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2310.10493
Hyun-Jic Oh Mr.
SeungKyu Kim, Hyun-Jic Oh, Seonghui Min and Won-Ki Jeong
Evaluation and improvement of Segment Anything Model for interactive histopathology image segmentation
MICCAI 2023 workshop accepted (1st International Workshop on Foundation Models for General Medical AI - MedAGI)
null
null
null
cs.CV
http://creativecommons.org/licenses/by-nc-sa/4.0/
With the emergence of the Segment Anything Model (SAM) as a foundational model for image segmentation, its application has been extensively studied across various domains, including the medical field. However, its potential in the context of histopathology data, specifically in region segmentation, has received relat...
[ { "created": "Mon, 16 Oct 2023 15:17:06 GMT", "version": "v1" } ]
2023-10-17
[ [ "Kim", "SeungKyu", "" ], [ "Oh", "Hyun-Jic", "" ], [ "Min", "Seonghui", "" ], [ "Jeong", "Won-Ki", "" ] ]
With the emergence of the Segment Anything Model (SAM) as a foundational model for image segmentation, its application has been extensively studied across various domains, including the medical field. However, its potential in the context of histopathology data, specifically in region segmentation, has received relativ...
2310.10071
Yutong Kou
Yutong Kou, Jin Gao, Bing Li, Gang Wang, Weiming Hu, Yizheng Wang and Liang Li
ZoomTrack: Target-aware Non-uniform Resizing for Efficient Visual Tracking
19 pages, 7 figures, Accepted by NeurIPS 2023 as a Spotlight
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recently, the transformer has enabled the speed-oriented trackers to approach state-of-the-art (SOTA) performance with high-speed thanks to the smaller input size or the lighter feature extraction backbone, though they still substantially lag behind their corresponding performance-oriented versions. In this paper, we...
[ { "created": "Mon, 16 Oct 2023 05:06:13 GMT", "version": "v1" } ]
2023-10-17
[ [ "Kou", "Yutong", "" ], [ "Gao", "Jin", "" ], [ "Li", "Bing", "" ], [ "Wang", "Gang", "" ], [ "Hu", "Weiming", "" ], [ "Wang", "Yizheng", "" ], [ "Li", "Liang", "" ] ]
Recently, the transformer has enabled the speed-oriented trackers to approach state-of-the-art (SOTA) performance with high-speed thanks to the smaller input size or the lighter feature extraction backbone, though they still substantially lag behind their corresponding performance-oriented versions. In this paper, we d...
2401.10530
Liangliang Zhao
Junyu Gao, Liangliang Zhao, and Xuelong Li
NWPU-MOC: A Benchmark for Fine-grained Multi-category Object Counting in Aerial Images
null
null
10.1109/TGRS.2024.3356492
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Object counting is a hot topic in computer vision, which aims to estimate the number of objects in a given image. However, most methods only count objects of a single category for an image, which cannot be applied to scenes that need to count objects with multiple categories simultaneously, especially in aerial scene...
[ { "created": "Fri, 19 Jan 2024 07:12:36 GMT", "version": "v1" } ]
2024-01-22
[ [ "Gao", "Junyu", "" ], [ "Zhao", "Liangliang", "" ], [ "Li", "Xuelong", "" ] ]
Object counting is a hot topic in computer vision, which aims to estimate the number of objects in a given image. However, most methods only count objects of a single category for an image, which cannot be applied to scenes that need to count objects with multiple categories simultaneously, especially in aerial scenes....
1606.08694
Martin Alain PhD
Martin Alain, Christine Guillemot, Dominique Thoreau, Philippe Guillotel
Scalable image coding based on epitomes
Preprint submitted to IEEE Trans. on Image Processing
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we propose a novel scheme for scalable image coding based on the concept of epitome. An epitome can be seen as a factorized representation of an image. Focusing on spatial scalability, the enhancement layer of the proposed scheme contains only the epitome of the input image. The pixels of the enhanceme...
[ { "created": "Tue, 28 Jun 2016 13:37:41 GMT", "version": "v1" } ]
2016-06-29
[ [ "Alain", "Martin", "" ], [ "Guillemot", "Christine", "" ], [ "Thoreau", "Dominique", "" ], [ "Guillotel", "Philippe", "" ] ]
In this paper, we propose a novel scheme for scalable image coding based on the concept of epitome. An epitome can be seen as a factorized representation of an image. Focusing on spatial scalability, the enhancement layer of the proposed scheme contains only the epitome of the input image. The pixels of the enhancement...
0710.4655
EDA Publishing Association
Baosheng Wang, Yuejian Wu, Andre Ivanov
A Fast Diagnosis Scheme for Distributed Small Embedded SRAMs
Submitted on behalf of EDAA (http://www.edaa.com/)
Dans Design, Automation and Test in Europe - DATE'05, Munich : Allemagne (2005)
null
null
cs.AR
null
This paper proposes a diagnosis scheme aimed at reducing diagnosis time of distributed small embedded SRAMs (e-SRAMs). This scheme improves the one proposed in [A parallel built-in self-diagnostic method for embedded memory buffers, A parallel built-in self-diagnostic method for embedded memory arrays]. The improveme...
[ { "created": "Thu, 25 Oct 2007 08:34:09 GMT", "version": "v1" } ]
2011-11-09
[ [ "Wang", "Baosheng", "" ], [ "Wu", "Yuejian", "" ], [ "Ivanov", "Andre", "" ] ]
This paper proposes a diagnosis scheme aimed at reducing diagnosis time of distributed small embedded SRAMs (e-SRAMs). This scheme improves the one proposed in [A parallel built-in self-diagnostic method for embedded memory buffers, A parallel built-in self-diagnostic method for embedded memory arrays]. The improvement...
2308.14622
Kaustav Bhattacharjee
Jun Yuan, Kaustav Bhattacharjee, Akm Zahirul Islam and Aritra Dasgupta
TRIVEA: Transparent Ranking Interpretation using Visual Explanation of Black-Box Algorithmic Rankers
Accepted for publication in SpringerNature's Visual Computer Journal
null
null
null
cs.IR cs.AI cs.HC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Ranking schemes drive many real-world decisions, like, where to study, whom to hire, what to buy, etc. Many of these decisions often come with high consequences. For example, a university can be deemed less prestigious if not featured in a top-k list, and consumers might not even explore products that do not get reco...
[ { "created": "Mon, 28 Aug 2023 16:58:44 GMT", "version": "v1" } ]
2023-08-29
[ [ "Yuan", "Jun", "" ], [ "Bhattacharjee", "Kaustav", "" ], [ "Islam", "Akm Zahirul", "" ], [ "Dasgupta", "Aritra", "" ] ]
Ranking schemes drive many real-world decisions, like, where to study, whom to hire, what to buy, etc. Many of these decisions often come with high consequences. For example, a university can be deemed less prestigious if not featured in a top-k list, and consumers might not even explore products that do not get recomm...
2109.13450
Xinhua Wang
Xinhua Wang, Alexei Ashikhmin, Zhicheng Dong, Chao Zhai
Two-Stage Channel Estimation Approach for Cell-Free IoT With Massive Random Access
null
null
null
null
cs.IT cs.NI eess.SP math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We investigate the activity detection and channel estimation issues for cell-free Internet of Things (IoT) networks with massive random access. In each time slot, only partial devices are active and communicate with neighboring access points (APs) using non-orthogonal random pilot sequences. Different from the centra...
[ { "created": "Tue, 28 Sep 2021 02:59:30 GMT", "version": "v1" } ]
2021-09-29
[ [ "Wang", "Xinhua", "" ], [ "Ashikhmin", "Alexei", "" ], [ "Dong", "Zhicheng", "" ], [ "Zhai", "Chao", "" ] ]
We investigate the activity detection and channel estimation issues for cell-free Internet of Things (IoT) networks with massive random access. In each time slot, only partial devices are active and communicate with neighboring access points (APs) using non-orthogonal random pilot sequences. Different from the centrali...
2105.02625
Boyla Mainsah
Anish Karpurapu, Adam Krekorian, Ye Tian, Leslie M. Collins, Ravi Karra, Aaron Franklin and Boyla O. Mainsah
Evaluating the Effect of Longitudinal Dose and INR Data on Maintenance Warfarin Dose Predictions
null
null
null
null
cs.LG stat.AP
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Warfarin, a commonly prescribed drug to prevent blood clots, has a highly variable individual response. Determining a maintenance warfarin dose that achieves a therapeutic blood clotting time, as measured by the international normalized ratio (INR), is crucial in preventing complications. Machine learning algorithms ...
[ { "created": "Thu, 6 May 2021 13:01:42 GMT", "version": "v1" } ]
2021-05-07
[ [ "Karpurapu", "Anish", "" ], [ "Krekorian", "Adam", "" ], [ "Tian", "Ye", "" ], [ "Collins", "Leslie M.", "" ], [ "Karra", "Ravi", "" ], [ "Franklin", "Aaron", "" ], [ "Mainsah", "Boyla O.", "" ] ]
Warfarin, a commonly prescribed drug to prevent blood clots, has a highly variable individual response. Determining a maintenance warfarin dose that achieves a therapeutic blood clotting time, as measured by the international normalized ratio (INR), is crucial in preventing complications. Machine learning algorithms ar...
1612.04337
Tian Qi Chen
Tian Qi Chen and Mark Schmidt
Fast Patch-based Style Transfer of Arbitrary Style
null
null
null
null
cs.CV cs.GR cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Artistic style transfer is an image synthesis problem where the content of an image is reproduced with the style of another. Recent works show that a visually appealing style transfer can be achieved by using the hidden activations of a pretrained convolutional neural network. However, existing methods either apply (...
[ { "created": "Tue, 13 Dec 2016 20:05:37 GMT", "version": "v1" } ]
2016-12-14
[ [ "Chen", "Tian Qi", "" ], [ "Schmidt", "Mark", "" ] ]
Artistic style transfer is an image synthesis problem where the content of an image is reproduced with the style of another. Recent works show that a visually appealing style transfer can be achieved by using the hidden activations of a pretrained convolutional neural network. However, existing methods either apply (i)...
1709.06275
Ryan Carey
Ryan Carey
Incorrigibility in the CIRL Framework
null
null
null
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A value learning system has incentives to follow shutdown instructions, assuming the shutdown instruction provides information (in the technical sense) about which actions lead to valuable outcomes. However, this assumption is not robust to model mis-specification (e.g., in the case of programmer errors). We demonstr...
[ { "created": "Tue, 19 Sep 2017 07:23:18 GMT", "version": "v1" }, { "created": "Sun, 3 Jun 2018 17:43:18 GMT", "version": "v2" } ]
2018-06-05
[ [ "Carey", "Ryan", "" ] ]
A value learning system has incentives to follow shutdown instructions, assuming the shutdown instruction provides information (in the technical sense) about which actions lead to valuable outcomes. However, this assumption is not robust to model mis-specification (e.g., in the case of programmer errors). We demonstrat...
1404.7006
Erik Jan van Leeuwen
Karl Bringmann and Danny Hermelin and Matthias Mnich and Erik Jan van Leeuwen
Parameterized Complexity Dichotomy for Steiner Multicut
As submitted to journal. This version also adds a proof of fixed-parameter tractability for parameter k+t using the technique of randomized contractions
null
null
null
cs.DS cs.DM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The Steiner Multicut problem asks, given an undirected graph G, terminals sets T1,...,Tt $\subseteq$ V(G) of size at most p, and an integer k, whether there is a set S of at most k edges or nodes s.t. of each set Ti at least one pair of terminals is in different connected components of G \ S. This problem generalizes...
[ { "created": "Mon, 28 Apr 2014 14:41:40 GMT", "version": "v1" }, { "created": "Tue, 23 Jun 2015 14:00:38 GMT", "version": "v2" } ]
2015-06-24
[ [ "Bringmann", "Karl", "" ], [ "Hermelin", "Danny", "" ], [ "Mnich", "Matthias", "" ], [ "van Leeuwen", "Erik Jan", "" ] ]
The Steiner Multicut problem asks, given an undirected graph G, terminals sets T1,...,Tt $\subseteq$ V(G) of size at most p, and an integer k, whether there is a set S of at most k edges or nodes s.t. of each set Ti at least one pair of terminals is in different connected components of G \ S. This problem generalizes s...
2009.10855
Y-Lan Boureau
Eric Michael Smith, Diana Gonzalez-Rico, Emily Dinan, Y-Lan Boureau
Controlling Style in Generated Dialogue
null
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Open-domain conversation models have become good at generating natural-sounding dialogue, using very large architectures with billions of trainable parameters. The vast training data required to train these architectures aggregates many different styles, tones, and qualities. Using that data to train a single model m...
[ { "created": "Tue, 22 Sep 2020 23:21:04 GMT", "version": "v1" } ]
2020-09-24
[ [ "Smith", "Eric Michael", "" ], [ "Gonzalez-Rico", "Diana", "" ], [ "Dinan", "Emily", "" ], [ "Boureau", "Y-Lan", "" ] ]
Open-domain conversation models have become good at generating natural-sounding dialogue, using very large architectures with billions of trainable parameters. The vast training data required to train these architectures aggregates many different styles, tones, and qualities. Using that data to train a single model mak...
1711.11386
Kerem Can Tezcan
Kerem C. Tezcan, Christian F. Baumgartner, Roger Luechinger, Klaas P. Pruessmann, Ender Konukoglu
MR image reconstruction using deep density priors
Published in IEEE TMI. Main text and supplementary material, 19 pages total
IEEE Transactions on Medical Imaging, December 2018
10.1109/TMI.2018.2887072
null
cs.CV eess.IV stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Algorithms for Magnetic Resonance (MR) image reconstruction from undersampled measurements exploit prior information to compensate for missing k-space data. Deep learning (DL) provides a powerful framework for extracting such information from existing image datasets, through learning, and then using it for reconstruc...
