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2201.12673
Marco Rasetto
Marco Rasetto, Qingzhou Wan, Himanshu Akolkar, Feng Xiong, Bertram Shi and Ryad Benosman
Building time-surfaces by exploiting the complex volatility of an ECRAM memristor
null
null
10.1109/JETCAS.2023.3330832
null
cs.ET
http://creativecommons.org/licenses/by/4.0/
Memristors have emerged as a promising technology for efficient neuromorphic architectures owing to their ability to act as programmable synapses, combining processing and memory into a single device. Although they are most commonly used for static encoding of synaptic weights, recent work has begun to investigate th...
[ { "created": "Sat, 29 Jan 2022 22:18:55 GMT", "version": "v1" }, { "created": "Mon, 15 Apr 2024 09:21:39 GMT", "version": "v2" } ]
2024-04-16
[ [ "Rasetto", "Marco", "" ], [ "Wan", "Qingzhou", "" ], [ "Akolkar", "Himanshu", "" ], [ "Xiong", "Feng", "" ], [ "Shi", "Bertram", "" ], [ "Benosman", "Ryad", "" ] ]
Memristors have emerged as a promising technology for efficient neuromorphic architectures owing to their ability to act as programmable synapses, combining processing and memory into a single device. Although they are most commonly used for static encoding of synaptic weights, recent work has begun to investigate the ...
1803.08601
Carl Yang
Carl Yang, Aydin Buluc and John D. Owens
Design Principles for Sparse Matrix Multiplication on the GPU
16 pages, 7 figures, International European Conference on Parallel and Distributed Computing (Euro-Par) 2018
null
null
null
cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We implement two novel algorithms for sparse-matrix dense-matrix multiplication (SpMM) on the GPU. Our algorithms expect the sparse input in the popular compressed-sparse-row (CSR) format and thus do not require expensive format conversion. While previous SpMM work concentrates on thread-level parallelism, we additio...
[ { "created": "Thu, 22 Mar 2018 22:31:17 GMT", "version": "v1" }, { "created": "Tue, 12 Jun 2018 06:30:45 GMT", "version": "v2" } ]
2018-06-13
[ [ "Yang", "Carl", "" ], [ "Buluc", "Aydin", "" ], [ "Owens", "John D.", "" ] ]
We implement two novel algorithms for sparse-matrix dense-matrix multiplication (SpMM) on the GPU. Our algorithms expect the sparse input in the popular compressed-sparse-row (CSR) format and thus do not require expensive format conversion. While previous SpMM work concentrates on thread-level parallelism, we additiona...
1807.09224
Pierre Augier
Pierre Augier, Ashwin Vishnu Mohanan, Cyrille Bonamy
FluidDyn: a Python open-source framework for research and teaching in fluid dynamics
null
null
10.5334/jors.237
null
cs.OH
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
FluidDyn is a project to foster open-science and open-source in the fluid dynamics community. It is thought of as a research project to channel open-source dynamics, methods and tools to do science. We propose a set of Python packages forming a framework to study fluid dynamics with different methods, in particular l...
[ { "created": "Tue, 3 Jul 2018 10:04:39 GMT", "version": "v1" } ]
2019-04-10
[ [ "Augier", "Pierre", "" ], [ "Mohanan", "Ashwin Vishnu", "" ], [ "Bonamy", "Cyrille", "" ] ]
FluidDyn is a project to foster open-science and open-source in the fluid dynamics community. It is thought of as a research project to channel open-source dynamics, methods and tools to do science. We propose a set of Python packages forming a framework to study fluid dynamics with different methods, in particular lab...
2302.11458
Manuel Stoiber
Manuel Stoiber, Mariam Elsayed, Anne E. Reichert, Florian Steidle, Dongheui Lee, Rudolph Triebel
Fusing Visual Appearance and Geometry for Multi-modality 6DoF Object Tracking
Submitted to IEEE/RSJ International Conference on Intelligent Robots
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
In many applications of advanced robotic manipulation, six degrees of freedom (6DoF) object pose estimates are continuously required. In this work, we develop a multi-modality tracker that fuses information from visual appearance and geometry to estimate object poses. The algorithm extends our previous method ICG, wh...
[ { "created": "Wed, 22 Feb 2023 15:53:00 GMT", "version": "v1" } ]
2023-02-23
[ [ "Stoiber", "Manuel", "" ], [ "Elsayed", "Mariam", "" ], [ "Reichert", "Anne E.", "" ], [ "Steidle", "Florian", "" ], [ "Lee", "Dongheui", "" ], [ "Triebel", "Rudolph", "" ] ]
In many applications of advanced robotic manipulation, six degrees of freedom (6DoF) object pose estimates are continuously required. In this work, we develop a multi-modality tracker that fuses information from visual appearance and geometry to estimate object poses. The algorithm extends our previous method ICG, whic...
2301.11313
Ola Shorinw
Ola Shorinwa, Trevor Halsted, Javier Yu, Mac Schwager
Distributed Optimization Methods for Multi-Robot Systems: Part I -- A Tutorial
null
null
null
null
cs.RO cs.MA
http://creativecommons.org/licenses/by/4.0/
Distributed optimization provides a framework for deriving distributed algorithms for a variety of multi-robot problems. This tutorial constitutes the first part of a two-part series on distributed optimization applied to multi-robot problems, which seeks to advance the application of distributed optimization in robo...
[ { "created": "Thu, 26 Jan 2023 18:52:07 GMT", "version": "v1" } ]
2023-01-27
[ [ "Shorinwa", "Ola", "" ], [ "Halsted", "Trevor", "" ], [ "Yu", "Javier", "" ], [ "Schwager", "Mac", "" ] ]
Distributed optimization provides a framework for deriving distributed algorithms for a variety of multi-robot problems. This tutorial constitutes the first part of a two-part series on distributed optimization applied to multi-robot problems, which seeks to advance the application of distributed optimization in roboti...
1902.09941
Jian Zhang
Runsheng Zhang, jian zhang, Yaping Huang and Qi Zou
Unsupervised Part Mining for Fine-grained Image Classification
10 pages,4 figures
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Fine-grained image classification remains challenging due to the large intra-class variance and small inter-class variance. Since the subtle visual differences are only in local regions of discriminative parts among subcategories, part localization is a key issue for fine-grained image classification. Most existing a...
[ { "created": "Tue, 26 Feb 2019 14:04:58 GMT", "version": "v1" }, { "created": "Thu, 31 Mar 2022 13:20:38 GMT", "version": "v2" } ]
2022-04-01
[ [ "Zhang", "Runsheng", "" ], [ "zhang", "jian", "" ], [ "Huang", "Yaping", "" ], [ "Zou", "Qi", "" ] ]
Fine-grained image classification remains challenging due to the large intra-class variance and small inter-class variance. Since the subtle visual differences are only in local regions of discriminative parts among subcategories, part localization is a key issue for fine-grained image classification. Most existing app...
2206.04667
Zhirong Wu
Zhirong Wu, Zihang Lai, Xiao Sun, Stephen Lin
Extreme Masking for Learning Instance and Distributed Visual Representations
Accepted in TMLR
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
The paper presents a scalable approach for learning spatially distributed visual representations over individual tokens and a holistic instance representation simultaneously. We use self-attention blocks to represent spatially distributed tokens, followed by cross-attention blocks to aggregate the holistic image inst...
