2023 04:43:54 GMT", "version": "v1" } ]
2023-08-03
[ [ "Li", "Xinze", "" ], [ "Mao", "Kezhi", "" ], [ "Lin", "Fanfan", "" ], [ "Feng", "Zijian", "" ] ]
Category text generation receives considerable attentions since it is beneficial for various natural language processing tasks. Recently, the generative adversarial network (GAN) has attained promising performance in text generation, attributed to its adversarial training process. However, there are several issues in t...
2101.12736
Osman Ramadan
Osman Ramadan, James Withers, Douglas Orr
N-grams Bayesian Differential Privacy
12 pages, 6 figures
null
null
null
cs.CR cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Differential privacy has gained popularity in machine learning as a strong privacy guarantee, in contrast to privacy mitigation techniques such as k-anonymity. However, applying differential privacy to n-gram counts significantly degrades the utility of derived language models due to their large vocabularies. We prop...
[ { "created": "Fri, 29 Jan 2021 18:48:49 GMT", "version": "v1" } ]
2021-02-01
[ [ "Ramadan", "Osman", "" ], [ "Withers", "James", "" ], [ "Orr", "Douglas", "" ] ]
Differential privacy has gained popularity in machine learning as a strong privacy guarantee, in contrast to privacy mitigation techniques such as k-anonymity. However, applying differential privacy to n-gram counts significantly degrades the utility of derived language models due to their large vocabularies. We propos...