[ { "created": "Thu, 30 Nov 2017 13:36:58 GMT", "version": "v1" }, { "created": "Fri, 1 Dec 2017 10:34:44 GMT", "version": "v2" }, { "created": "Wed, 17 Jan 2018 13:42:41 GMT", "version": "v3" }, { "created": "Wed, 19 Dec 2018 18:00:04 GMT", "version": "v4" } ]
2018-12-20
[ [ "Tezcan", "Kerem C.", "" ], [ "Baumgartner", "Christian F.", "" ], [ "Luechinger", "Roger", "" ], [ "Pruessmann", "Klaas P.", "" ], [ "Konukoglu", "Ender", "" ] ]
Algorithms for Magnetic Resonance (MR) image reconstruction from undersampled measurements exploit prior information to compensate for missing k-space data. Deep learning (DL) provides a powerful framework for extracting such information from existing image datasets, through learning, and then using it for reconstructi...
1910.14578
Minh-Tan Pham
Minh-Tan Pham, S\'ebastien Lef\`evre
Very high resolution Airborne PolSAR Image Classification using Convolutional Neural Networks
5 pages, accepted in EUSAR 2020
null
null
null
cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this work, we exploit convolutional neural networks (CNNs) for the classification of very high resolution (VHR) polarimetric SAR (PolSAR) data. Due to the significant appearance of heterogeneous textures within these data, not only polarimetric features but also structural tensors are exploited to feed CNN models....
[ { "created": "Thu, 31 Oct 2019 16:32:10 GMT", "version": "v1" }, { "created": "Thu, 9 Apr 2020 21:13:23 GMT", "version": "v2" } ]
2020-04-13
[ [ "Pham", "Minh-Tan", "" ], [ "Lefèvre", "Sébastien", "" ] ]
In this work, we exploit convolutional neural networks (CNNs) for the classification of very high resolution (VHR) polarimetric SAR (PolSAR) data. Due to the significant appearance of heterogeneous textures within these data, not only polarimetric features but also structural tensors are exploited to feed CNN models. F...
2305.08125
Niclas Boehmer
Niclas Boehmer, Piotr Faliszewski, {\L}ukasz Janeczko, Andrzej Kaczmarczyk
Robustness of Participatory Budgeting Outcomes: Complexity and Experiments
null
null
null
null
cs.GT econ.TH
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We study the robustness of approval-based participatory budgeting (PB) rules to random noise in the votes. Our contributions are twofold. First, we study the computational complexity of the #Flip-Bribery problem, where given a PB instance we ask for the number of ways in which we can flip a given number of approvals ...
[ { "created": "Sun, 14 May 2023 11:08:10 GMT", "version": "v1" } ]
2023-05-16
[ [ "Boehmer", "Niclas", "" ], [ "Faliszewski", "Piotr", "" ], [ "Janeczko", "Łukasz", "" ], [ "Kaczmarczyk", "Andrzej", "" ] ]
We study the robustness of approval-based participatory budgeting (PB) rules to random noise in the votes. Our contributions are twofold. First, we study the computational complexity of the #Flip-Bribery problem, where given a PB instance we ask for the number of ways in which we can flip a given number of approvals in...
2310.18845
Rita Garcia
Rita Garcia, Christoph Treude, Andrew Valentine
Application of Collaborative Learning Paradigms within Software Engineering Education: A Systematic Mapping Study
7 pages
null
10.1145/3626252.3630780
null
cs.SE
http://creativecommons.org/licenses/by-sa/4.0/
Collaboration is used in Software Engineering (SE) to develop software. Industry seeks SE graduates with collaboration skills to contribute to productive software development. SE educators can use Collaborative Learning (CL) to help students develop collaboration skills. This paper uses a Systematic Mapping Study (SM...
[ { "created": "Sat, 28 Oct 2023 23:16:38 GMT", "version": "v1" } ]
2023-10-31
[ [ "Garcia", "Rita", "" ], [ "Treude", "Christoph", "" ], [ "Valentine", "Andrew", "" ] ]
Collaboration is used in Software Engineering (SE) to develop software. Industry seeks SE graduates with collaboration skills to contribute to productive software development. SE educators can use Collaborative Learning (CL) to help students develop collaboration skills. This paper uses a Systematic Mapping Study (SMS)...
1509.00379
Benjamin Niedermann
Lukas Barth, Andreas Gemsa, Benjamin Niedermann, Martin N\"ollenburg
On the Readability of Boundary Labeling
Full version of GD 2015 paper
null
null
null
cs.CG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Boundary labeling deals with annotating features in images such that labels are placed outside of the image and are connected by curves (so-called leaders) to the corresponding features. While boundary labeling has been extensively investigated from an algorithmic perspective, the research on its readability has been...
[ { "created": "Tue, 1 Sep 2015 16:24:26 GMT", "version": "v1" } ]
2015-09-02
[ [ "Barth", "Lukas", "" ], [ "Gemsa", "Andreas", "" ], [ "Niedermann", "Benjamin", "" ], [ "Nöllenburg", "Martin", "" ] ]
Boundary labeling deals with annotating features in images such that labels are placed outside of the image and are connected by curves (so-called leaders) to the corresponding features. While boundary labeling has been extensively investigated from an algorithmic perspective, the research on its readability has been n...
2106.08848
Zhengzheng Tang
Zhengzheng Tang, Ziyue Qiao, Xuehai Hong, Yang Wang, Fayaz Ali Dharejo, Yuanchun Zhou, Yi Du
Data Augmentation for Graph Convolutional Network on Semi-Supervised Classification
16 pages, 6 figures,APWeb-WAIM 2021: The 5th APWeb-WAIM International Joint Conference on Web and Big Data
null
null
null
cs.LG cs.SI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Data augmentation aims to generate new and synthetic features from the original data, which can identify a better representation of data and improve the performance and generalizability of downstream tasks. However, data augmentation for graph-based models remains a challenging problem, as graph data is more complex ...
[ { "created": "Wed, 16 Jun 2021 15:13:51 GMT", "version": "v1" } ]
2021-06-17
[ [ "Tang", "Zhengzheng", "" ], [ "Qiao", "Ziyue", "" ], [ "Hong", "Xuehai", "" ], [ "Wang", "Yang", "" ], [ "Dharejo", "Fayaz Ali", "" ], [ "Zhou", "Yuanchun", "" ], [ "Du", "Yi", "" ] ]
Data augmentation aims to generate new and synthetic features from the original data, which can identify a better representation of data and improve the performance and generalizability of downstream tasks. However, data augmentation for graph-based models remains a challenging problem, as graph data is more complex th...
1903.09616
Xinshuo Weng
Xinshuo Weng
On the Importance of Video Action Recognition for Visual Lipreading
This paper is withdrawn by the author due to errors and there will be no replacement in this thread
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We focus on the word-level visual lipreading, which requires to decode the word from the speaker's video. Recently, many state-of-the-art visual lipreading methods explore the end-to-end trainable deep models, involving the use of 2D convolutional networks (e.g., ResNet) as the front-end visual feature extractor and ...
[ { "created": "Fri, 22 Mar 2019 17:24:37 GMT", "version": "v1" }, { "created": "Mon, 16 Sep 2019 15:32:15 GMT", "version": "v2" } ]
2019-09-17
[ [ "Weng", "Xinshuo", "" ] ]
We focus on the word-level visual lipreading, which requires to decode the word from the speaker's video. Recently, many state-of-the-art visual lipreading methods explore the end-to-end trainable deep models, involving the use of 2D convolutional networks (e.g., ResNet) as the front-end visual feature extractor and th...
1111.6191
Albrecht Zimmermann
Bj\"orn Bringmann and Siegfried Nijssen and Albrecht Zimmermann
Pattern-Based Classification: A Unifying Perspective
null
null
null
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The use of patterns in predictive models is a topic that has received a lot of attention in recent years. Pattern mining can help to obtain models for structured domains, such as graphs and sequences, and has been proposed as a means to obtain more accurate and more interpretable models. Despite the large amount of p...
[ { "created": "Sat, 26 Nov 2011 20:11:56 GMT", "version": "v1" } ]
2011-11-29
[ [ "Bringmann", "Björn", "" ], [ "Nijssen", "Siegfried", "" ], [ "Zimmermann", "Albrecht", "" ] ]
The use of patterns in predictive models is a topic that has received a lot of attention in recent years. Pattern mining can help to obtain models for structured domains, such as graphs and sequences, and has been proposed as a means to obtain more accurate and more interpretable models. Despite the large amount of pub...
2312.06638
Lev Utkin
Lev V. Utkin, Danila Y. Eremenko, Andrei V. Konstantinov
SurvBeNIM: The Beran-Based Neural Importance Model for Explaining the Survival Models
null
null
null
null
cs.LG cs.AI stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A new method called the Survival Beran-based Neural Importance Model (SurvBeNIM) is proposed. It aims to explain predictions of machine learning survival models, which are in the form of survival or cumulative hazard functions. The main idea behind SurvBeNIM is to extend the Beran estimator by incorporating the impor...
[ { "created": "Mon, 11 Dec 2023 18:54:26 GMT", "version": "v1" } ]
2023-12-12
[ [ "Utkin", "Lev V.", "" ], [ "Eremenko", "Danila Y.", "" ], [ "Konstantinov", "Andrei V.", "" ] ]
A new method called the Survival Beran-based Neural Importance Model (SurvBeNIM) is proposed. It aims to explain predictions of machine learning survival models, which are in the form of survival or cumulative hazard functions. The main idea behind SurvBeNIM is to extend the Beran estimator by incorporating the importa...
1702.02184
Ramkumar Natarajan
Sri Ramana Sekharan, Ramkumar Natarajan, Siddharthan Rajasekaran
Transfer from Multiple Linear Predictive State Representations (PSR)
8 pages, 3 algorithms, 3 figures
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we tackle the problem of transferring policy from multiple partially observable source environments to a partially observable target environment modeled as predictive state representation. This is an entirely new approach with no previous work, other than the case of transfer in fully observable domain...
[ { "created": "Tue, 7 Feb 2017 20:14:30 GMT", "version": "v1" } ]
2017-02-09
[ [ "Sekharan", "Sri Ramana", "" ], [ "Natarajan", "Ramkumar", "" ], [ "Rajasekaran", "Siddharthan", "" ] ]
In this paper, we tackle the problem of transferring policy from multiple partially observable source environments to a partially observable target environment modeled as predictive state representation. This is an entirely new approach with no previous work, other than the case of transfer in fully observable domains....
1511.04901
Erjin Zhou
Zhiao Huang, Erjin Zhou, Zhimin Cao
Coarse-to-fine Face Alignment with Multi-Scale Local Patch Regression
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Facial landmark localization plays an important role in face recognition and analysis applications. In this paper, we give a brief introduction to a coarse-to-fine pipeline with neural networks and sequential regression. First, a global convolutional network is applied to the holistic facial image to give an initial ...
[ { "created": "Mon, 16 Nov 2015 10:31:18 GMT", "version": "v1" } ]
2015-11-17
[ [ "Huang", "Zhiao", "" ], [ "Zhou", "Erjin", "" ], [ "Cao", "Zhimin", "" ] ]
Facial landmark localization plays an important role in face recognition and analysis applications. In this paper, we give a brief introduction to a coarse-to-fine pipeline with neural networks and sequential regression. First, a global convolutional network is applied to the holistic facial image to give an initial la...
1906.02944
Han-Jia Ye
Han-Jia Ye, Hexiang Hu, De-Chuan Zhan
Learning Adaptive Classifiers Synthesis for Generalized Few-Shot Learning
Accepted by IJCV; The code is available at https://github.com/Sha-Lab/aCASTLE
null
null
null
cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Object recognition in the real-world requires handling long-tailed or even open-ended data. An ideal visual system needs to recognize the populated head visual concepts reliably and meanwhile efficiently learn about emerging new tail categories with a few training instances. Class-balanced many-shot learning and few-...
[ { "created": "Fri, 7 Jun 2019 08:07:05 GMT", "version": "v1" }, { "created": "Sat, 28 Sep 2019 06:27:48 GMT", "version": "v2" }, { "created": "Sun, 29 Dec 2019 02:39:02 GMT", "version": "v3" }, { "created": "Wed, 28 Oct 2020 04:34:30 GMT", "version": "v4" }, { "cr...
2021-06-29
[ [ "Ye", "Han-Jia", "" ], [ "Hu", "Hexiang", "" ], [ "Zhan", "De-Chuan", "" ] ]
Object recognition in the real-world requires handling long-tailed or even open-ended data. An ideal visual system needs to recognize the populated head visual concepts reliably and meanwhile efficiently learn about emerging new tail categories with a few training instances. Class-balanced many-shot learning and few-sh...
2309.01115
Xiaoxue Wang
Xuanming Zhang, Xiaoxue Wang, Yonghang Chen
Multicollinearity Resolution Based on Machine Learning: A Case Study of Carbon Emissions in Sichuan Province
21 pages,19 figures
null
null
null
cs.LG
http://creativecommons.org/licenses/by-nc-sa/4.0/
This study preprocessed 2000-2019 energy consumption data for 46 key Sichuan industries using matrix normalization. DBSCAN clustering identified 16 feature classes to objectively group industries. Penalized regression models were then applied for their advantages in overfitting control, high-dimensional data processi...
[ { "created": "Sun, 3 Sep 2023 08:08:59 GMT", "version": "v1" }, { "created": "Sat, 20 Jan 2024 12:29:57 GMT", "version": "v2" } ]
2024-01-23
[ [ "Zhang", "Xuanming", "" ], [ "Wang", "Xiaoxue", "" ], [ "Chen", "Yonghang", "" ] ]
This study preprocessed 2000-2019 energy consumption data for 46 key Sichuan industries using matrix normalization. DBSCAN clustering identified 16 feature classes to objectively group industries. Penalized regression models were then applied for their advantages in overfitting control, high-dimensional data processing...
2103.12334
Zhiyuan Wang
Zhiyuan Wang and Lin Gao and Jianwei Huang
Taming Time-Varying Information Asymmetry in Fresh Status Acquisition
null
IEEE INFOCOM 2021
null
null
cs.GT
http://creativecommons.org/licenses/by/4.0/
Many online platforms are providing valuable real-time contents (e.g., traffic) by continuously acquiring the status of different Points of Interest (PoIs). In status acquisition, it is challenging to determine how frequently a PoI should upload its status to a platform, since they are self-interested with private an...