[ { "created": "Thu, 9 Jun 2022 17:59:43 GMT", "version": "v1" }, { "created": "Wed, 8 Mar 2023 09:51:25 GMT", "version": "v2" } ]
2023-03-09
[ [ "Wu", "Zhirong", "" ], [ "Lai", "Zihang", "" ], [ "Sun", "Xiao", "" ], [ "Lin", "Stephen", "" ] ]
The paper presents a scalable approach for learning spatially distributed visual representations over individual tokens and a holistic instance representation simultaneously. We use self-attention blocks to represent spatially distributed tokens, followed by cross-attention blocks to aggregate the holistic image instan...
2212.05420
Mike Thelwall Prof
Mike Thelwall, Kayvan Kousha, Mahshid Abdoli, Emma Stuart, Meiko Makita, Paul Wilson, Jonathan Levitt
Terms in journal articles associating with high quality: Can qualitative research be world-leading?
null
null
null
null
cs.DL
http://creativecommons.org/licenses/by/4.0/
Purpose: Scholars often aim to conduct high quality research and their success is judged primarily by peer reviewers. Research quality is difficult for either group to identify, however, and misunderstandings can reduce the efficiency of the scientific enterprise. In response, we use a novel term association strategy...
[ { "created": "Sun, 11 Dec 2022 06:12:31 GMT", "version": "v1" } ]
2022-12-13
[ [ "Thelwall", "Mike", "" ], [ "Kousha", "Kayvan", "" ], [ "Abdoli", "Mahshid", "" ], [ "Stuart", "Emma", "" ], [ "Makita", "Meiko", "" ], [ "Wilson", "Paul", "" ], [ "Levitt", "Jonathan", "" ] ]
Purpose: Scholars often aim to conduct high quality research and their success is judged primarily by peer reviewers. Research quality is difficult for either group to identify, however, and misunderstandings can reduce the efficiency of the scientific enterprise. In response, we use a novel term association strategy t...
2405.05853
Zheming Zuo
Zheming Zuo, Joseph Smith, Jonathan Stonehouse, Boguslaw Obara
Robust and Explainable Fine-Grained Visual Classification with Transfer Learning: A Dual-Carriageway Framework
Accepted in the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2024 workshop
null
null
null
cs.CV
http://creativecommons.org/licenses/by-nc-sa/4.0/
In the realm of practical fine-grained visual classification applications rooted in deep learning, a common scenario involves training a model using a pre-existing dataset. Subsequently, a new dataset becomes available, prompting the desire to make a pivotal decision for achieving enhanced and leveraged inference per...
[ { "created": "Thu, 9 May 2024 15:41:10 GMT", "version": "v1" } ]
2024-05-10
[ [ "Zuo", "Zheming", "" ], [ "Smith", "Joseph", "" ], [ "Stonehouse", "Jonathan", "" ], [ "Obara", "Boguslaw", "" ] ]
In the realm of practical fine-grained visual classification applications rooted in deep learning, a common scenario involves training a model using a pre-existing dataset. Subsequently, a new dataset becomes available, prompting the desire to make a pivotal decision for achieving enhanced and leveraged inference perfo...
2210.09197
Zhixue Zhao
Zhixue Zhao, George Chrysostomou, Kalina Bontcheva, Nikolaos Aletras
On the Impact of Temporal Concept Drift on Model Explanations
Accepted at EMNLP Findings 2022
null
null
null
cs.CL cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Explanation faithfulness of model predictions in natural language processing is typically evaluated on held-out data from the same temporal distribution as the training data (i.e. synchronous settings). While model performance often deteriorates due to temporal variation (i.e. temporal concept drift), it is currently...
[ { "created": "Mon, 17 Oct 2022 15:53:09 GMT", "version": "v1" } ]
2022-10-18
[ [ "Zhao", "Zhixue", "" ], [ "Chrysostomou", "George", "" ], [ "Bontcheva", "Kalina", "" ], [ "Aletras", "Nikolaos", "" ] ]
Explanation faithfulness of model predictions in natural language processing is typically evaluated on held-out data from the same temporal distribution as the training data (i.e. synchronous settings). While model performance often deteriorates due to temporal variation (i.e. temporal concept drift), it is currently u...
2303.02601
Maria Lymperaiou
Theodoti Stoikou, Maria Lymperaiou, Giorgos Stamou
Knowledge-Based Counterfactual Queries for Visual Question Answering
null
AAAI MAKE 2023
null
null
cs.CL
http://creativecommons.org/licenses/by-nc-nd/4.0/
Visual Question Answering (VQA) has been a popular task that combines vision and language, with numerous relevant implementations in literature. Even though there are some attempts that approach explainability and robustness issues in VQA models, very few of them employ counterfactuals as a means of probing such chal...
[ { "created": "Sun, 5 Mar 2023 08:00:30 GMT", "version": "v1" } ]
2024-05-06
[ [ "Stoikou", "Theodoti", "" ], [ "Lymperaiou", "Maria", "" ], [ "Stamou", "Giorgos", "" ] ]
Visual Question Answering (VQA) has been a popular task that combines vision and language, with numerous relevant implementations in literature. Even though there are some attempts that approach explainability and robustness issues in VQA models, very few of them employ counterfactuals as a means of probing such challe...
2406.08101
Qianli Wang
Qianli Wang, Tatiana Anikina, Nils Feldhus, Simon Ostermann, Sebastian M\"oller
CoXQL: A Dataset for Parsing Explanation Requests in Conversational XAI Systems
4 pages, short paper
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
Conversational explainable artificial intelligence (ConvXAI) systems based on large language models (LLMs) have garnered significant interest from the research community in natural language processing (NLP) and human-computer interaction (HCI). Such systems can provide answers to user questions about explanations in ...
[ { "created": "Wed, 12 Jun 2024 11:27:10 GMT", "version": "v1" }, { "created": "Thu, 13 Jun 2024 03:16:47 GMT", "version": "v2" } ]
2024-06-14
[ [ "Wang", "Qianli", "" ], [ "Anikina", "Tatiana", "" ], [ "Feldhus", "Nils", "" ], [ "Ostermann", "Simon", "" ], [ "Möller", "Sebastian", "" ] ]
Conversational explainable artificial intelligence (ConvXAI) systems based on large language models (LLMs) have garnered significant interest from the research community in natural language processing (NLP) and human-computer interaction (HCI). Such systems can provide answers to user questions about explanations in di...
2209.07088
Zhengming Zhou
Zhengming Zhou and Qiulei Dong
Self-distilled Feature Aggregation for Self-supervised Monocular Depth Estimation
Accepted to ECCV 2022
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Self-supervised monocular depth estimation has received much attention recently in computer vision. Most of the existing works in literature aggregate multi-scale features for depth prediction via either straightforward concatenation or element-wise addition, however, such feature aggregation operations generally neg...
[ { "created": "Thu, 15 Sep 2022 07:00:52 GMT", "version": "v1" } ]
2022-09-16
[ [ "Zhou", "Zhengming", "" ], [ "Dong", "Qiulei", "" ] ]
Self-supervised monocular depth estimation has received much attention recently in computer vision. Most of the existing works in literature aggregate multi-scale features for depth prediction via either straightforward concatenation or element-wise addition, however, such feature aggregation operations generally negle...