[ { "created": "Tue, 23 Mar 2021 06:09:53 GMT", "version": "v1" }, { "created": "Mon, 29 Mar 2021 11:25:21 GMT", "version": "v2" } ]
2021-03-30
[ [ "Wang", "Zhiyuan", "" ], [ "Gao", "Lin", "" ], [ "Huang", "Jianwei", "" ] ]
Many online platforms are providing valuable real-time contents (e.g., traffic) by continuously acquiring the status of different Points of Interest (PoIs). In status acquisition, it is challenging to determine how frequently a PoI should upload its status to a platform, since they are self-interested with private and ...
1910.13011
Pedro Ribeiro
Pedro Ribeiro, Pedro Paredes, Miguel E.P. Silva, David Aparicio, Fernando Silva
A Survey on Subgraph Counting: Concepts, Algorithms and Applications to Network Motifs and Graphlets
35 pages
ACM Computing Surveys, Volume 54, Issue 2, March 2022 ,Article No 28, pp 1-36
10.1145/3433652
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Computing subgraph frequencies is a fundamental task that lies at the core of several network analysis methodologies, such as network motifs and graphlet-based metrics, which have been widely used to categorize and compare networks from multiple domains. Counting subgraphs is however computationally very expensive an...
[ { "created": "Tue, 29 Oct 2019 00:01:24 GMT", "version": "v1" } ]
2021-12-30
[ [ "Ribeiro", "Pedro", "" ], [ "Paredes", "Pedro", "" ], [ "Silva", "Miguel E. P.", "" ], [ "Aparicio", "David", "" ], [ "Silva", "Fernando", "" ] ]
Computing subgraph frequencies is a fundamental task that lies at the core of several network analysis methodologies, such as network motifs and graphlet-based metrics, which have been widely used to categorize and compare networks from multiple domains. Counting subgraphs is however computationally very expensive and ...
2310.06670
Masih Aminbeidokhti
Masih Aminbeidokhti, Fidel A. Guerrero Pe\~na, Heitor Rapela Medeiros, Thomas Dubail, Eric Granger, Marco Pedersoli
Domain Generalization by Rejecting Extreme Augmentations
null
null
null
null
cs.LG cs.CV
http://creativecommons.org/licenses/by/4.0/
Data augmentation is one of the most effective techniques for regularizing deep learning models and improving their recognition performance in a variety of tasks and domains. However, this holds for standard in-domain settings, in which the training and test data follow the same distribution. For the out-of-domain ca...
[ { "created": "Tue, 10 Oct 2023 14:46:22 GMT", "version": "v1" } ]
2023-10-11
[ [ "Aminbeidokhti", "Masih", "" ], [ "Peña", "Fidel A. Guerrero", "" ], [ "Medeiros", "Heitor Rapela", "" ], [ "Dubail", "Thomas", "" ], [ "Granger", "Eric", "" ], [ "Pedersoli", "Marco", "" ] ]
Data augmentation is one of the most effective techniques for regularizing deep learning models and improving their recognition performance in a variety of tasks and domains. However, this holds for standard in-domain settings, in which the training and test data follow the same distribution. For the out-of-domain case...
2112.03458
Rong Zhu
Rong Zhu, Tianjing Zeng, Andreas Pfadler, Wei Chen, Bolin Ding, Jingren Zhou
Glue: Adaptively Merging Single Table Cardinality to Estimate Join Query Size
null
null
null
null
cs.DB cs.AI
http://creativecommons.org/licenses/by/4.0/
Cardinality estimation (CardEst), a central component of the query optimizer, plays a significant role in generating high-quality query plans in DBMS. The CardEst problem has been extensively studied in the last several decades, using both traditional and ML-enhanced methods. Whereas, the hardest problem in CardEst, ...
[ { "created": "Tue, 7 Dec 2021 02:46:46 GMT", "version": "v1" } ]
2021-12-08
[ [ "Zhu", "Rong", "" ], [ "Zeng", "Tianjing", "" ], [ "Pfadler", "Andreas", "" ], [ "Chen", "Wei", "" ], [ "Ding", "Bolin", "" ], [ "Zhou", "Jingren", "" ] ]
Cardinality estimation (CardEst), a central component of the query optimizer, plays a significant role in generating high-quality query plans in DBMS. The CardEst problem has been extensively studied in the last several decades, using both traditional and ML-enhanced methods. Whereas, the hardest problem in CardEst, i....
2310.07061
He Zhang
He Zhang, Chuhao Wu, Jingyi Xie, ChanMin Kim, John M. Carroll
QualiGPT: GPT as an easy-to-use tool for qualitative coding
25 pages, 7 figures, 1 table, under review
null
null
null
cs.HC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Qualitative research delves deeply into individual complex perspectives on technology and various phenomena. However, a meticulous analysis of qualitative data often requires a significant amount of time, especially during the crucial coding stage. Although there is software specifically designed for qualitative eval...
[ { "created": "Tue, 10 Oct 2023 22:57:18 GMT", "version": "v1" } ]
2023-10-12
[ [ "Zhang", "He", "" ], [ "Wu", "Chuhao", "" ], [ "Xie", "Jingyi", "" ], [ "Kim", "ChanMin", "" ], [ "Carroll", "John M.", "" ] ]
Qualitative research delves deeply into individual complex perspectives on technology and various phenomena. However, a meticulous analysis of qualitative data often requires a significant amount of time, especially during the crucial coding stage. Although there is software specifically designed for qualitative evalua...
2306.09008
Zhentao Tan
Zhentao Tan, Yue Wu, Qiankun Liu, Qi Chu, Le Lu, Jieping Ye, Nenghai Yu
Exploring the Application of Large-scale Pre-trained Models on Adverse Weather Removal
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Image restoration under adverse weather conditions (e.g., rain, snow and haze) is a fundamental computer vision problem and has important indications for various downstream applications. Different from early methods that are specially designed for specific type of weather, most recent works tend to remove various adv...
[ { "created": "Thu, 15 Jun 2023 10:06:13 GMT", "version": "v1" } ]
2023-06-16
[ [ "Tan", "Zhentao", "" ], [ "Wu", "Yue", "" ], [ "Liu", "Qiankun", "" ], [ "Chu", "Qi", "" ], [ "Lu", "Le", "" ], [ "Ye", "Jieping", "" ], [ "Yu", "Nenghai", "" ] ]
Image restoration under adverse weather conditions (e.g., rain, snow and haze) is a fundamental computer vision problem and has important indications for various downstream applications. Different from early methods that are specially designed for specific type of weather, most recent works tend to remove various adver...
1901.09837
Hassam Sheikh
Hassam Ullah Sheikh, Ladislau B\"ol\"oni
Designing a Multi-Objective Reward Function for Creating Teams of Robotic Bodyguards Using Deep Reinforcement Learning
Accepted at the 1st Workshop on Goal Specifications for Reinforcement Learning at ICML 2018
null
null
null
cs.MA cs.LG
http://creativecommons.org/licenses/by/4.0/
We are considering a scenario where a team of bodyguard robots provides physical protection to a VIP in a crowded public space. We use deep reinforcement learning to learn the policy to be followed by the robots. As the robot bodyguards need to follow several difficult-to-reconcile goals, we study several primitive a...
[ { "created": "Mon, 28 Jan 2019 17:33:45 GMT", "version": "v1" } ]
2019-01-29
[ [ "Sheikh", "Hassam Ullah", "" ], [ "Bölöni", "Ladislau", "" ] ]
We are considering a scenario where a team of bodyguard robots provides physical protection to a VIP in a crowded public space. We use deep reinforcement learning to learn the policy to be followed by the robots. As the robot bodyguards need to follow several difficult-to-reconcile goals, we study several primitive and...
2311.08835
WonJun Moon
WonJun Moon, Sangeek Hyun, SuBeen Lee, Jae-Pil Heo
Correlation-Guided Query-Dependency Calibration for Video Temporal Grounding
29 pages, 15 figures, 14 tables, Code is available at https://github.com/wjun0830/CGDETR
null
null
null
cs.CV
http://creativecommons.org/licenses/by-sa/4.0/
Temporal Grounding is to identify specific moments or highlights from a video corresponding to textual descriptions. Typical approaches in temporal grounding treat all video clips equally during the encoding process regardless of their semantic relevance with the text query. Therefore, we propose Correlation-Guided D...
[ { "created": "Wed, 15 Nov 2023 10:22:35 GMT", "version": "v1" }, { "created": "Sat, 18 Nov 2023 15:51:20 GMT", "version": "v2" }, { "created": "Sat, 30 Mar 2024 11:01:17 GMT", "version": "v3" }, { "created": "Wed, 3 Jul 2024 18:05:02 GMT", "version": "v4" } ]
2024-07-08
[ [ "Moon", "WonJun", "" ], [ "Hyun", "Sangeek", "" ], [ "Lee", "SuBeen", "" ], [ "Heo", "Jae-Pil", "" ] ]
Temporal Grounding is to identify specific moments or highlights from a video corresponding to textual descriptions. Typical approaches in temporal grounding treat all video clips equally during the encoding process regardless of their semantic relevance with the text query. Therefore, we propose Correlation-Guided DEt...
2307.07440
Emily Fox
Emily Fox
A simple deterministic near-linear time approximation scheme for transshipment with arbitrary positive edge costs
Accepted for ESA 2024 v3: ESA 2024 reviewer suggestions
null
null
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We describe a simple deterministic near-linear time approximation scheme for uncapacitated minimum cost flow in undirected graphs with real edge weights, a problem also known as transshipment. Specifically, our algorithm takes as input a (connected) undirected graph $G = (V, E)$, vertex demands $b \in \mathbb{R}^V$ s...
[ { "created": "Fri, 14 Jul 2023 16:04:14 GMT", "version": "v1" }, { "created": "Tue, 23 Apr 2024 20:23:00 GMT", "version": "v2" }, { "created": "Wed, 26 Jun 2024 16:37:40 GMT", "version": "v3" } ]
2024-06-27
[ [ "Fox", "Emily", "" ] ]
We describe a simple deterministic near-linear time approximation scheme for uncapacitated minimum cost flow in undirected graphs with real edge weights, a problem also known as transshipment. Specifically, our algorithm takes as input a (connected) undirected graph $G = (V, E)$, vertex demands $b \in \mathbb{R}^V$ suc...
2203.01769
Miao Li
Miao Li, Jianzhong Qi, Jey Han Lau
PeerSum: A Peer Review Dataset for Abstractive Multi-document Summarization
This is because the paper has changed so much and the arxiv paper no longer represents the PeerSum
null
null
null
cs.IR cs.CL
http://creativecommons.org/licenses/by/4.0/
We present PeerSum, a new MDS dataset using peer reviews of scientific publications. Our dataset differs from the existing MDS datasets in that our summaries (i.e., the meta-reviews) are highly abstractive and they are real summaries of the source documents (i.e., the reviews) and it also features disagreements among...
[ { "created": "Thu, 3 Mar 2022 15:27:02 GMT", "version": "v1" }, { "created": "Thu, 29 Sep 2022 01:14:20 GMT", "version": "v2" } ]
2022-09-30
[ [ "Li", "Miao", "" ], [ "Qi", "Jianzhong", "" ], [ "Lau", "Jey Han", "" ] ]
We present PeerSum, a new MDS dataset using peer reviews of scientific publications. Our dataset differs from the existing MDS datasets in that our summaries (i.e., the meta-reviews) are highly abstractive and they are real summaries of the source documents (i.e., the reviews) and it also features disagreements among s...
2210.07522
Praveen Ravirathinam
Praveen Ravirathinam, Rahul Ghosh, Ke Wang, Keyang Xuan, Ankush Khandelwal, Hilary Dugan, Paul Hanson, Vipin Kumar
Spatiotemporal Classification with limited labels using Constrained Clustering for large datasets
9 pages
null
null
null
cs.LG
http://creativecommons.org/licenses/by/4.0/
Creating separable representations via representation learning and clustering is critical in analyzing large unstructured datasets with only a few labels. Separable representations can lead to supervised models with better classification capabilities and additionally aid in generating new labeled samples. Most unsupe...
[ { "created": "Fri, 14 Oct 2022 05:05:22 GMT", "version": "v1" } ]
2022-10-17
[ [ "Ravirathinam", "Praveen", "" ], [ "Ghosh", "Rahul", "" ], [ "Wang", "Ke", "" ], [ "Xuan", "Keyang", "" ], [ "Khandelwal", "Ankush", "" ], [ "Dugan", "Hilary", "" ], [ "Hanson", "Paul", "" ], [ "Kum...
Creating separable representations via representation learning and clustering is critical in analyzing large unstructured datasets with only a few labels. Separable representations can lead to supervised models with better classification capabilities and additionally aid in generating new labeled samples. Most unsuperv...
0704.2680
Tobias Koch
Tobias Koch, Amos Lapidoth and Paul P. Sotiriadis
A Channel that Heats Up
to appear in Proceedings of the 2007 IEEE International Symposium on Information Theory (ISIT), Nice, France
null
null
null
cs.IT math.IT
null
Motivated by on-chip communication, a channel model is proposed where the variance of the additive noise depends on the weighted sum of the past channel input powers. For this channel, an expression for the capacity per unit cost is derived, and it is shown that the expression holds also in the presence of feedback.
[ { "created": "Fri, 20 Apr 2007 10:26:53 GMT", "version": "v1" } ]
2007-07-13
[ [ "Koch", "Tobias", "" ], [ "Lapidoth", "Amos", "" ], [ "Sotiriadis", "Paul P.", "" ] ]
Motivated by on-chip communication, a channel model is proposed where the variance of the additive noise depends on the weighted sum of the past channel input powers. For this channel, an expression for the capacity per unit cost is derived, and it is shown that the expression holds also in the presence of feedback.
1504.00045
Yongxin Yang
Zhiyuan Shi, Yongxin Yang, Timothy M. Hospedales and Tao Xiang
Weakly Supervised Learning of Objects, Attributes and their Associations
14 pages, Accepted to ECCV 2014
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
When humans describe images they tend to use combinations of nouns and adjectives, corresponding to objects and their associated attributes respectively. To generate such a description automatically, one needs to model objects, attributes and their associations. Conventional methods require strong annotation of objec...
[ { "created": "Tue, 31 Mar 2015 21:18:18 GMT", "version": "v1" } ]
2015-04-02
[ [ "Shi", "Zhiyuan", "" ], [ "Yang", "Yongxin", "" ], [ "Hospedales", "Timothy M.", "" ], [ "Xiang", "Tao", "" ] ]
When humans describe images they tend to use combinations of nouns and adjectives, corresponding to objects and their associated attributes respectively. To generate such a description automatically, one needs to model objects, attributes and their associations. Conventional methods require strong annotation of object ...
2106.15998
Daniel Wiens
Daniel Wiens and Barbara Hammer
Single-Step Adversarial Training for Semantic Segmentation
null
null
null
null
cs.CV cs.LG eess.IV
http://creativecommons.org/licenses/by-nc-nd/4.0/
Even though deep neural networks succeed on many different tasks including semantic segmentation, they lack on robustness against adversarial examples. To counteract this exploit, often adversarial training is used. However, it is known that adversarial training with weak adversarial attacks (e.g. using the Fast Grad...
[ { "created": "Wed, 30 Jun 2021 11:41:09 GMT", "version": "v1" } ]
2021-07-01
[ [ "Wiens", "Daniel", "" ], [ "Hammer", "Barbara", "" ] ]
Even though deep neural networks succeed on many different tasks including semantic segmentation, they lack on robustness against adversarial examples. To counteract this exploit, often adversarial training is used. However, it is known that adversarial training with weak adversarial attacks (e.g. using the Fast Gradie...
1511.06522
Yan Zhang
Yan Zhang, Mete Ozay, Xing Liu, Takayuki Okatani
Integrating Deep Features for Material Recognition
6 pages
null
null
null
cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We propose a method for integration of features extracted using deep representations of Convolutional Neural Networks (CNNs) each of which is learned using a different image dataset of objects and materials for material recognition. Given a set of representations of multiple pre-trained CNNs, we first compute activat...
[ { "created": "Fri, 20 Nov 2015 08:31:00 GMT", "version": "v1" }, { "created": "Sat, 28 Nov 2015 14:21:28 GMT", "version": "v2" }, { "created": "Sun, 13 Dec 2015 13:39:24 GMT", "version": "v3" }, { "created": "Mon, 22 Feb 2016 14:36:36 GMT", "version": "v4" }, { "c...
2016-04-22
[ [ "Zhang", "Yan", "" ], [ "Ozay", "Mete", "" ], [ "Liu", "Xing", "" ], [ "Okatani", "Takayuki", "" ] ]
We propose a method for integration of features extracted using deep representations of Convolutional Neural Networks (CNNs) each of which is learned using a different image dataset of objects and materials for material recognition. Given a set of representations of multiple pre-trained CNNs, we first compute activatio...
2305.15353
Thiago S. Gouv\^ea
Hannes Kath, Bengt L\"uers, Thiago S. Gouv\^ea, Daniel Sonntag
A Virtual Reality Tool for Representing, Visualizing and Updating Deep Learning Models
null
null
null
null
cs.HC cs.LG
http://creativecommons.org/licenses/by-nc-sa/4.0/
Deep learning is ubiquitous, but its lack of transparency limits its impact on several potential application areas. We demonstrate a virtual reality tool for automating the process of assigning data inputs to different categories. A dataset is represented as a cloud of points in virtual space. The user explores the c...
[ { "created": "Wed, 24 May 2023 17:06:59 GMT", "version": "v1" } ]
2023-05-25
[ [ "Kath", "Hannes", "" ], [ "Lüers", "Bengt", "" ], [ "Gouvêa", "Thiago S.", "" ], [ "Sonntag", "Daniel", "" ] ]
Deep learning is ubiquitous, but its lack of transparency limits its impact on several potential application areas. We demonstrate a virtual reality tool for automating the process of assigning data inputs to different categories. A dataset is represented as a cloud of points in virtual space. The user explores the clo...
0908.0078
Abhik Das
Abhik Das, Shweta Agarwal and Sriram Vishwanath
On Algebraic Traceback in Dynamic Networks
9 pages, 4 figures
null
null
null
cs.IT cs.NI math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper introduces the concept of incremental traceback for determining changes in the trace of a network as it evolves with time. A distributed algorithm, based on the methodology of algebraic traceback developed by Dean et al, is proposed which can completely determine a path of d nodes/routers using O(d) marked...
[ { "created": "Sat, 1 Aug 2009 13:45:17 GMT", "version": "v1" }, { "created": "Tue, 11 Aug 2009 07:07:26 GMT", "version": "v2" }, { "created": "Wed, 20 Jan 2010 01:55:43 GMT", "version": "v3" } ]
2010-01-20
[ [ "Das", "Abhik", "" ], [ "Agarwal", "Shweta", "" ], [ "Vishwanath", "Sriram", "" ] ]
This paper introduces the concept of incremental traceback for determining changes in the trace of a network as it evolves with time. A distributed algorithm, based on the methodology of algebraic traceback developed by Dean et al, is proposed which can completely determine a path of d nodes/routers using O(d) marked p...
1408.1776
Radoslaw Klimek
Radoslaw Klimek, Leszek Kotulski
Context-awareness of the IoT through the on-the-fly preference modeling
null
null
null
null
cs.SE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The context-awareness of things that belong to IoT networks have to be considered in a distributed computation paradigm. In the paper we suggest the use of graph transformations and temporal logic as a formal framework for a knowledge representation of user/inhabitant behaviors in multi-agent systems. IoT networks ar...
[ { "created": "Fri, 8 Aug 2014 07:47:46 GMT", "version": "v1" } ]
2014-08-11
[ [ "Klimek", "Radoslaw", "" ], [ "Kotulski", "Leszek", "" ] ]
The context-awareness of things that belong to IoT networks have to be considered in a distributed computation paradigm. In the paper we suggest the use of graph transformations and temporal logic as a formal framework for a knowledge representation of user/inhabitant behaviors in multi-agent systems. IoT networks are ...
2112.09348
Omid Madani
Omid Madani
Expedition: A System for the Unsupervised Learning of a Hierarchy of Concepts
null
null
null
null
cs.LG cs.CL
http://creativecommons.org/licenses/by/4.0/
We present a system for bottom-up cumulative learning of myriad concepts corresponding to meaningful character strings, and their part-related and prediction edges. The learning is self-supervised in that the concepts discovered are used as predictors as well as targets of prediction. We devise an objective for segme...
[ { "created": "Fri, 17 Dec 2021 06:49:18 GMT", "version": "v1" } ]
2021-12-20
[ [ "Madani", "Omid", "" ] ]
We present a system for bottom-up cumulative learning of myriad concepts corresponding to meaningful character strings, and their part-related and prediction edges. The learning is self-supervised in that the concepts discovered are used as predictors as well as targets of prediction. We devise an objective for segment...
2206.05737
Xiaoxiao Long
Xiaoxiao Long, Cheng Lin, Peng Wang, Taku Komura, Wenping Wang
SparseNeuS: Fast Generalizable Neural Surface Reconstruction from Sparse Views
Project page: https://www.xxlong.site/SparseNeuS/
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
We introduce SparseNeuS, a novel neural rendering based method for the task of surface reconstruction from multi-view images. This task becomes more difficult when only sparse images are provided as input, a scenario where existing neural reconstruction approaches usually produce incomplete or distorted results. More...
[ { "created": "Sun, 12 Jun 2022 13:34:03 GMT", "version": "v1" }, { "created": "Tue, 2 Aug 2022 10:53:02 GMT", "version": "v2" } ]
2022-08-03
[ [ "Long", "Xiaoxiao", "" ], [ "Lin", "Cheng", "" ], [ "Wang", "Peng", "" ], [ "Komura", "Taku", "" ], [ "Wang", "Wenping", "" ] ]
We introduce SparseNeuS, a novel neural rendering based method for the task of surface reconstruction from multi-view images. This task becomes more difficult when only sparse images are provided as input, a scenario where existing neural reconstruction approaches usually produce incomplete or distorted results. Moreov...
1304.4557
Lionel Rieg
Lionel Rieg (LIP)
Extracting Herbrand trees from Coq
null
null
null
null
cs.LO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Software certification aims at proving the correctness of programs but in many cases, the use of external libraries allows only a conditional proof: it depends on the assumption that the libraries meet their specifications. In particular, a bug in these libraries might still impact the certified program. In this case...
[ { "created": "Tue, 16 Apr 2013 19:05:21 GMT", "version": "v1" } ]
2013-04-17
[ [ "Rieg", "Lionel", "", "LIP" ] ]
Software certification aims at proving the correctness of programs but in many cases, the use of external libraries allows only a conditional proof: it depends on the assumption that the libraries meet their specifications. In particular, a bug in these libraries might still impact the certified program. In this case, ...
1207.3976
Manoj Gupta
Abhash Anand and Surender Baswana and Manoj Gupta and Sandeep Sen
Maintaining Approximate Maximum Weighted Matching in Fully Dynamic Graphs
null
null
null
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present a fully dynamic algorithm for maintaining approximate maximum weight matching in general weighted graphs. The algorithm maintains a matching ${\cal M}$ whose weight is at least $1/8 M^{*}$ where $M^{*}$ is the weight of the maximum weight matching. The algorithm achieves an expected amortized $O(\log n \lo...
[ { "created": "Tue, 17 Jul 2012 12:51:55 GMT", "version": "v1" }, { "created": "Mon, 10 Dec 2012 17:01:03 GMT", "version": "v2" }, { "created": "Wed, 12 Dec 2012 07:09:40 GMT", "version": "v3" } ]
2012-12-13
[ [ "Anand", "Abhash", "" ], [ "Baswana", "Surender", "" ], [ "Gupta", "Manoj", "" ], [ "Sen", "Sandeep", "" ] ]
We present a fully dynamic algorithm for maintaining approximate maximum weight matching in general weighted graphs. The algorithm maintains a matching ${\cal M}$ whose weight is at least $1/8 M^{*}$ where $M^{*}$ is the weight of the maximum weight matching. The algorithm achieves an expected amortized $O(\log n \log ...
1608.00860
Jie Chen
Jie Chen, Haim Avron, Vikas Sindhwani
Hierarchically Compositional Kernels for Scalable Nonparametric Learning
Journal of Machine Learning Research, vol 18, 2017
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We propose a novel class of kernels to alleviate the high computational cost of large-scale nonparametric learning with kernel methods. The proposed kernel is defined based on a hierarchical partitioning of the underlying data domain, where the Nystr\"om method (a globally low-rank approximation) is married with a lo...
[ { "created": "Tue, 2 Aug 2016 15:07:25 GMT", "version": "v1" }, { "created": "Mon, 14 Aug 2017 15:11:25 GMT", "version": "v2" } ]
2017-08-15
[ [ "Chen", "Jie", "" ], [ "Avron", "Haim", "" ], [ "Sindhwani", "Vikas", "" ] ]
We propose a novel class of kernels to alleviate the high computational cost of large-scale nonparametric learning with kernel methods. The proposed kernel is defined based on a hierarchical partitioning of the underlying data domain, where the Nystr\"om method (a globally low-rank approximation) is married with a loca...
2306.03866
Jan Deriu
Jan Deriu, Pius von D\"aniken, Don Tuggener, Mark Cieliebak
Correction of Errors in Preference Ratings from Automated Metrics for Text Generation
null
null
null
null
cs.CL cs.AI
http://creativecommons.org/licenses/by/4.0/
A major challenge in the field of Text Generation is evaluation: Human evaluations are cost-intensive, and automated metrics often display considerable disagreement with human judgments. In this paper, we propose a statistical model of Text Generation evaluation that accounts for the error-proneness of automated metr...
[ { "created": "Tue, 6 Jun 2023 17:09:29 GMT", "version": "v1" } ]
2023-06-07
[ [ "Deriu", "Jan", "" ], [ "von Däniken", "Pius", "" ], [ "Tuggener", "Don", "" ], [ "Cieliebak", "Mark", "" ] ]
A major challenge in the field of Text Generation is evaluation: Human evaluations are cost-intensive, and automated metrics often display considerable disagreement with human judgments. In this paper, we propose a statistical model of Text Generation evaluation that accounts for the error-proneness of automated metric...
2406.16821
Yue Jian
Yue Jian, Curtis Wu, Danny Reidenbach, Aditi S. Krishnapriyan
General Binding Affinity Guidance for Diffusion Models in Structure-Based Drug Design
null
null
null
null
cs.LG cs.AI physics.bio-ph physics.chem-ph q-bio.BM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Structure-Based Drug Design (SBDD) focuses on generating valid ligands that strongly and specifically bind to a designated protein pocket. Several methods use machine learning for SBDD to generate these ligands in 3D space, conditioned on the structure of a desired protein pocket. Recently, diffusion models have show...
[ { "created": "Mon, 24 Jun 2024 17:31:41 GMT", "version": "v1" } ]
2024-06-25
[ [ "Jian", "Yue", "" ], [ "Wu", "Curtis", "" ], [ "Reidenbach", "Danny", "" ], [ "Krishnapriyan", "Aditi S.", "" ] ]
Structure-Based Drug Design (SBDD) focuses on generating valid ligands that strongly and specifically bind to a designated protein pocket. Several methods use machine learning for SBDD to generate these ligands in 3D space, conditioned on the structure of a desired protein pocket. Recently, diffusion models have shown ...
2112.02856
Wenjia Ba
Wenjia Ba, Tianyi Lin, Jiawei Zhang, Zhengyuan Zhou
Doubly Optimal No-Regret Online Learning in Strongly Monotone Games with Bandit Feedback
43 pages, 4 figures
null
null
null
cs.LG cs.GT math.OC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We consider online no-regret learning in unknown games with bandit feedback, where each player can only observe its reward at each time -- determined by all players' current joint action -- rather than its gradient. We focus on the class of \textit{smooth and strongly monotone} games and study optimal no-regret learn...