2311.13681
Joo Chan Lee
Joo Chan Lee, Daniel Rho, Xiangyu Sun, Jong Hwan Ko, Eunbyung Park
Compact 3D Gaussian Representation for Radiance Field
Project page: http://maincold2.github.io/c3dgs/
null
null
null
cs.CV cs.GR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Neural Radiance Fields (NeRFs) have demonstrated remarkable potential in capturing complex 3D scenes with high fidelity. However, one persistent challenge that hinders the widespread adoption of NeRFs is the computational bottleneck due to the volumetric rendering. On the other hand, 3D Gaussian splatting (3DGS) has ...
[ { "created": "Wed, 22 Nov 2023 20:31:16 GMT", "version": "v1" }, { "created": "Thu, 15 Feb 2024 13:52:53 GMT", "version": "v2" } ]
2024-02-16
[ [ "Lee", "Joo Chan", "" ], [ "Rho", "Daniel", "" ], [ "Sun", "Xiangyu", "" ], [ "Ko", "Jong Hwan", "" ], [ "Park", "Eunbyung", "" ] ]
Neural Radiance Fields (NeRFs) have demonstrated remarkable potential in capturing complex 3D scenes with high fidelity. However, one persistent challenge that hinders the widespread adoption of NeRFs is the computational bottleneck due to the volumetric rendering. On the other hand, 3D Gaussian splatting (3DGS) has re...
2006.02903
Pengzhen Ren
Pengzhen Ren, Yun Xiao, Xiaojun Chang, Po-Yao Huang, Zhihui Li, Xiaojiang Chen, and Xin Wang
A Comprehensive Survey of Neural Architecture Search: Challenges and Solutions
Accepted by ACM Computing Surveys 2021
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Deep learning has made breakthroughs and substantial in many fields due to its powerful automatic representation capabilities. It has been proven that neural architecture design is crucial to the feature representation of data and the final performance. However, the design of the neural architecture heavily relies on...
[ { "created": "Mon, 1 Jun 2020 13:08:03 GMT", "version": "v1" }, { "created": "Mon, 18 Jan 2021 03:56:19 GMT", "version": "v2" }, { "created": "Tue, 2 Mar 2021 08:35:02 GMT", "version": "v3" } ]
2021-03-03
[ [ "Ren", "Pengzhen", "" ], [ "Xiao", "Yun", "" ], [ "Chang", "Xiaojun", "" ], [ "Huang", "Po-Yao", "" ], [ "Li", "Zhihui", "" ], [ "Chen", "Xiaojiang", "" ], [ "Wang", "Xin", "" ] ]
Deep learning has made breakthroughs and substantial in many fields due to its powerful automatic representation capabilities. It has been proven that neural architecture design is crucial to the feature representation of data and the final performance. However, the design of the neural architecture heavily relies on t...
2406.17714
Purva Pruthi
Purva Pruthi and David Jensen
Compositional Models for Estimating Causal Effects
null
null
null
null
cs.AI cs.LG stat.ME
http://creativecommons.org/licenses/by/4.0/
Many real-world systems can be represented as sets of interacting components. Examples of such systems include computational systems such as query processors, natural systems such as cells, and social systems such as families. Many approaches have been proposed in traditional (associational) machine learning to model...
[ { "created": "Tue, 25 Jun 2024 16:56:17 GMT", "version": "v1" } ]
2024-06-26
[ [ "Pruthi", "Purva", "" ], [ "Jensen", "David", "" ] ]
Many real-world systems can be represented as sets of interacting components. Examples of such systems include computational systems such as query processors, natural systems such as cells, and social systems such as families. Many approaches have been proposed in traditional (associational) machine learning to model s...
1711.08475
Aleksander Cis{\l}ak
Aleksander Cis{\l}ak, Szymon Grabowski
Lightweight Fingerprints for Fast Approximate Keyword Matching Using Bitwise Operations
16 pages, 1 figure, 4 tables
null
null
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We aim to speed up approximate keyword matching by storing a lightweight, fixed-size block of data for each string, called a fingerprint. These work in a similar way to hash values; however, they can be also used for matching with errors. They store information regarding symbol occurrences using individual bits, and ...
[ { "created": "Wed, 22 Nov 2017 19:13:08 GMT", "version": "v1" } ]
2017-11-27
[ [ "Cisłak", "Aleksander", "" ], [ "Grabowski", "Szymon", "" ] ]
We aim to speed up approximate keyword matching by storing a lightweight, fixed-size block of data for each string, called a fingerprint. These work in a similar way to hash values; however, they can be also used for matching with errors. They store information regarding symbol occurrences using individual bits, and th...
2206.12540
David Munechika
David Munechika, Zijie J. Wang, Jack Reidy, Josh Rubin, Krishna Gade, Krishnaram Kenthapadi, Duen Horng Chau
Visual Auditor: Interactive Visualization for Detection and Summarization of Model Biases
null
null
null
null
cs.HC cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
As machine learning (ML) systems become increasingly widespread, it is necessary to audit these systems for biases prior to their deployment. Recent research has developed algorithms for effectively identifying intersectional bias in the form of interpretable, underperforming subsets (or slices) of the data. However,...
[ { "created": "Sat, 25 Jun 2022 02:48:27 GMT", "version": "v1" } ]
2022-06-28
[ [ "Munechika", "David", "" ], [ "Wang", "Zijie J.", "" ], [ "Reidy", "Jack", "" ], [ "Rubin", "Josh", "" ], [ "Gade", "Krishna", "" ], [ "Kenthapadi", "Krishnaram", "" ], [ "Chau", "Duen Horng", "" ] ]
As machine learning (ML) systems become increasingly widespread, it is necessary to audit these systems for biases prior to their deployment. Recent research has developed algorithms for effectively identifying intersectional bias in the form of interpretable, underperforming subsets (or slices) of the data. However, t...
2008.04411
Giuseppe Patane'
Giuseppe Patan\`e
Meshless Approximation and Helmholtz-Hodge Decomposition of Vector Fields
null
null
null
null
cs.GR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The analysis of vector fields is crucial for the understanding of several physical phenomena, such as natural events (e.g., analysis of waves), diffusive processes, electric and electromagnetic fields. While previous work has been focused mainly on the analysis of 2D or 3D vector fields on volumes or surfaces, we add...
[ { "created": "Mon, 10 Aug 2020 20:58:47 GMT", "version": "v1" } ]
2020-08-12
[ [ "Patanè", "Giuseppe", "" ] ]
The analysis of vector fields is crucial for the understanding of several physical phenomena, such as natural events (e.g., analysis of waves), diffusive processes, electric and electromagnetic fields. While previous work has been focused mainly on the analysis of 2D or 3D vector fields on volumes or surfaces, we addre...
2402.09760
Hongjin Qian
Hongjin Qian, Zheng Liu, Kelong Mao, Yujia Zhou, Zhicheng Dou
Grounding Language Model with Chunking-Free In-Context Retrieval
null
null
null
null
cs.CL cs.AI cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper presents a novel Chunking-Free In-Context (CFIC) retrieval approach, specifically tailored for Retrieval-Augmented Generation (RAG) systems. Traditional RAG systems often struggle with grounding responses using precise evidence text due to the challenges of processing lengthy documents and filtering out ir...