[ { "created": "Mon, 6 Dec 2021 08:27:54 GMT", "version": "v1" }, { "created": "Wed, 8 Dec 2021 02:06:50 GMT", "version": "v2" }, { "created": "Sun, 10 Jul 2022 01:29:19 GMT", "version": "v3" }, { "created": "Fri, 29 Mar 2024 04:18:14 GMT", "version": "v4" } ]
2024-04-01
[ [ "Ba", "Wenjia", "" ], [ "Lin", "Tianyi", "" ], [ "Zhang", "Jiawei", "" ], [ "Zhou", "Zhengyuan", "" ] ]
We consider online no-regret learning in unknown games with bandit feedback, where each player can only observe its reward at each time -- determined by all players' current joint action -- rather than its gradient. We focus on the class of \textit{smooth and strongly monotone} games and study optimal no-regret learnin...
2112.12318
Michael Sun
Michael Sun, Kaili Huang, and Mehrad Moradshahi
Investigating Effect of Dialogue History in Multilingual Task Oriented Dialogue Systems
null
null
null
null
cs.CL cs.AI
http://creativecommons.org/licenses/by/4.0/
While the English virtual assistants have achieved exciting performance with an enormous amount of training resources, the needs of non-English-speakers have not been satisfied well. Up to Dec 2021, Alexa, one of the most popular smart speakers around the world, is able to support 9 different languages [1], while the...
[ { "created": "Thu, 23 Dec 2021 02:27:10 GMT", "version": "v1" } ]
2021-12-24
[ [ "Sun", "Michael", "" ], [ "Huang", "Kaili", "" ], [ "Moradshahi", "Mehrad", "" ] ]
While the English virtual assistants have achieved exciting performance with an enormous amount of training resources, the needs of non-English-speakers have not been satisfied well. Up to Dec 2021, Alexa, one of the most popular smart speakers around the world, is able to support 9 different languages [1], while there...
2408.00137
Sangwon Yu
Sangwon Yu, Jongyoon Song, Bongkyu Hwang, Hoyoung Kang, Sooah Cho, Junhwa Choi, Seongho Joe, Taehee Lee, Youngjune L. Gwon, Sungroh Yoon
Correcting Negative Bias in Large Language Models through Negative Attention Score Alignment
null
null
null
null
cs.CL cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A binary decision task, like yes-no questions or answer verification, reflects a significant real-world scenario such as where users look for confirmation about the correctness of their decisions on specific issues. In this work, we observe that language models exhibit a negative bias in the binary decisions of compl...
[ { "created": "Wed, 31 Jul 2024 19:50:57 GMT", "version": "v1" } ]
2024-08-02
[ [ "Yu", "Sangwon", "" ], [ "Song", "Jongyoon", "" ], [ "Hwang", "Bongkyu", "" ], [ "Kang", "Hoyoung", "" ], [ "Cho", "Sooah", "" ], [ "Choi", "Junhwa", "" ], [ "Joe", "Seongho", "" ], [ "Lee", "Ta...
A binary decision task, like yes-no questions or answer verification, reflects a significant real-world scenario such as where users look for confirmation about the correctness of their decisions on specific issues. In this work, we observe that language models exhibit a negative bias in the binary decisions of complex...
1201.3881
Alain-J\'er\^ome Foug\`eres
Alain-J\'er\^ome Foug\`eres
Agent-Based {\mu}-Tools Integrated into a Co-Design Platform
10 pages; IJCSI International Journal of Computer Science Issues, Vol. 7, Issue 1, 2010
null
null
null
cs.HC cs.DC cs.MA
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper we present successively the proposition and the design of: 1) {\mu}-tools adapted to collaborative activity of design, and 2) a multi-agent platform adapted to innovative and distributed design of products or services. This platform called PLACID (innovating and distributed design platform) must support...
[ { "created": "Wed, 18 Jan 2012 19:08:23 GMT", "version": "v1" } ]
2012-01-19
[ [ "Fougères", "Alain-Jérôme", "" ] ]
In this paper we present successively the proposition and the design of: 1) {\mu}-tools adapted to collaborative activity of design, and 2) a multi-agent platform adapted to innovative and distributed design of products or services. This platform called PLACID (innovating and distributed design platform) must support a...
2309.00700
Sathvik Murli
Sathvik Murli, Dhruv Nandakumar, Prabhat Kumar Kushwaha, Cheng Wang, Christopher Redino, Abdul Rahman, Shalini Israni, Tarun Singh, Edward Bowen
Cross-temporal Detection of Novel Ransomware Campaigns: A Multi-Modal Alert Approach
Preprint. Under Review
null
null
null
cs.CR
http://creativecommons.org/licenses/by-nc-nd/4.0/
We present a novel approach to identify ransomware campaigns derived from attack timelines representations within victim networks. Malicious activity profiles developed from multiple alert sources support the construction of alert graphs. This approach enables an effective and scalable representation of the attack ti...
[ { "created": "Fri, 1 Sep 2023 18:46:00 GMT", "version": "v1" } ]
2023-09-06
[ [ "Murli", "Sathvik", "" ], [ "Nandakumar", "Dhruv", "" ], [ "Kushwaha", "Prabhat Kumar", "" ], [ "Wang", "Cheng", "" ], [ "Redino", "Christopher", "" ], [ "Rahman", "Abdul", "" ], [ "Israni", "Shalini", "" ...
We present a novel approach to identify ransomware campaigns derived from attack timelines representations within victim networks. Malicious activity profiles developed from multiple alert sources support the construction of alert graphs. This approach enables an effective and scalable representation of the attack time...
1905.09684
Ryo Yonetani
Ryo Yonetani, Tomohiro Takahashi, Atsushi Hashimoto, Yoshitaka Ushiku
Decentralized Learning of Generative Adversarial Networks from Non-iid Data
null
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This work addresses a new problem that learns generative adversarial networks (GANs) from multiple data collections that are each i) owned separately by different clients and ii) drawn from a non-identical distribution that comprises different classes. Given such non-iid data as input, we aim to learn a distribution ...
[ { "created": "Thu, 23 May 2019 14:41:54 GMT", "version": "v1" }, { "created": "Fri, 22 Nov 2019 02:04:11 GMT", "version": "v2" } ]
2019-11-25
[ [ "Yonetani", "Ryo", "" ], [ "Takahashi", "Tomohiro", "" ], [ "Hashimoto", "Atsushi", "" ], [ "Ushiku", "Yoshitaka", "" ] ]
This work addresses a new problem that learns generative adversarial networks (GANs) from multiple data collections that are each i) owned separately by different clients and ii) drawn from a non-identical distribution that comprises different classes. Given such non-iid data as input, we aim to learn a distribution in...
1602.07320
Zachary Lipton
Zachary C. Lipton
Stuck in a What? Adventures in Weight Space
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Deep learning researchers commonly suggest that converged models are stuck in local minima. More recently, some researchers observed that under reasonable assumptions, the vast majority of critical points are saddle points, not true minima. Both descriptions suggest that weights converge around a point in weight spac...
[ { "created": "Tue, 23 Feb 2016 21:23:24 GMT", "version": "v1" } ]
2016-02-25
[ [ "Lipton", "Zachary C.", "" ] ]
Deep learning researchers commonly suggest that converged models are stuck in local minima. More recently, some researchers observed that under reasonable assumptions, the vast majority of critical points are saddle points, not true minima. Both descriptions suggest that weights converge around a point in weight space,...
2304.11837
Yao Su
Yao Su, Pengkang Yu, Matthew J. Gerber, Lecheng Ruan, Tsu-Chin Tsao
Fault-tolerant Control of an Over-actuated UAV Platform Built on Quadcopters and Passive Hinges
null
null
null
null
cs.RO cs.SY eess.SY
http://creativecommons.org/licenses/by-nc-nd/4.0/
Propeller failure is a major cause of multirotor Unmanned Aerial Vehicles (UAVs) crashes. While conventional multirotor systems struggle to address this issue due to underactuation, over-actuated platforms can continue flying with appropriate fault-tolerant control (FTC). This paper presents a robust FTC controller f...
[ { "created": "Mon, 24 Apr 2023 06:05:24 GMT", "version": "v1" }, { "created": "Wed, 14 Jun 2023 05:47:32 GMT", "version": "v2" } ]
2023-06-16
[ [ "Su", "Yao", "" ], [ "Yu", "Pengkang", "" ], [ "Gerber", "Matthew J.", "" ], [ "Ruan", "Lecheng", "" ], [ "Tsao", "Tsu-Chin", "" ] ]
Propeller failure is a major cause of multirotor Unmanned Aerial Vehicles (UAVs) crashes. While conventional multirotor systems struggle to address this issue due to underactuation, over-actuated platforms can continue flying with appropriate fault-tolerant control (FTC). This paper presents a robust FTC controller for...
2107.04939
Mengyu Fu
Mengyu Fu, Oren Salzman, Ron Alterovitz
Toward Certifiable Motion Planning for Medical Steerable Needles
To be published in Robotics: Science and Systems (RSS) 2021
null
10.15607/RSS.2021.XVII.081
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Medical steerable needles can move along 3D curvilinear trajectories to avoid anatomical obstacles and reach clinically significant targets inside the human body. Automating steerable needle procedures can enable physicians and patients to harness the full potential of steerable needles by maximally leveraging their ...
[ { "created": "Sun, 11 Jul 2021 02:09:44 GMT", "version": "v1" } ]
2021-07-13
[ [ "Fu", "Mengyu", "" ], [ "Salzman", "Oren", "" ], [ "Alterovitz", "Ron", "" ] ]
Medical steerable needles can move along 3D curvilinear trajectories to avoid anatomical obstacles and reach clinically significant targets inside the human body. Automating steerable needle procedures can enable physicians and patients to harness the full potential of steerable needles by maximally leveraging their st...
2103.06381
Ranesh Kumar Naha
Ranesh Kumar Naha, Saurabh Garg, Muhammad Bilal Amin, and Rajiv Ranjan
Fuzzy Logic-based Robust Failure Handling Mechanism for Fog Computing
12 Pages,12 Figures
null
null
null
cs.DC
http://creativecommons.org/licenses/by/4.0/
Fog computing is an emerging computing paradigm which is mainly suitable for time-sensitive and real-time Internet of Things (IoT) applications. Academia and industries are focusing on the exploration of various aspects of Fog computing for market adoption. The key idea of the Fog computing paradigm is to use idle co...
[ { "created": "Wed, 10 Mar 2021 23:03:48 GMT", "version": "v1" } ]
2021-03-12
[ [ "Naha", "Ranesh Kumar", "" ], [ "Garg", "Saurabh", "" ], [ "Amin", "Muhammad Bilal", "" ], [ "Ranjan", "Rajiv", "" ] ]
Fog computing is an emerging computing paradigm which is mainly suitable for time-sensitive and real-time Internet of Things (IoT) applications. Academia and industries are focusing on the exploration of various aspects of Fog computing for market adoption. The key idea of the Fog computing paradigm is to use idle comp...
2209.08844
Curie Kim
Curie Kim and Ue-Hwan Kim
A Dual-Cycled Cross-View Transformer Network for Unified Road Layout Estimation and 3D Object Detection in the Bird's-Eye-View
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The bird's-eye-view (BEV) representation allows robust learning of multiple tasks for autonomous driving including road layout estimation and 3D object detection. However, contemporary methods for unified road layout estimation and 3D object detection rarely handle the class imbalance of the training dataset and mult...
[ { "created": "Mon, 19 Sep 2022 08:43:38 GMT", "version": "v1" } ]
2022-09-20
[ [ "Kim", "Curie", "" ], [ "Kim", "Ue-Hwan", "" ] ]
The bird's-eye-view (BEV) representation allows robust learning of multiple tasks for autonomous driving including road layout estimation and 3D object detection. However, contemporary methods for unified road layout estimation and 3D object detection rarely handle the class imbalance of the training dataset and multi-...
2307.13131
Luis Garcia
Yi Han, Matthew Chan, Eric Wengrowski, Zhuohuan Li, Nils Ole Tippenhauer, Mani Srivastava, Saman Zonouz, Luis Garcia
Why Don't You Clean Your Glasses? Perception Attacks with Dynamic Optical Perturbations
15 pages, 11 figures
null
null
null
cs.CR cs.AI
http://creativecommons.org/licenses/by/4.0/
Camera-based autonomous systems that emulate human perception are increasingly being integrated into safety-critical platforms. Consequently, an established body of literature has emerged that explores adversarial attacks targeting the underlying machine learning models. Adapting adversarial attacks to the physical w...
[ { "created": "Mon, 24 Jul 2023 21:16:38 GMT", "version": "v1" }, { "created": "Thu, 27 Jul 2023 21:58:03 GMT", "version": "v2" } ]
2023-07-31
[ [ "Han", "Yi", "" ], [ "Chan", "Matthew", "" ], [ "Wengrowski", "Eric", "" ], [ "Li", "Zhuohuan", "" ], [ "Tippenhauer", "Nils Ole", "" ], [ "Srivastava", "Mani", "" ], [ "Zonouz", "Saman", "" ], [ "G...
Camera-based autonomous systems that emulate human perception are increasingly being integrated into safety-critical platforms. Consequently, an established body of literature has emerged that explores adversarial attacks targeting the underlying machine learning models. Adapting adversarial attacks to the physical wor...
1612.05316
Jan Blech
Keith Foster, Jan Olaf Blech, Guillaume Prevost
Towards the Formalization of a Factory Demonstrator in BeSpaceD
null
null
null
null
cs.SE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This report gives an overview of our efforts towards a formalization for a food processing demonstrator plant. Our BeSpaceD framework is used for the formalization. The formalization comprises properties of components and relations between components. We present domain-specific constructs for the formalization of ind...
[ { "created": "Fri, 16 Dec 2016 00:08:26 GMT", "version": "v1" } ]
2016-12-19
[ [ "Foster", "Keith", "" ], [ "Blech", "Jan Olaf", "" ], [ "Prevost", "Guillaume", "" ] ]
This report gives an overview of our efforts towards a formalization for a food processing demonstrator plant. Our BeSpaceD framework is used for the formalization. The formalization comprises properties of components and relations between components. We present domain-specific constructs for the formalization of indus...
2211.08411
Nikhil Kandpal
Nikhil Kandpal, Haikang Deng, Adam Roberts, Eric Wallace, Colin Raffel
Large Language Models Struggle to Learn Long-Tail Knowledge
ICML 2023 Camera Ready Version
null
null
null
cs.CL cs.LG
http://creativecommons.org/licenses/by/4.0/
The Internet contains a wealth of knowledge -- from the birthdays of historical figures to tutorials on how to code -- all of which may be learned by language models. However, while certain pieces of information are ubiquitous on the web, others appear extremely rarely. In this paper, we study the relationship betwee...
[ { "created": "Tue, 15 Nov 2022 18:49:27 GMT", "version": "v1" }, { "created": "Thu, 27 Jul 2023 08:01:42 GMT", "version": "v2" } ]
2023-07-28
[ [ "Kandpal", "Nikhil", "" ], [ "Deng", "Haikang", "" ], [ "Roberts", "Adam", "" ], [ "Wallace", "Eric", "" ], [ "Raffel", "Colin", "" ] ]
The Internet contains a wealth of knowledge -- from the birthdays of historical figures to tutorials on how to code -- all of which may be learned by language models. However, while certain pieces of information are ubiquitous on the web, others appear extremely rarely. In this paper, we study the relationship between ...
1607.04767
Ahmad Eid H. A.
Ahmad Hosney Awad Eid
Optimized Automatic Code Generation for Geometric Algebra Based Algorithms with Ray Tracing Application
PhD Thesis, 2010, 249 pages
null
null
null
cs.MS cs.GR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Automatic code generation for low-dimensional geometric algorithms is capable of producing efficient low-level software code through a high-level geometric domain specific language. Geometric Algebra (GA) is one of the most suitable algebraic systems for being the base for such code generator. This work presents an a...
[ { "created": "Sat, 16 Jul 2016 16:54:39 GMT", "version": "v1" } ]
2016-07-19
[ [ "Eid", "Ahmad Hosney Awad", "" ] ]
Automatic code generation for low-dimensional geometric algorithms is capable of producing efficient low-level software code through a high-level geometric domain specific language. Geometric Algebra (GA) is one of the most suitable algebraic systems for being the base for such code generator. This work presents an att...
1905.08622
Mingyuan Zhou
Hao Zhang, Bo Chen, Long Tian, Zhengjue Wang, Mingyuan Zhou
Variational Hetero-Encoder Randomized GANs for Joint Image-Text Modeling
ICLR 2020
null
null
null
cs.CV cs.CL cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
For bidirectional joint image-text modeling, we develop variational hetero-encoder (VHE) randomized generative adversarial network (GAN), a versatile deep generative model that integrates a probabilistic text decoder, probabilistic image encoder, and GAN into a coherent end-to-end multi-modality learning framework. V...
[ { "created": "Sat, 18 May 2019 13:58:12 GMT", "version": "v1" }, { "created": "Wed, 25 Sep 2019 16:43:14 GMT", "version": "v2" }, { "created": "Tue, 7 Jan 2020 20:51:34 GMT", "version": "v3" } ]
2020-01-09
[ [ "Zhang", "Hao", "" ], [ "Chen", "Bo", "" ], [ "Tian", "Long", "" ], [ "Wang", "Zhengjue", "" ], [ "Zhou", "Mingyuan", "" ] ]
For bidirectional joint image-text modeling, we develop variational hetero-encoder (VHE) randomized generative adversarial network (GAN), a versatile deep generative model that integrates a probabilistic text decoder, probabilistic image encoder, and GAN into a coherent end-to-end multi-modality learning framework. VHE...
2207.06392
Shenghui Chen
Shenghui Chen, Yigit E. Bayiz, David Fridovich-Keil, Ufuk Topcu
Relationship Design for Socially-Aware Behavior in Static Games
null
null
null
null
cs.MA cs.SY eess.SY
http://creativecommons.org/licenses/by/4.0/
Autonomous agents can adopt socially-aware behaviors to reduce social costs, mimicking the way animals interact in nature and humans in society. We present a new approach to model socially-aware decision-making that includes two key elements: bounded rationality and inter-agent relationships. We capture the interagen...
[ { "created": "Wed, 13 Jul 2022 17:50:34 GMT", "version": "v1" }, { "created": "Fri, 26 Jan 2024 04:30:02 GMT", "version": "v2" } ]
2024-01-29
[ [ "Chen", "Shenghui", "" ], [ "Bayiz", "Yigit E.", "" ], [ "Fridovich-Keil", "David", "" ], [ "Topcu", "Ufuk", "" ] ]
Autonomous agents can adopt socially-aware behaviors to reduce social costs, mimicking the way animals interact in nature and humans in society. We present a new approach to model socially-aware decision-making that includes two key elements: bounded rationality and inter-agent relationships. We capture the interagent ...
2402.03666
Haoxuan Wang
Haoxuan Wang, Yuzhang Shang, Zhihang Yuan, Junyi Wu, Yan Yan
QuEST: Low-bit Diffusion Model Quantization via Efficient Selective Finetuning
null
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Diffusion models have achieved remarkable success in image generation tasks, yet their practical deployment is restrained by the high memory and time consumption. While quantization paves a way for diffusion model compression and acceleration, existing methods totally fail when the models are quantized to low-bits. I...
[ { "created": "Tue, 6 Feb 2024 03:39:44 GMT", "version": "v1" }, { "created": "Tue, 13 Feb 2024 05:22:34 GMT", "version": "v2" } ]
2024-02-14
[ [ "Wang", "Haoxuan", "" ], [ "Shang", "Yuzhang", "" ], [ "Yuan", "Zhihang", "" ], [ "Wu", "Junyi", "" ], [ "Yan", "Yan", "" ] ]
Diffusion models have achieved remarkable success in image generation tasks, yet their practical deployment is restrained by the high memory and time consumption. While quantization paves a way for diffusion model compression and acceleration, existing methods totally fail when the models are quantized to low-bits. In ...
2406.16807
Katherine Collins
Katherine M. Collins, Najoung Kim, Yonatan Bitton, Verena Rieser, Shayegan Omidshafiei, Yushi Hu, Sherol Chen, Senjuti Dutta, Minsuk Chang, Kimin Lee, Youwei Liang, Georgina Evans, Sahil Singla, Gang Li, Adrian Weller, Junfeng He, Deepak Ramachandran, Krishnamurthy Dj Dvijotham
Beyond Thumbs Up/Down: Untangling Challenges of Fine-Grained Feedback for Text-to-Image Generation
null
null
null
null
cs.LG cs.CL cs.CV
http://creativecommons.org/licenses/by/4.0/
Human feedback plays a critical role in learning and refining reward models for text-to-image generation, but the optimal form the feedback should take for learning an accurate reward function has not been conclusively established. This paper investigates the effectiveness of fine-grained feedback which captures nuan...
[ { "created": "Mon, 24 Jun 2024 17:19:34 GMT", "version": "v1" } ]
2024-06-25
[ [ "Collins", "Katherine M.", "" ], [ "Kim", "Najoung", "" ], [ "Bitton", "Yonatan", "" ], [ "Rieser", "Verena", "" ], [ "Omidshafiei", "Shayegan", "" ], [ "Hu", "Yushi", "" ], [ "Chen", "Sherol", "" ], [ ...
Human feedback plays a critical role in learning and refining reward models for text-to-image generation, but the optimal form the feedback should take for learning an accurate reward function has not been conclusively established. This paper investigates the effectiveness of fine-grained feedback which captures nuance...
2110.04035
Jihao Liu
Jihao Liu and Hongsheng Li and Guanglu Song and Xin Huang and Yu Liu
UniNet: Unified Architecture Search with Convolution, Transformer, and MLP
technich report
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recently, transformer and multi-layer perceptron (MLP) architectures have achieved impressive results on various vision tasks. A few works investigated manually combining those operators to design visual network architectures, and can achieve satisfactory performances to some extent. In this paper, we propose to join...
[ { "created": "Fri, 8 Oct 2021 11:09:40 GMT", "version": "v1" } ]
2021-10-11
[ [ "Liu", "Jihao", "" ], [ "Li", "Hongsheng", "" ], [ "Song", "Guanglu", "" ], [ "Huang", "Xin", "" ], [ "Liu", "Yu", "" ] ]
Recently, transformer and multi-layer perceptron (MLP) architectures have achieved impressive results on various vision tasks. A few works investigated manually combining those operators to design visual network architectures, and can achieve satisfactory performances to some extent. In this paper, we propose to jointl...
1802.03604
Gong-Duo Zhang
Gong-Duo Zhang, Shen-Yi Zhao, Hao Gao, Wu-Jun Li
Feature-Distributed SVRG for High-Dimensional Linear Classification
null
null
null
null
cs.LG cs.DC stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Linear classification has been widely used in many high-dimensional applications like text classification. To perform linear classification for large-scale tasks, we often need to design distributed learning methods on a cluster of multiple machines. In this paper, we propose a new distributed learning method, called...
[ { "created": "Sat, 10 Feb 2018 14:53:57 GMT", "version": "v1" } ]
2018-02-13
[ [ "Zhang", "Gong-Duo", "" ], [ "Zhao", "Shen-Yi", "" ], [ "Gao", "Hao", "" ], [ "Li", "Wu-Jun", "" ] ]
Linear classification has been widely used in many high-dimensional applications like text classification. To perform linear classification for large-scale tasks, we often need to design distributed learning methods on a cluster of multiple machines. In this paper, we propose a new distributed learning method, called f...
2110.06384
Pooja Sethi
Pooja Sethi, Denis Savenkov, Forough Arabshahi, Jack Goetz, Micaela Tolliver, Nicolas Scheffer, Ilknur Kabul, Yue Liu, Ahmed Aly
AutoNLU: Detecting, root-causing, and fixing NLU model errors
8 pages, 5 figures
null
null
null
cs.CL cs.LG
http://creativecommons.org/licenses/by/4.0/
Improving the quality of Natural Language Understanding (NLU) models, and more specifically, task-oriented semantic parsing models, in production is a cumbersome task. In this work, we present a system called AutoNLU, which we designed to scale the NLU quality improvement process. It adds automation to three key step...
[ { "created": "Tue, 12 Oct 2021 22:12:26 GMT", "version": "v1" } ]
2021-10-14
[ [ "Sethi", "Pooja", "" ], [ "Savenkov", "Denis", "" ], [ "Arabshahi", "Forough", "" ], [ "Goetz", "Jack", "" ], [ "Tolliver", "Micaela", "" ], [ "Scheffer", "Nicolas", "" ], [ "Kabul", "Ilknur", "" ], [ ...
Improving the quality of Natural Language Understanding (NLU) models, and more specifically, task-oriented semantic parsing models, in production is a cumbersome task. In this work, we present a system called AutoNLU, which we designed to scale the NLU quality improvement process. It adds automation to three key steps:...
1012.2394
Bin Fu
Bin Fu
NE is not NP Turing Reducible to Nonexpoentially Dense NP Sets
null
null
null
null
cs.CC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A long standing open problem in the computational complexity theory is to separate NE from BPP, which is a subclass of $NP_T(NP\cap P/poly)$. In this paper, we show that $NE\not\subseteq NP_(NP \cap$ Nonexponentially-Dense-Class), where Nonexponentially-Dense-Class is the class of languages A without exponential dens...
[ { "created": "Fri, 10 Dec 2010 21:19:11 GMT", "version": "v1" } ]
2010-12-14
[ [ "Fu", "Bin", "" ] ]
A long standing open problem in the computational complexity theory is to separate NE from BPP, which is a subclass of $NP_T(NP\cap P/poly)$. In this paper, we show that $NE\not\subseteq NP_(NP \cap$ Nonexponentially-Dense-Class), where Nonexponentially-Dense-Class is the class of languages A without exponential densit...
2305.00067
Nurislam Tursynbek
Nurislam Tursynbek, Marc Niethammer
Unsupervised Discovery of 3D Hierarchical Structure with Generative Diffusion Features
MICCAI 2023
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Inspired by recent findings that generative diffusion models learn semantically meaningful representations, we use them to discover the intrinsic hierarchical structure in biomedical 3D images using unsupervised segmentation. We show that features of diffusion models from different stages of a U-Net-based ladder-like...
[ { "created": "Fri, 28 Apr 2023 19:37:17 GMT", "version": "v1" }, { "created": "Tue, 10 Oct 2023 04:01:38 GMT", "version": "v2" } ]
2023-10-11
[ [ "Tursynbek", "Nurislam", "" ], [ "Niethammer", "Marc", "" ] ]
Inspired by recent findings that generative diffusion models learn semantically meaningful representations, we use them to discover the intrinsic hierarchical structure in biomedical 3D images using unsupervised segmentation. We show that features of diffusion models from different stages of a U-Net-based ladder-like a...
1211.0055
ELkebir Sarhrouni
Elkebir Sarhrouni, Ahmed Hammouch and Driss Aboutajdine
Dimensionality Reduction and Classification Feature Using Mutual Information Applied to Hyperspectral Images: A Wrapper Strategy Algorithm Based on Minimizing the Error Probability Using the Inequality of Fano
12 page, 5 figures. arXiv admin note: substantial text overlap with arXiv:1210.0528, arXiv:1210.0052
Applied Mathematical Sciences, Vol. 6, 2012, no. 102, 5073 - 5084
null
null
cs.CV
http://creativecommons.org/licenses/publicdomain/
In the feature classification domain, the choice of data affects widely the results. For the Hyperspectral image, the bands dont all contain the information; some bands are irrelevant like those affected by various atmospheric effects, see Figure.4, and decrease the classification accuracy. And there exist redundant ...
[ { "created": "Wed, 31 Oct 2012 23:30:59 GMT", "version": "v1" } ]
2012-11-02
[ [ "Sarhrouni", "Elkebir", "" ], [ "Hammouch", "Ahmed", "" ], [ "Aboutajdine", "Driss", "" ] ]
In the feature classification domain, the choice of data affects widely the results. For the Hyperspectral image, the bands dont all contain the information; some bands are irrelevant like those affected by various atmospheric effects, see Figure.4, and decrease the classification accuracy. And there exist redundant ba...