[ { "created": "Thu, 15 Feb 2024 07:22:04 GMT", "version": "v1" } ]
2024-02-16
[ [ "Qian", "Hongjin", "" ], [ "Liu", "Zheng", "" ], [ "Mao", "Kelong", "" ], [ "Zhou", "Yujia", "" ], [ "Dou", "Zhicheng", "" ] ]
This paper presents a novel Chunking-Free In-Context (CFIC) retrieval approach, specifically tailored for Retrieval-Augmented Generation (RAG) systems. Traditional RAG systems often struggle with grounding responses using precise evidence text due to the challenges of processing lengthy documents and filtering out irre...
1903.09030
Juan Maro\~nas
Juan Maro\~nas, Roberto Paredes, Daniel Ramos
Generative Models For Deep Learning with Very Scarce Data
null
null
10.1007/978-3-030-13469-3_3
null
cs.LG stat.ML
http://creativecommons.org/publicdomain/zero/1.0/
The goal of this paper is to deal with a data scarcity scenario where deep learning techniques use to fail. We compare the use of two well established techniques, Restricted Boltzmann Machines and Variational Auto-encoders, as generative models in order to increase the training set in a classification framework. Esse...
[ { "created": "Thu, 21 Mar 2019 14:38:45 GMT", "version": "v1" } ]
2020-03-02
[ [ "Maroñas", "Juan", "" ], [ "Paredes", "Roberto", "" ], [ "Ramos", "Daniel", "" ] ]
The goal of this paper is to deal with a data scarcity scenario where deep learning techniques use to fail. We compare the use of two well established techniques, Restricted Boltzmann Machines and Variational Auto-encoders, as generative models in order to increase the training set in a classification framework. Essent...
cs/0006007
Stephen Marsand
Stephen Marsland, Ulrich Nehmzow and Jonathan Shapiro
Novelty Detection on a Mobile Robot Using Habituation
10 pages, 6 figures. In From Animals to Animats, The Sixth International Conference on Simulation of Adaptive Behaviour, Paris, 2000
null
null
null
cs.RO cs.NE nlin.AO
null
In this paper a novelty filter is introduced which allows a robot operating in an un structured environment to produce a self-organised model of its surroundings and to detect deviations from the learned model. The environment is perceived using the rob ot's 16 sonar sensors. The algorithm produces a novelty measure ...
[ { "created": "Fri, 2 Jun 2000 12:33:13 GMT", "version": "v1" } ]
2007-05-23
[ [ "Marsland", "Stephen", "" ], [ "Nehmzow", "Ulrich", "" ], [ "Shapiro", "Jonathan", "" ] ]
In this paper a novelty filter is introduced which allows a robot operating in an un structured environment to produce a self-organised model of its surroundings and to detect deviations from the learned model. The environment is perceived using the rob ot's 16 sonar sensors. The algorithm produces a novelty measure fo...
2208.12125
Yuci Han
Yuci Han, Jianli Wei, Alper Yilmaz
UAS Navigation in the Real World Using Visual Observation
null
null
null
null
cs.RO cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper presents a novel end-to-end Unmanned Aerial System (UAS) navigation approach for long-range visual navigation in the real world. Inspired by dual-process visual navigation system of human's instinct: environment understanding and landmark recognition, we formulate the UAS navigation task into two same phas...
[ { "created": "Thu, 25 Aug 2022 14:40:53 GMT", "version": "v1" } ]
2022-08-26
[ [ "Han", "Yuci", "" ], [ "Wei", "Jianli", "" ], [ "Yilmaz", "Alper", "" ] ]
This paper presents a novel end-to-end Unmanned Aerial System (UAS) navigation approach for long-range visual navigation in the real world. Inspired by dual-process visual navigation system of human's instinct: environment understanding and landmark recognition, we formulate the UAS navigation task into two same phases...
2112.01479
Subarna Tripathi
Sourya Roy, Kyle Min, Subarna Tripathi, Tanaya Guha and Somdeb Majumdar
Learning Spatial-Temporal Graphs for Active Speaker Detection
10 pages
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We address the problem of active speaker detection through a new framework, called SPELL, that learns long-range multimodal graphs to encode the inter-modal relationship between audio and visual data. We cast active speaker detection as a node classification task that is aware of longer-term dependencies. We first co...
[ { "created": "Thu, 2 Dec 2021 18:29:07 GMT", "version": "v1" }, { "created": "Fri, 3 Dec 2021 19:41:06 GMT", "version": "v2" } ]
2021-12-07
[ [ "Roy", "Sourya", "" ], [ "Min", "Kyle", "" ], [ "Tripathi", "Subarna", "" ], [ "Guha", "Tanaya", "" ], [ "Majumdar", "Somdeb", "" ] ]
We address the problem of active speaker detection through a new framework, called SPELL, that learns long-range multimodal graphs to encode the inter-modal relationship between audio and visual data. We cast active speaker detection as a node classification task that is aware of longer-term dependencies. We first cons...
2010.14244
Dr. Vinita Jindal
Vinita Jindal and Punam Bedi
GMACO-P: GPU assisted Preemptive MACO algorithm for enabling Smart Transportation
13 pages
null
null
null
cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Vehicular Ad-hoc NETworks (VANETs) are developing at a very fast pace to enable smart transportation in urban cities, by designing some mechanisms for decreasing travel time for commuters by reducing congestion. Inefficient Traffic signals and routing mechanisms are the major factors that contribute to the increase o...
[ { "created": "Tue, 27 Oct 2020 12:38:10 GMT", "version": "v1" } ]
2020-10-28
[ [ "Jindal", "Vinita", "" ], [ "Bedi", "Punam", "" ] ]
Vehicular Ad-hoc NETworks (VANETs) are developing at a very fast pace to enable smart transportation in urban cities, by designing some mechanisms for decreasing travel time for commuters by reducing congestion. Inefficient Traffic signals and routing mechanisms are the major factors that contribute to the increase of ...
2003.07383
Jacopo Mauro
Michael Lienhardt, Ferruccio Damiani, Einar Broch Johnsen, Jacopo Mauro
Lazy Product Discovery in Huge Configuration Spaces
null
null
null
null
cs.SE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Highly-configurable software systems can have thousands of interdependent configuration options across different subsystems. In the resulting configuration space, discovering a valid product configuration for some selected options can be complex and error prone. The configuration space can be organized using a featur...
[ { "created": "Mon, 16 Mar 2020 18:06:26 GMT", "version": "v1" } ]
2020-03-18
[ [ "Lienhardt", "Michael", "" ], [ "Damiani", "Ferruccio", "" ], [ "Johnsen", "Einar Broch", "" ], [ "Mauro", "Jacopo", "" ] ]
Highly-configurable software systems can have thousands of interdependent configuration options across different subsystems. In the resulting configuration space, discovering a valid product configuration for some selected options can be complex and error prone. The configuration space can be organized using a feature ...
1812.06300
Patrick Spettel
Patrick Spettel and Hans-Georg Beyer
Analysis of the $(\mu/\mu_I,\lambda)$-$\sigma$-Self-Adaptation Evolution Strategy with Repair by Projection Applied to a Conically Constrained Problem
This is a PREPRINT of an article submitted to IEEE Transactions On Evolutionary Computation. It is currently under review. Due to size limitations, this manuscript comprises figures with reduced resolution. 10 pages + supplementary material. Copyright 2018 IEEE. The work was supported by the Austrian Science Fu...
null
null
null
cs.NE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A theoretical performance analysis of the $(\mu/\mu_I,\lambda)$-$\sigma$-Self-Adaptation Evolution Strategy ($\sigma$SA-ES) is presented considering a conically constrained problem. Infeasible offspring are repaired using projection onto the boundary of the feasibility region. Closed-form approximations are used for ...