2408.06110
Zhiyuan Zhang
Zhiyuan Zhang, Licheng Yang, Zhiyu Xiang
RISurConv: Rotation Invariant Surface Attention-Augmented Convolutions for 3D Point Cloud Classification and Segmentation
ECCV 2024 (oral)
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Despite the progress on 3D point cloud deep learning, most prior works focus on learning features that are invariant to translation and point permutation, and very limited efforts have been devoted for rotation invariant property. Several recent studies achieve rotation invariance at the cost of lower accuracies. In ...
[ { "created": "Mon, 12 Aug 2024 12:47:37 GMT", "version": "v1" } ]
2024-08-13
[ [ "Zhang", "Zhiyuan", "" ], [ "Yang", "Licheng", "" ], [ "Xiang", "Zhiyu", "" ] ]
Despite the progress on 3D point cloud deep learning, most prior works focus on learning features that are invariant to translation and point permutation, and very limited efforts have been devoted for rotation invariant property. Several recent studies achieve rotation invariance at the cost of lower accuracies. In th...
2007.11280
Yuhu Yan
Bo-Jian Hou, Yu-Hu Yan, Peng Zhao and Zhi-Hua Zhou
Storage Fit Learning with Feature Evolvable Streams
null
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Feature evolvable learning has been widely studied in recent years where old features will vanish and new features will emerge when learning with streams. Conventional methods usually assume that a label will be revealed after prediction at each time step. However, in practice, this assumption may not hold whereas no...
[ { "created": "Wed, 22 Jul 2020 09:08:42 GMT", "version": "v1" }, { "created": "Tue, 5 Jan 2021 11:24:10 GMT", "version": "v2" }, { "created": "Tue, 23 Feb 2021 07:27:01 GMT", "version": "v3" } ]
2021-02-24
[ [ "Hou", "Bo-Jian", "" ], [ "Yan", "Yu-Hu", "" ], [ "Zhao", "Peng", "" ], [ "Zhou", "Zhi-Hua", "" ] ]
Feature evolvable learning has been widely studied in recent years where old features will vanish and new features will emerge when learning with streams. Conventional methods usually assume that a label will be revealed after prediction at each time step. However, in practice, this assumption may not hold whereas no l...
2006.12031
Itay Tsabary
Itay Tsabary, Matan Yechieli, Alex Manuskin, Ittay Eyal
MAD-HTLC: Because HTLC is Crazy-Cheap to Attack
null
null
null
null
cs.CR cs.GT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Smart Contracts and transactions allow users to implement elaborate constructions on cryptocurrency blockchains like Bitcoin and Ethereum. Many of these constructions, including operational payment channels and atomic swaps, use a building block called Hashed Time-Locked Contract (HTLC). In this work, we distill fr...
[ { "created": "Mon, 22 Jun 2020 06:58:24 GMT", "version": "v1" }, { "created": "Mon, 7 Dec 2020 12:14:36 GMT", "version": "v2" }, { "created": "Thu, 25 Mar 2021 09:59:57 GMT", "version": "v3" } ]
2021-03-26
[ [ "Tsabary", "Itay", "" ], [ "Yechieli", "Matan", "" ], [ "Manuskin", "Alex", "" ], [ "Eyal", "Ittay", "" ] ]
Smart Contracts and transactions allow users to implement elaborate constructions on cryptocurrency blockchains like Bitcoin and Ethereum. Many of these constructions, including operational payment channels and atomic swaps, use a building block called Hashed Time-Locked Contract (HTLC). In this work, we distill from H...
1905.04767
Ilia Petrov
Tobias Vincon, Andreas Koch, Ilia Petrov
Moving Processing to Data: On the Influence of Processing in Memory on Data Management
null
null
null
null
cs.DB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Near-Data Processing refers to an architectural hardware and software paradigm, based on the co-location of storage and compute units. Ideally, it will allow to execute application-defined data- or compute-intensive operations in-situ, i.e. within (or close to) the physical data storage. Thus, Near-Data Processing se...
[ { "created": "Sun, 12 May 2019 18:27:44 GMT", "version": "v1" } ]
2019-05-14
[ [ "Vincon", "Tobias", "" ], [ "Koch", "Andreas", "" ], [ "Petrov", "Ilia", "" ] ]
Near-Data Processing refers to an architectural hardware and software paradigm, based on the co-location of storage and compute units. Ideally, it will allow to execute application-defined data- or compute-intensive operations in-situ, i.e. within (or close to) the physical data storage. Thus, Near-Data Processing seek...
1903.04084
Yang Zheng
Yang Zheng, Izzat H. Izzat, John H.L. Hansen
Exploring OpenStreetMap Availability for Driving Environment Understanding
12 pages, 16 figures
null
null
null
cs.HC cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
With the great achievement of artificial intelligence, vehicle technologies have advanced significantly from human centric driving towards fully automated driving. An intelligent vehicle should be able to understand the driver's perception of the environment as well as controlling behavior of the vehicle. Since high ...
[ { "created": "Mon, 11 Mar 2019 00:43:13 GMT", "version": "v1" } ]
2019-03-12
[ [ "Zheng", "Yang", "" ], [ "Izzat", "Izzat H.", "" ], [ "Hansen", "John H. L.", "" ] ]
With the great achievement of artificial intelligence, vehicle technologies have advanced significantly from human centric driving towards fully automated driving. An intelligent vehicle should be able to understand the driver's perception of the environment as well as controlling behavior of the vehicle. Since high di...
1904.08451
Jingjing Bu
Jingjing Bu and Afshin Mesbahi and Mehran Mesbahi
On Topological Properties of the Set of Stabilizing Feedback Gains
null
null
null
null
cs.SY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This work presents a fairly complete account on various topological and metrical aspects of feedback stabilization for single-input-single-output (SISO) continuous and discrete time linear-time-invariant (LTI) systems. In particular, we prove that the set of stabilizing output feedback gains for a SISO system with n ...
[ { "created": "Wed, 17 Apr 2019 18:48:08 GMT", "version": "v1" } ]
2019-04-19
[ [ "Bu", "Jingjing", "" ], [ "Mesbahi", "Afshin", "" ], [ "Mesbahi", "Mehran", "" ] ]
This work presents a fairly complete account on various topological and metrical aspects of feedback stabilization for single-input-single-output (SISO) continuous and discrete time linear-time-invariant (LTI) systems. In particular, we prove that the set of stabilizing output feedback gains for a SISO system with n st...
1601.06527
Pascal Held
Pascal Held, Rudolf Kruse
Online Community Detection by Using Nearest Hubs
Presented as poster at the NetSciX 2016
null
null
null
cs.SI physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Community and cluster detection is a popular field of social network analysis. Most algorithms focus on static graphs or series of snapshots. In this paper we present an algorithm, which detects communities in dynamic graphs. The method is based on shortest paths to high-connected nodes, so called hubs. Due to loca...
[ { "created": "Mon, 25 Jan 2016 09:41:43 GMT", "version": "v1" } ]
2016-01-26
[ [ "Held", "Pascal", "" ], [ "Kruse", "Rudolf", "" ] ]
Community and cluster detection is a popular field of social network analysis. Most algorithms focus on static graphs or series of snapshots. In this paper we present an algorithm, which detects communities in dynamic graphs. The method is based on shortest paths to high-connected nodes, so called hubs. Due to local me...
1910.10310
Zilong Wang
Zilong Wang, Dongxu Ma, Erzhong Xue, Guang Gong, Srdjan Budisin
New Construction of Complementary Sequence (or Array) Sets and Complete Complementary Codes (II)
This paper and another is merged together. And the merged paper is online
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Previously, we have presented a framework to use the para-unitary (PU) matrix-based approach for constructing new complementary sequence set (CSS), complete complementary code (CCC), complementary sequence array (CSA), and complete complementary array (CCA). In this paper, we introduce a new class of delay matrices f...
[ { "created": "Wed, 23 Oct 2019 01:31:28 GMT", "version": "v1" }, { "created": "Tue, 12 May 2020 14:34:20 GMT", "version": "v2" } ]
2020-05-13
[ [ "Wang", "Zilong", "" ], [ "Ma", "Dongxu", "" ], [ "Xue", "Erzhong", "" ], [ "Gong", "Guang", "" ], [ "Budisin", "Srdjan", "" ] ]
Previously, we have presented a framework to use the para-unitary (PU) matrix-based approach for constructing new complementary sequence set (CSS), complete complementary code (CCC), complementary sequence array (CSA), and complete complementary array (CCA). In this paper, we introduce a new class of delay matrices for...
1906.09822
Mark Levene
Mark Levene, Trevor Fenner and Judit Bar-Ilan
Characterisation of the $\chi$-index and the $rec$-index
14 pages, 3 figures. This is a pre-print of an article published in Scientometrics. The final authenticated version is available online at: https://doi.org/10.1007/s11192-019-03151-7
null
10.1007/s11192-019-03151-7
null
cs.DL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Axiomatic characterisation of a bibliometric index provides insight into the properties that the index satisfies and facilitates the comparison of different indices. A geometric generalisation of the $h$-index, called the $\chi$-index, has recently been proposed to address some of the problems with the $h$-index, in ...
[ { "created": "Mon, 24 Jun 2019 09:59:38 GMT", "version": "v1" } ]
2019-06-25
[ [ "Levene", "Mark", "" ], [ "Fenner", "Trevor", "" ], [ "Bar-Ilan", "Judit", "" ] ]
Axiomatic characterisation of a bibliometric index provides insight into the properties that the index satisfies and facilitates the comparison of different indices. A geometric generalisation of the $h$-index, called the $\chi$-index, has recently been proposed to address some of the problems with the $h$-index, in pa...
2208.00444
Siladittya Manna
Siladittya Manna, Rakesh Dey, Souvik Chakraborty
BYOLMed3D: Self-Supervised Representation Learning of Medical Videos using Gradient Accumulation Assisted 3D BYOL Framework
The work requires revision. After verification it came to light, that the data presented in the paper is erroneous. The correct data will be updated after extensive experiments
null
null
null
cs.CV
http://creativecommons.org/publicdomain/zero/1.0/
Applications on Medical Image Analysis suffer from acute shortage of large volume of data properly annotated by medical experts. Supervised Learning algorithms require a large volumes of balanced data to learn robust representations. Often supervised learning algorithms require various techniques to deal with imbalan...
[ { "created": "Sun, 31 Jul 2022 14:48:06 GMT", "version": "v1" }, { "created": "Sun, 25 Sep 2022 13:36:42 GMT", "version": "v2" }, { "created": "Sat, 12 Nov 2022 15:54:25 GMT", "version": "v3" } ]
2022-11-15
[ [ "Manna", "Siladittya", "" ], [ "Dey", "Rakesh", "" ], [ "Chakraborty", "Souvik", "" ] ]
Applications on Medical Image Analysis suffer from acute shortage of large volume of data properly annotated by medical experts. Supervised Learning algorithms require a large volumes of balanced data to learn robust representations. Often supervised learning algorithms require various techniques to deal with imbalance...
2403.01545
Annie Johnson
Colleen Estes, Beth Twomey, Annie Johnson
It Takes a Village: A Distributed Training Model for AI-based Chatbots
null
null
null
null
cs.DL
http://creativecommons.org/licenses/by-nc-sa/4.0/
In Summer 2023, staff from the information technology and reference departments at the University of Delaware Library, Museums and Press came together in a unique partnership to pilot a low-cost AI-powered chatbot. The goal of the pilot is to learn more about student and faculty interest in engaging with this tool, a...
[ { "created": "Sun, 3 Mar 2024 15:46:35 GMT", "version": "v1" } ]
2024-03-05
[ [ "Estes", "Colleen", "" ], [ "Twomey", "Beth", "" ], [ "Johnson", "Annie", "" ] ]
In Summer 2023, staff from the information technology and reference departments at the University of Delaware Library, Museums and Press came together in a unique partnership to pilot a low-cost AI-powered chatbot. The goal of the pilot is to learn more about student and faculty interest in engaging with this tool, and...
1812.10202
Mikhail Prokopenko
Mikhail Prokopenko and Peter Wang
Gliders2d: Source Code Base for RoboCup 2D Soccer Simulation League
12 pages, 1 figure, Gliders2d code release
null
null
null
cs.MA
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We describe Gliders2d, a base code release for Gliders, a soccer simulation team which won the RoboCup Soccer 2D Simulation League in 2016. We trace six evolutionary steps, each of which is encapsulated in a sequential change of the released code, from v1.1 to v1.6, starting from agent2d-3.1.1 (set as the baseline v1...
[ { "created": "Wed, 26 Dec 2018 02:20:24 GMT", "version": "v1" } ]
2018-12-27
[ [ "Prokopenko", "Mikhail", "" ], [ "Wang", "Peter", "" ] ]
We describe Gliders2d, a base code release for Gliders, a soccer simulation team which won the RoboCup Soccer 2D Simulation League in 2016. We trace six evolutionary steps, each of which is encapsulated in a sequential change of the released code, from v1.1 to v1.6, starting from agent2d-3.1.1 (set as the baseline v1.0...
2404.08692
Shangyu Chen
Shangyu Chen, Zibo Zhao, Yuanyuan Zhao, Xiang Li
Apollonion: Profile-centric Dialog Agent
null
null
null
null
cs.IR cs.AI cs.CL
http://creativecommons.org/licenses/by/4.0/
The emergence of Large Language Models (LLMs) has innovated the development of dialog agents. Specially, a well-trained LLM, as a central process unit, is capable of providing fluent and reasonable response for user's request. Besides, auxiliary tools such as external knowledge retrieval, personalized character for v...
[ { "created": "Wed, 10 Apr 2024 03:32:41 GMT", "version": "v1" } ]
2024-04-16
[ [ "Chen", "Shangyu", "" ], [ "Zhao", "Zibo", "" ], [ "Zhao", "Yuanyuan", "" ], [ "Li", "Xiang", "" ] ]
The emergence of Large Language Models (LLMs) has innovated the development of dialog agents. Specially, a well-trained LLM, as a central process unit, is capable of providing fluent and reasonable response for user's request. Besides, auxiliary tools such as external knowledge retrieval, personalized character for viv...
0812.1093
Stephane Devismes
Ajoy K. Datta (UNLV), St\'ephane Devismes (VERIMAG - IMAG), Florian Horn (LIAFA), Lawrence L. Larmore (UNLV)
Self-stabilizing K-out-of-L exclusion on tree network
15 pages
null
null
null
cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we address the problem of K-out-of-L exclusion, a generalization of the mutual exclusion problem, in which there are $\ell$ units of a shared resource, and any process can request up to $\mathtt k$ units ($1\leq\mathtt k\leq\ell$). We propose the first deterministic self-stabilizing distributed K-out-o...
[ { "created": "Fri, 5 Dec 2008 08:47:25 GMT", "version": "v1" }, { "created": "Sun, 7 Dec 2008 20:19:29 GMT", "version": "v2" }, { "created": "Fri, 19 Dec 2008 07:49:35 GMT", "version": "v3" }, { "created": "Fri, 13 Feb 2009 12:37:39 GMT", "version": "v4" } ]
2009-09-29
[ [ "Datta", "Ajoy K.", "", "UNLV" ], [ "Devismes", "Stéphane", "", "VERIMAG - IMAG" ], [ "Horn", "Florian", "", "LIAFA" ], [ "Larmore", "Lawrence L.", "", "UNLV" ] ]
In this paper, we address the problem of K-out-of-L exclusion, a generalization of the mutual exclusion problem, in which there are $\ell$ units of a shared resource, and any process can request up to $\mathtt k$ units ($1\leq\mathtt k\leq\ell$). We propose the first deterministic self-stabilizing distributed K-out-of-...
2303.07042
Charalampos Bechlioulis
Raksi Kopo, Charalampos P. Bechlioulis, Kostas J. Kyriakopoulos
Harmonic Field-based Provable Exploration of 3D Indoor Environments
null
null
null
null
cs.RO
http://creativecommons.org/licenses/by/4.0/
This work presents an safe and efficient methodology for autonomous indoor exploration with aerial robots using Harmonic Potential Fields (HPF). The challenge of applying HPF in complex 3D environments rests on high computational load involved in solving the Laplace equation. To address this issue, the proposed solut...
[ { "created": "Mon, 13 Mar 2023 12:05:40 GMT", "version": "v1" } ]
2023-03-14
[ [ "Kopo", "Raksi", "" ], [ "Bechlioulis", "Charalampos P.", "" ], [ "Kyriakopoulos", "Kostas J.", "" ] ]
This work presents an safe and efficient methodology for autonomous indoor exploration with aerial robots using Harmonic Potential Fields (HPF). The challenge of applying HPF in complex 3D environments rests on high computational load involved in solving the Laplace equation. To address this issue, the proposed solutio...
1110.4703
John Tadrous Mr.
John Tadrous, Atilla Eryilmaz, Hesham El Gamal
Proactive Resource Allocation: Harnessing the Diversity and Multicast Gains
null
null
null
null
cs.IT cs.NI math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper introduces the novel concept of proactive resource allocation through which the predictability of user behavior is exploited to balance the wireless traffic over time, and hence, significantly reduce the bandwidth required to achieve a given blocking/outage probability. We start with a simple model in whic...
[ { "created": "Fri, 21 Oct 2011 05:11:48 GMT", "version": "v1" } ]
2011-10-24
[ [ "Tadrous", "John", "" ], [ "Eryilmaz", "Atilla", "" ], [ "Gamal", "Hesham El", "" ] ]
This paper introduces the novel concept of proactive resource allocation through which the predictability of user behavior is exploited to balance the wireless traffic over time, and hence, significantly reduce the bandwidth required to achieve a given blocking/outage probability. We start with a simple model in which ...
1802.07177
Shay Solomon
Shirel Attali and Merav Parter and David Peleg and Shay Solomon
Wireless Expanders
null
null
null
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper introduces an extended notion of expansion suitable for radio networks. A graph $G=(V,E)$ is called an $(\alpha_w, \beta_w)$-{wireless expander} if for every subset $S \subseteq V$ s.t. $|S|\leq \alpha_w \cdot |V|$, there exists a subset $S'\subseteq S$ s.t. there are at least $\beta_w \cdot |S|$ vertices ...
[ { "created": "Tue, 20 Feb 2018 16:17:30 GMT", "version": "v1" } ]
2018-02-21
[ [ "Attali", "Shirel", "" ], [ "Parter", "Merav", "" ], [ "Peleg", "David", "" ], [ "Solomon", "Shay", "" ] ]
This paper introduces an extended notion of expansion suitable for radio networks. A graph $G=(V,E)$ is called an $(\alpha_w, \beta_w)$-{wireless expander} if for every subset $S \subseteq V$ s.t. $|S|\leq \alpha_w \cdot |V|$, there exists a subset $S'\subseteq S$ s.t. there are at least $\beta_w \cdot |S|$ vertices in...
2206.03253
Stefano Mariani
Stefano Mariani, Marco Picone, Alessandro Ricci
About Digital Twins, agents, and multiagent systems: a cross-fertilisation journey
Digital Twin, Agent, Multiagent system, Cyber-physical system;16 pages; accepted and presented at EMAS2022 (workshop of AAMAS: https://emas.in.tu-clausthal.de/2022/#accepted)
Autonomous Agents and Multiagent Systems. Best and Visionary Papers. AAMAS 2022. Lecture Notes in Computer Science(), vol 13441, pp. 114-129
10.1007/978-3-031-20179-0_8
null
cs.MA
http://creativecommons.org/licenses/by/4.0/
Digital Twins (DTs) are rapidly emerging as a fundamental brick of engineering cyber-physical systems, but their notion is still mostly bound to specific business domains (e.g. manufacturing), goals (e.g. product design), or application domains (e.g. the Internet of Things). As such, their value as general purpose en...
[ { "created": "Tue, 7 Jun 2022 13:08:46 GMT", "version": "v1" } ]
2022-11-15
[ [ "Mariani", "Stefano", "" ], [ "Picone", "Marco", "" ], [ "Ricci", "Alessandro", "" ] ]
Digital Twins (DTs) are rapidly emerging as a fundamental brick of engineering cyber-physical systems, but their notion is still mostly bound to specific business domains (e.g. manufacturing), goals (e.g. product design), or application domains (e.g. the Internet of Things). As such, their value as general purpose engi...
0902.1254
Wadie Guizani
Mahdi Cheraghchi (EPFL), Amin Shokrollahi (EPFL)
Almost-Uniform Sampling of Points on High-Dimensional Algebraic Varieties
null
26th International Symposium on Theoretical Aspects of Computer Science STACS 2009 (2009) 277-288
null
null
cs.DS cs.CC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We consider the problem of uniform sampling of points on an algebraic variety. Specifically, we develop a randomized algorithm that, given a small set of multivariate polynomials over a sufficiently large finite field, produces a common zero of the polynomials almost uniformly at random. The statistical distance betw...
[ { "created": "Sat, 7 Feb 2009 17:56:02 GMT", "version": "v1" } ]
2009-02-10
[ [ "Cheraghchi", "Mahdi", "", "EPFL" ], [ "Shokrollahi", "Amin", "", "EPFL" ] ]
We consider the problem of uniform sampling of points on an algebraic variety. Specifically, we develop a randomized algorithm that, given a small set of multivariate polynomials over a sufficiently large finite field, produces a common zero of the polynomials almost uniformly at random. The statistical distance betwee...
2111.03442
Mohammad Zeineldeen
Mohammad Zeineldeen, Jingjing Xu, Christoph L\"uscher, Wilfried Michel, Alexander Gerstenberger, Ralf Schl\"uter, Hermann Ney
Conformer-based Hybrid ASR System for Switchboard Dataset
Accepted at ICASSP 2022
null
null
null
cs.CL eess.AS stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The recently proposed conformer architecture has been successfully used for end-to-end automatic speech recognition (ASR) architectures achieving state-of-the-art performance on different datasets. To our best knowledge, the impact of using conformer acoustic model for hybrid ASR is not investigated. In this paper, w...
[ { "created": "Fri, 5 Nov 2021 12:03:18 GMT", "version": "v1" }, { "created": "Sat, 19 Feb 2022 21:53:03 GMT", "version": "v2" } ]
2022-02-22
[ [ "Zeineldeen", "Mohammad", "" ], [ "Xu", "Jingjing", "" ], [ "Lüscher", "Christoph", "" ], [ "Michel", "Wilfried", "" ], [ "Gerstenberger", "Alexander", "" ], [ "Schlüter", "Ralf", "" ], [ "Ney", "Hermann", ...
The recently proposed conformer architecture has been successfully used for end-to-end automatic speech recognition (ASR) architectures achieving state-of-the-art performance on different datasets. To our best knowledge, the impact of using conformer acoustic model for hybrid ASR is not investigated. In this paper, we ...
2209.02997
Miki Tanaka
Miki Tanaka, Isao Echizen, Hitoshi Kiya
On the Transferability of Adversarial Examples between Encrypted Models
to be appear in ISPACS 2022
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Deep neural networks (DNNs) are well known to be vulnerable to adversarial examples (AEs). In addition, AEs have adversarial transferability, namely, AEs generated for a source model fool other (target) models. In this paper, we investigate the transferability of models encrypted for adversarially robust defense for ...
[ { "created": "Wed, 7 Sep 2022 08:50:26 GMT", "version": "v1" } ]
2022-09-08
[ [ "Tanaka", "Miki", "" ], [ "Echizen", "Isao", "" ], [ "Kiya", "Hitoshi", "" ] ]
Deep neural networks (DNNs) are well known to be vulnerable to adversarial examples (AEs). In addition, AEs have adversarial transferability, namely, AEs generated for a source model fool other (target) models. In this paper, we investigate the transferability of models encrypted for adversarially robust defense for th...
2010.11531
Manuel Kaufmann
Manuel Kaufmann, Emre Aksan, Jie Song, Fabrizio Pece, Remo Ziegler, Otmar Hilliges
Convolutional Autoencoders for Human Motion Infilling
Accepted to 3DV 2020
null
10.1109/3DV50981.2020.00102
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper we propose a convolutional autoencoder to address the problem of motion infilling for 3D human motion data. Given a start and end sequence, motion infilling aims to complete the missing gap in between, such that the filled in poses plausibly forecast the start sequence and naturally transition into the ...
[ { "created": "Thu, 22 Oct 2020 08:45:38 GMT", "version": "v1" } ]
2021-11-17
[ [ "Kaufmann", "Manuel", "" ], [ "Aksan", "Emre", "" ], [ "Song", "Jie", "" ], [ "Pece", "Fabrizio", "" ], [ "Ziegler", "Remo", "" ], [ "Hilliges", "Otmar", "" ] ]
In this paper we propose a convolutional autoencoder to address the problem of motion infilling for 3D human motion data. Given a start and end sequence, motion infilling aims to complete the missing gap in between, such that the filled in poses plausibly forecast the start sequence and naturally transition into the en...
1905.03525
Peter Sanders
Lorenz H\"ubschle-Schneider, Peter Sanders
Linear Work Generation of R-MAT Graphs
null
Net Sci 8 (2020) 543-550
10.1017/nws.2020.21
null
cs.DS cs.DC cs.DM cs.SI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
R-MAT is a simple, widely used recursive model for generating `complex network' graphs with a power law degree distribution and community structure. We make R-MAT even more useful by reducing the required work per edge from logarithmic to constant. The algorithm works in an embarrassingly parallel way.
[ { "created": "Thu, 9 May 2019 10:46:34 GMT", "version": "v1" } ]
2020-10-14
[ [ "Hübschle-Schneider", "Lorenz", "" ], [ "Sanders", "Peter", "" ] ]
R-MAT is a simple, widely used recursive model for generating `complex network' graphs with a power law degree distribution and community structure. We make R-MAT even more useful by reducing the required work per edge from logarithmic to constant. The algorithm works in an embarrassingly parallel way.
2111.09642
Mandar Gogate
Tassadaq Hussain, Mandar Gogate, Kia Dashtipour, Amir Hussain
Towards Intelligibility-Oriented Audio-Visual Speech Enhancement
6 pages, 4 figures
null
null
null
cs.SD cs.CV cs.LG eess.AS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Existing deep learning (DL) based speech enhancement approaches are generally optimised to minimise the distance between clean and enhanced speech features. These often result in improved speech quality however they suffer from a lack of generalisation and may not deliver the required speech intelligibility in real n...
[ { "created": "Thu, 18 Nov 2021 11:47:37 GMT", "version": "v1" } ]
2021-11-19
[ [ "Hussain", "Tassadaq", "" ], [ "Gogate", "Mandar", "" ], [ "Dashtipour", "Kia", "" ], [ "Hussain", "Amir", "" ] ]
Existing deep learning (DL) based speech enhancement approaches are generally optimised to minimise the distance between clean and enhanced speech features. These often result in improved speech quality however they suffer from a lack of generalisation and may not deliver the required speech intelligibility in real noi...
2306.05401
Ori Press
Ori Press, Steffen Schneider, Matthias K\"ummerer, Matthias Bethge
RDumb: A simple approach that questions our progress in continual test-time adaptation
null
null
null
null
cs.LG cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Test-Time Adaptation (TTA) allows to update pre-trained models to changing data distributions at deployment time. While early work tested these algorithms for individual fixed distribution shifts, recent work proposed and applied methods for continual adaptation over long timescales. To examine the reported progress ...
[ { "created": "Thu, 8 Jun 2023 17:52:34 GMT", "version": "v1" }, { "created": "Sat, 4 Nov 2023 20:07:18 GMT", "version": "v2" }, { "created": "Wed, 3 Apr 2024 10:16:22 GMT", "version": "v3" } ]
2024-04-04
[ [ "Press", "Ori", "" ], [ "Schneider", "Steffen", "" ], [ "Kümmerer", "Matthias", "" ], [ "Bethge", "Matthias", "" ] ]
Test-Time Adaptation (TTA) allows to update pre-trained models to changing data distributions at deployment time. While early work tested these algorithms for individual fixed distribution shifts, recent work proposed and applied methods for continual adaptation over long timescales. To examine the reported progress in...