[ { "created": "Sat, 15 Dec 2018 14:48:40 GMT", "version": "v1" } ]
2018-12-18
[ [ "Spettel", "Patrick", "" ], [ "Beyer", "Hans-Georg", "" ] ]
A theoretical performance analysis of the $(\mu/\mu_I,\lambda)$-$\sigma$-Self-Adaptation Evolution Strategy ($\sigma$SA-ES) is presented considering a conically constrained problem. Infeasible offspring are repaired using projection onto the boundary of the feasibility region. Closed-form approximations are used for th...
1511.03524
Buddhadeb Sau
B. Sau and S. Mukhopadhyaya and K. Mukhopadhyaya
MAINT: Localization of Mobile Sensors with Energy Control
null
null
null
null
cs.DC cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Localization is an important issue for Wireless Sensor Networks (WSN). A mobile sensor may change its position rapidly and thus require localization calls frequently. A localization may require network wide information and increase traffic over the network. It dissipates valuable energy for message communication. Thu...
[ { "created": "Tue, 10 Nov 2015 07:22:10 GMT", "version": "v1" } ]
2015-11-12
[ [ "Sau", "B.", "" ], [ "Mukhopadhyaya", "S.", "" ], [ "Mukhopadhyaya", "K.", "" ] ]
Localization is an important issue for Wireless Sensor Networks (WSN). A mobile sensor may change its position rapidly and thus require localization calls frequently. A localization may require network wide information and increase traffic over the network. It dissipates valuable energy for message communication. Thus ...
2405.15863
Chang Li
Chang Li, Ruoyu Wang, Lijuan Liu, Jun Du, Yixuan Sun, Zilu Guo, Zhenrong Zhang, Yuan Jiang
Quality-aware Masked Diffusion Transformer for Enhanced Music Generation
null
null
null
null
cs.SD cs.AI eess.AS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In recent years, diffusion-based text-to-music (TTM) generation has gained prominence, offering a novel approach to synthesizing musical content from textual descriptions. Achieving high accuracy and diversity in this generation process requires extensive, high-quality data, which often constitutes only a fraction of...
[ { "created": "Fri, 24 May 2024 18:09:27 GMT", "version": "v1" } ]
2024-05-28
[ [ "Li", "Chang", "" ], [ "Wang", "Ruoyu", "" ], [ "Liu", "Lijuan", "" ], [ "Du", "Jun", "" ], [ "Sun", "Yixuan", "" ], [ "Guo", "Zilu", "" ], [ "Zhang", "Zhenrong", "" ], [ "Jiang", "Yuan", ""...
In recent years, diffusion-based text-to-music (TTM) generation has gained prominence, offering a novel approach to synthesizing musical content from textual descriptions. Achieving high accuracy and diversity in this generation process requires extensive, high-quality data, which often constitutes only a fraction of a...
1310.1693
Borhan Sanandaji
Borhan M. Sanandaji, He Hao, Kameshwar Poolla, and Tyrone L. Vincent
Improved Battery Models of an Aggregation of Thermostatically Controlled Loads for Frequency Regulation
to appear in the 2014 American Control Conference - ACC
null
null
null
cs.SY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recently it has been shown that an aggregation of Thermostatically Controlled Loads (TCLs) can be utilized to provide fast regulating reserve service for power grids and the behavior of the aggregation can be captured by a stochastic battery with dissipation. In this paper, we address two practical issues associated ...
[ { "created": "Mon, 7 Oct 2013 07:44:38 GMT", "version": "v1" }, { "created": "Tue, 8 Apr 2014 01:31:35 GMT", "version": "v2" } ]
2014-04-09
[ [ "Sanandaji", "Borhan M.", "" ], [ "Hao", "He", "" ], [ "Poolla", "Kameshwar", "" ], [ "Vincent", "Tyrone L.", "" ] ]
Recently it has been shown that an aggregation of Thermostatically Controlled Loads (TCLs) can be utilized to provide fast regulating reserve service for power grids and the behavior of the aggregation can be captured by a stochastic battery with dissipation. In this paper, we address two practical issues associated wi...
1509.06321
Wojciech Samek
Wojciech Samek, Alexander Binder, Gr\'egoire Montavon, Sebastian Bach, Klaus-Robert M\"uller
Evaluating the visualization of what a Deep Neural Network has learned
13 pages, 8 Figures
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Deep Neural Networks (DNNs) have demonstrated impressive performance in complex machine learning tasks such as image classification or speech recognition. However, due to their multi-layer nonlinear structure, they are not transparent, i.e., it is hard to grasp what makes them arrive at a particular classification or...
[ { "created": "Mon, 21 Sep 2015 17:36:22 GMT", "version": "v1" } ]
2015-09-22
[ [ "Samek", "Wojciech", "" ], [ "Binder", "Alexander", "" ], [ "Montavon", "Grégoire", "" ], [ "Bach", "Sebastian", "" ], [ "Müller", "Klaus-Robert", "" ] ]
Deep Neural Networks (DNNs) have demonstrated impressive performance in complex machine learning tasks such as image classification or speech recognition. However, due to their multi-layer nonlinear structure, they are not transparent, i.e., it is hard to grasp what makes them arrive at a particular classification or r...
2209.13792
Gustavo Lacerda
Gustavo Cunha Lacerda, Raimundo Claudio da Silva Vasconcelos
A Machine Learning Approach for DeepFake Detection
4 pages, accepted for presentation at the SIBGRAPI 2022
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
With the spread of DeepFake techniques, this technology has become quite accessible and good enough that there is concern about its malicious use. Faced with this problem, detecting forged faces is of utmost importance to ensure security and avoid socio-political problems, both on a global and private scale. This pap...
[ { "created": "Wed, 28 Sep 2022 02:46:04 GMT", "version": "v1" } ]
2022-09-29
[ [ "Lacerda", "Gustavo Cunha", "" ], [ "Vasconcelos", "Raimundo Claudio da Silva", "" ] ]
With the spread of DeepFake techniques, this technology has become quite accessible and good enough that there is concern about its malicious use. Faced with this problem, detecting forged faces is of utmost importance to ensure security and avoid socio-political problems, both on a global and private scale. This paper...
2305.03953
Xu Chen
Xu Chen and Zida Cheng and Shuai Xiao and Xiaoyi Zeng and Weilin Huang
Cross-domain Augmentation Networks for Click-Through Rate Prediction
null
null
null
null
cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Data sparsity is an important issue for click-through rate (CTR) prediction, particularly when user-item interactions is too sparse to learn a reliable model. Recently, many works on cross-domain CTR (CDCTR) prediction have been developed in an effort to leverage meaningful data from a related domain. However, most e...
[ { "created": "Sat, 6 May 2023 06:37:52 GMT", "version": "v1" }, { "created": "Tue, 9 May 2023 08:43:29 GMT", "version": "v2" } ]
2023-05-10
[ [ "Chen", "Xu", "" ], [ "Cheng", "Zida", "" ], [ "Xiao", "Shuai", "" ], [ "Zeng", "Xiaoyi", "" ], [ "Huang", "Weilin", "" ] ]
Data sparsity is an important issue for click-through rate (CTR) prediction, particularly when user-item interactions is too sparse to learn a reliable model. Recently, many works on cross-domain CTR (CDCTR) prediction have been developed in an effort to leverage meaningful data from a related domain. However, most exi...
1406.2395
Ines Dutra
Ezilda Almeida, Pedro Ferreira, Tiago Vinhoza, In\^es Dutra, Jingwei Li, Yirong Wu, Elizabeth Burnside
ExpertBayes: Automatically refining manually built Bayesian networks
14 pages
null
null
null
cs.AI cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Bayesian network structures are usually built using only the data and starting from an empty network or from a naive Bayes structure. Very often, in some domains, like medicine, a prior structure knowledge is already known. This structure can be automatically or manually refined in search for better performance model...
[ { "created": "Tue, 10 Jun 2014 00:50:05 GMT", "version": "v1" } ]
2014-06-11
[ [ "Almeida", "Ezilda", "" ], [ "Ferreira", "Pedro", "" ], [ "Vinhoza", "Tiago", "" ], [ "Dutra", "Inês", "" ], [ "Li", "Jingwei", "" ], [ "Wu", "Yirong", "" ], [ "Burnside", "Elizabeth", "" ] ]
Bayesian network structures are usually built using only the data and starting from an empty network or from a naive Bayes structure. Very often, in some domains, like medicine, a prior structure knowledge is already known. This structure can be automatically or manually refined in search for better performance models....
2011.05119
Mostafa Khalaji
Mostafa Khalaji
TRSM-RS: A Movie Recommender System Based on Users' Gender and New Weighted Similarity Measure
11 pages, 17th Iran Media Technology Exhibition and Conference, At: Tehran, Iran, November 2020
null
null
null
cs.IR
http://creativecommons.org/licenses/by/4.0/
With the growing data on the Internet, recommender systems have been able to predict users' preferences and offer related movies. Collaborative filtering is one of the most popular algorithms in these systems. The main purpose of collaborative filtering is to find the users or the same items using the rating matrix. ...
[ { "created": "Tue, 10 Nov 2020 14:41:40 GMT", "version": "v1" } ]
2020-11-11
[ [ "Khalaji", "Mostafa", "" ] ]
With the growing data on the Internet, recommender systems have been able to predict users' preferences and offer related movies. Collaborative filtering is one of the most popular algorithms in these systems. The main purpose of collaborative filtering is to find the users or the same items using the rating matrix. By...
2403.08650
Wentao Jiang
Wentao Jiang, Yige Zhang, Shaozhong Zheng, Si Liu, Shuicheng Yan
Data Augmentation in Human-Centric Vision
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This survey presents a comprehensive analysis of data augmentation techniques in human-centric vision tasks, a first of its kind in the field. It delves into a wide range of research areas including person ReID, human parsing, human pose estimation, and pedestrian detection, addressing the significant challenges pose...
[ { "created": "Wed, 13 Mar 2024 16:05:18 GMT", "version": "v1" } ]
2024-03-14
[ [ "Jiang", "Wentao", "" ], [ "Zhang", "Yige", "" ], [ "Zheng", "Shaozhong", "" ], [ "Liu", "Si", "" ], [ "Yan", "Shuicheng", "" ] ]
This survey presents a comprehensive analysis of data augmentation techniques in human-centric vision tasks, a first of its kind in the field. It delves into a wide range of research areas including person ReID, human parsing, human pose estimation, and pedestrian detection, addressing the significant challenges posed ...
0904.3711
Florentina Pintea
Mihai Timis
Output Width Signal Control In Asynchronous Digital Systems Using External Clock Signal
6 pages,exposed on 1st "European Conference on Computer Sciences & Applications" - XA2006, Timisoara, Romania
Ann. Univ. Tibiscus Comp. Sci. Series IV (2006), 237-242
null
null
cs.OH
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In present paper, I propose a method for resolving the timing delays for output signals from an asynchronous sequential system. It will be used an example of an asynchronous sequential system that will set up an output signal when an input signal will be set up. The width of the output signal depends on the input sig...
[ { "created": "Thu, 23 Apr 2009 14:45:42 GMT", "version": "v1" } ]
2009-04-24
[ [ "Timis", "Mihai", "" ] ]
In present paper, I propose a method for resolving the timing delays for output signals from an asynchronous sequential system. It will be used an example of an asynchronous sequential system that will set up an output signal when an input signal will be set up. The width of the output signal depends on the input signa...
2307.02103
Abdelhadi Soudi
Abdelhadi Soudi, Manal El Hakkaoui, Kristof Van Laerhoven
Do predictability factors towards signing avatars hold across cultures?
5 pages, Proceedings of the ICASSP 2023 8th Workshop on Sign Language Translation and Avatar Technology, Rhodes Island, Greece, June 10, 2023
null
null
null
cs.CL
http://creativecommons.org/licenses/by-nc-sa/4.0/
Avatar technology can offer accessibility possibilities and improve the Deaf-and-Hard of Hearing sign language users access to communication, education and services, such as the healthcare system. However, sign language users acceptance of signing avatars as well as their attitudes towards them vary and depend on man...
[ { "created": "Wed, 5 Jul 2023 08:22:46 GMT", "version": "v1" } ]
2023-07-20
[ [ "Soudi", "Abdelhadi", "" ], [ "Hakkaoui", "Manal El", "" ], [ "Van Laerhoven", "Kristof", "" ] ]
Avatar technology can offer accessibility possibilities and improve the Deaf-and-Hard of Hearing sign language users access to communication, education and services, such as the healthcare system. However, sign language users acceptance of signing avatars as well as their attitudes towards them vary and depend on many ...
1202.2759
Alyson Fletcher
Alyson K. Fletcher and Sundeep Rangan
Iterative Reconstruction of Rank-One Matrices in Noise
28 pages, 2 figures
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We consider the problem of estimating a rank-one matrix in Gaussian noise under a probabilistic model for the left and right factors of the matrix. The probabilistic model can impose constraints on the factors including sparsity and positivity that arise commonly in learning problems. We propose a family of algorithm...
[ { "created": "Mon, 13 Feb 2012 15:18:02 GMT", "version": "v1" }, { "created": "Mon, 30 Apr 2012 17:54:21 GMT", "version": "v2" }, { "created": "Tue, 8 May 2012 04:06:04 GMT", "version": "v3" }, { "created": "Tue, 15 Sep 2015 19:50:18 GMT", "version": "v4" } ]
2015-09-16
[ [ "Fletcher", "Alyson K.", "" ], [ "Rangan", "Sundeep", "" ] ]
We consider the problem of estimating a rank-one matrix in Gaussian noise under a probabilistic model for the left and right factors of the matrix. The probabilistic model can impose constraints on the factors including sparsity and positivity that arise commonly in learning problems. We propose a family of algorithms ...
2312.15313
Haiwei Dong
Zijian Long, Haiwei Dong, and Abdulmotaleb El Saddik
Human-Centric Resource Allocation for the Metaverse With Multiaccess Edge Computing
null
IEEE Internet of Things Journal, vol. 10, no. 22, pp. 19993-20005, 2023
10.1109/JIOT.2023.3283335
null
cs.MM cs.AI cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Multi-access edge computing (MEC) is a promising solution to the computation-intensive, low-latency rendering tasks of the metaverse. However, how to optimally allocate limited communication and computation resources at the edge to a large number of users in the metaverse is quite challenging. In this paper, we propo...
[ { "created": "Sat, 23 Dec 2023 18:07:46 GMT", "version": "v1" } ]
2023-12-27
[ [ "Long", "Zijian", "" ], [ "Dong", "Haiwei", "" ], [ "Saddik", "Abdulmotaleb El", "" ] ]
Multi-access edge computing (MEC) is a promising solution to the computation-intensive, low-latency rendering tasks of the metaverse. However, how to optimally allocate limited communication and computation resources at the edge to a large number of users in the metaverse is quite challenging. In this paper, we propose...
1501.04797
Sven Puchinger
Wenhui Li, Johan S. R. Nielsen, Sven Puchinger, Vladimir Sidorenko
Solving Shift Register Problems over Skew Polynomial Rings using Module Minimisation
10 pages, submitted to WCC 2015
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
For many algebraic codes the main part of decoding can be reduced to a shift register synthesis problem. In this paper we present an approach for solving generalised shift register problems over skew polynomial rings which occur in error and erasure decoding of $\ell$-Interleaved Gabidulin codes. The algorithm is bas...
[ { "created": "Tue, 20 Jan 2015 13:07:59 GMT", "version": "v1" } ]
2015-01-21
[ [ "Li", "Wenhui", "" ], [ "Nielsen", "Johan S. R.", "" ], [ "Puchinger", "Sven", "" ], [ "Sidorenko", "Vladimir", "" ] ]
For many algebraic codes the main part of decoding can be reduced to a shift register synthesis problem. In this paper we present an approach for solving generalised shift register problems over skew polynomial rings which occur in error and erasure decoding of $\ell$-Interleaved Gabidulin codes. The algorithm is based...
2210.14208
Khasa Gillani
Khasa Gillani, Jorge Mart\'in P\'erez, Milan Groshev, Antonio de la Oliva, Robert Gazda
Don't Let Me Down! Offloading Robot VFs Up to the Cloud
5 Pages, 6 figures, submitted to 2023 IEEE 9th International Conference on Network Softwarization (NetSoft)
null
null
null
cs.RO cs.NI
http://creativecommons.org/licenses/by-nc-nd/4.0/
Recent trends in robotic services propose offloading robot functionalities to the Edge to meet the strict latency requirements of networked robotics. However, the Edge is typically an expensive resource and sometimes the Cloud is also an option, thus, decreasing the cost. Following this idea, we propose Don't Let Me ...
[ { "created": "Tue, 25 Oct 2022 17:53:16 GMT", "version": "v1" }, { "created": "Mon, 13 Feb 2023 10:14:06 GMT", "version": "v2" }, { "created": "Tue, 14 Feb 2023 15:19:03 GMT", "version": "v3" } ]
2023-02-15
[ [ "Gillani", "Khasa", "" ], [ "Pérez", "Jorge Martín", "" ], [ "Groshev", "Milan", "" ], [ "de la Oliva", "Antonio", "" ], [ "Gazda", "Robert", "" ] ]
Recent trends in robotic services propose offloading robot functionalities to the Edge to meet the strict latency requirements of networked robotics. However, the Edge is typically an expensive resource and sometimes the Cloud is also an option, thus, decreasing the cost. Following this idea, we propose Don't Let Me Do...
2102.07889
Pei Wang
Arash Givchi, Pei Wang, Junqi Wang, Patrick Shafto
Distributionally-Constrained Policy Optimization via Unbalanced Optimal Transport
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We consider constrained policy optimization in Reinforcement Learning, where the constraints are in form of marginals on state visitations and global action executions. Given these distributions, we formulate policy optimization as unbalanced optimal transport over the space of occupancy measures. We propose a genera...
[ { "created": "Mon, 15 Feb 2021 23:04:37 GMT", "version": "v1" } ]
2021-02-17
[ [ "Givchi", "Arash", "" ], [ "Wang", "Pei", "" ], [ "Wang", "Junqi", "" ], [ "Shafto", "Patrick", "" ] ]
We consider constrained policy optimization in Reinforcement Learning, where the constraints are in form of marginals on state visitations and global action executions. Given these distributions, we formulate policy optimization as unbalanced optimal transport over the space of occupancy measures. We propose a general ...
2402.07872
Brian Ichter
Soroush Nasiriany, Fei Xia, Wenhao Yu, Ted Xiao, Jacky Liang, Ishita Dasgupta, Annie Xie, Danny Driess, Ayzaan Wahid, Zhuo Xu, Quan Vuong, Tingnan Zhang, Tsang-Wei Edward Lee, Kuang-Huei Lee, Peng Xu, Sean Kirmani, Yuke Zhu, Andy Zeng, Karol Hausman, Nicolas Heess, Chelsea Finn, Sergey Levine, Brian Ichter
PIVOT: Iterative Visual Prompting Elicits Actionable Knowledge for VLMs
null
null
null
null
cs.RO cs.CL cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Vision language models (VLMs) have shown impressive capabilities across a variety of tasks, from logical reasoning to visual understanding. This opens the door to richer interaction with the world, for example robotic control. However, VLMs produce only textual outputs, while robotic control and other spatial tasks r...
[ { "created": "Mon, 12 Feb 2024 18:33:47 GMT", "version": "v1" } ]
2024-02-13
[ [ "Nasiriany", "Soroush", "" ], [ "Xia", "Fei", "" ], [ "Yu", "Wenhao", "" ], [ "Xiao", "Ted", "" ], [ "Liang", "Jacky", "" ], [ "Dasgupta", "Ishita", "" ], [ "Xie", "Annie", "" ], [ "Driess", "Da...
Vision language models (VLMs) have shown impressive capabilities across a variety of tasks, from logical reasoning to visual understanding. This opens the door to richer interaction with the world, for example robotic control. However, VLMs produce only textual outputs, while robotic control and other spatial tasks req...
2005.04986
Yunjin Tong
Yunjin Tong, Shiying Xiong, Xingzhe He, Guanghan Pan, Bo Zhu
Symplectic Neural Networks in Taylor Series Form for Hamiltonian Systems
null
Journal of Computational Physics, p.110325 (2021)
10.1016/j.jcp.2021.110325
null
cs.LG math.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We propose an effective and lightweight learning algorithm, Symplectic Taylor Neural Networks (Taylor-nets), to conduct continuous, long-term predictions of a complex Hamiltonian dynamic system based on sparse, short-term observations. At the heart of our algorithm is a novel neural network architecture consisting of...
[ { "created": "Mon, 11 May 2020 10:32:29 GMT", "version": "v1" }, { "created": "Wed, 13 May 2020 05:10:17 GMT", "version": "v2" }, { "created": "Thu, 8 Apr 2021 18:49:23 GMT", "version": "v3" }, { "created": "Sun, 20 Feb 2022 01:20:28 GMT", "version": "v4" } ]
2022-02-22
[ [ "Tong", "Yunjin", "" ], [ "Xiong", "Shiying", "" ], [ "He", "Xingzhe", "" ], [ "Pan", "Guanghan", "" ], [ "Zhu", "Bo", "" ] ]
We propose an effective and lightweight learning algorithm, Symplectic Taylor Neural Networks (Taylor-nets), to conduct continuous, long-term predictions of a complex Hamiltonian dynamic system based on sparse, short-term observations. At the heart of our algorithm is a novel neural network architecture consisting of t...
2302.04899
Dmitry Kazhdan
Dmitry Kazhdan, Botty Dimanov, Lucie Charlotte Magister, Pietro Barbiero, Mateja Jamnik, Pietro Lio
GCI: A (G)raph (C)oncept (I)nterpretation Framework
null
null
null
null
cs.LG
http://creativecommons.org/licenses/by/4.0/
Explainable AI (XAI) underwent a recent surge in research on concept extraction, focusing on extracting human-interpretable concepts from Deep Neural Networks. An important challenge facing concept extraction approaches is the difficulty of interpreting and evaluating discovered concepts, especially for complex tasks...
[ { "created": "Thu, 9 Feb 2023 19:02:45 GMT", "version": "v1" } ]
2023-02-13
[ [ "Kazhdan", "Dmitry", "" ], [ "Dimanov", "Botty", "" ], [ "Magister", "Lucie Charlotte", "" ], [ "Barbiero", "Pietro", "" ], [ "Jamnik", "Mateja", "" ], [ "Lio", "Pietro", "" ] ]
Explainable AI (XAI) underwent a recent surge in research on concept extraction, focusing on extracting human-interpretable concepts from Deep Neural Networks. An important challenge facing concept extraction approaches is the difficulty of interpreting and evaluating discovered concepts, especially for complex tasks s...
2004.14084
Yuki Nishida
Yuki Nishida and Atsushi Igarashi
Compilation of Coordinated Choice
null
null
null
null
cs.PL cs.LO
http://creativecommons.org/licenses/by/4.0/
Recently, we have proposed coordinated choices, which are nondeterministic choices equipped with names. The main characteristic of coordinated choices is that they synchronize nondeterministic decision among choices of the same name. The motivation of the synchronization mechanism is to solve a theoretical problem....
[ { "created": "Wed, 29 Apr 2020 11:15:19 GMT", "version": "v1" } ]
2020-05-05
[ [ "Nishida", "Yuki", "" ], [ "Igarashi", "Atsushi", "" ] ]
Recently, we have proposed coordinated choices, which are nondeterministic choices equipped with names. The main characteristic of coordinated choices is that they synchronize nondeterministic decision among choices of the same name. The motivation of the synchronization mechanism is to solve a theoretical problem. So,...
1810.09270
Rui Zhu
Rui Zhu and Di Niu
A Model Parallel Proximal Stochastic Gradient Algorithm for Partially Asynchronous Systems
arXiv admin note: substantial text overlap with arXiv:1802.08880
null
null
null
cs.LG stat.ML
http://creativecommons.org/licenses/by/4.0/
Large models are prevalent in modern machine learning scenarios, including deep learning, recommender systems, etc., which can have millions or even billions of parameters. Parallel algorithms have become an essential solution technique to many large-scale machine learning jobs. In this paper, we propose a model para...
[ { "created": "Fri, 19 Oct 2018 17:22:30 GMT", "version": "v1" } ]
2018-10-23
[ [ "Zhu", "Rui", "" ], [ "Niu", "Di", "" ] ]
Large models are prevalent in modern machine learning scenarios, including deep learning, recommender systems, etc., which can have millions or even billions of parameters. Parallel algorithms have become an essential solution technique to many large-scale machine learning jobs. In this paper, we propose a model parall...
2110.08477
Jian Du
Yan Shen and Jian Du and Han Zhao and Benyu Zhang and Zhanghexuan Ji and Mingchen Gao
FedMM: Saddle Point Optimization for Federated Adversarial Domain Adaptation
34 pages
null
null
null
cs.LG
http://creativecommons.org/licenses/by/4.0/
Federated adversary domain adaptation is a unique distributed minimax training task due to the prevalence of label imbalance among clients, with each client only seeing a subset of the classes of labels required to train a global model. To tackle this problem, we propose a distributed minimax optimizer referred to as...
[ { "created": "Sat, 16 Oct 2021 05:32:03 GMT", "version": "v1" }, { "created": "Sun, 24 Oct 2021 17:52:37 GMT", "version": "v2" }, { "created": "Tue, 16 Nov 2021 03:36:08 GMT", "version": "v3" } ]
2021-11-17
[ [ "Shen", "Yan", "" ], [ "Du", "Jian", "" ], [ "Zhao", "Han", "" ], [ "Zhang", "Benyu", "" ], [ "Ji", "Zhanghexuan", "" ], [ "Gao", "Mingchen", "" ] ]
Federated adversary domain adaptation is a unique distributed minimax training task due to the prevalence of label imbalance among clients, with each client only seeing a subset of the classes of labels required to train a global model. To tackle this problem, we propose a distributed minimax optimizer referred to as F...
2102.10629
Aaron Zimba
Aaron Zimba, Tozgani Fainess Mbale, Mumbi Chishimba, Mathews Chibuluma
Liberalisation of the International Gateway and Internet Development in Zambia: The Genesis, Opportunities, Challenges, and Future Directions
null
null
null
null
cs.NI
http://creativecommons.org/licenses/by/4.0/
Telecommunication reforms in Zambia and the subsequent liberalisation of the international gateway was perceived as one of the means of promoting social and economic growth in both the urban and rural areas of the country. The outcome of this undertaking propelled the rapid development of Internet which has evidently...
[ { "created": "Sun, 21 Feb 2021 15:49:37 GMT", "version": "v1" } ]
2021-02-23
[ [ "Zimba", "Aaron", "" ], [ "Mbale", "Tozgani Fainess", "" ], [ "Chishimba", "Mumbi", "" ], [ "Chibuluma", "Mathews", "" ] ]
Telecommunication reforms in Zambia and the subsequent liberalisation of the international gateway was perceived as one of the means of promoting social and economic growth in both the urban and rural areas of the country. The outcome of this undertaking propelled the rapid development of Internet which has evidently b...
2109.01718
Jing Ma
Jing Ma, Qiuchen Zhang, Jian Lou, Li Xiong, Sivasubramanium Bhavani, Joyce C. Ho
Communication Efficient Generalized Tensor Factorization for Decentralized Healthcare Networks
Short version accepted to IEEE ICDM 2021
null
null
null
cs.LG cs.DC
http://creativecommons.org/licenses/by-nc-sa/4.0/
Tensor factorization has been proved as an efficient unsupervised learning approach for health data analysis, especially for computational phenotyping, where the high-dimensional Electronic Health Records (EHRs) with patients' history of medical procedures, medications, diagnosis, lab tests, etc., are converted to me...
[ { "created": "Fri, 3 Sep 2021 19:47:08 GMT", "version": "v1" }, { "created": "Thu, 3 Nov 2022 06:15:31 GMT", "version": "v2" } ]
2022-11-04
[ [ "Ma", "Jing", "" ], [ "Zhang", "Qiuchen", "" ], [ "Lou", "Jian", "" ], [ "Xiong", "Li", "" ], [ "Bhavani", "Sivasubramanium", "" ], [ "Ho", "Joyce C.", "" ] ]
Tensor factorization has been proved as an efficient unsupervised learning approach for health data analysis, especially for computational phenotyping, where the high-dimensional Electronic Health Records (EHRs) with patients' history of medical procedures, medications, diagnosis, lab tests, etc., are converted to mean...
1908.11610
Zhuoren Jiang
Zhuoren Jiang, Jian Wang, Lujun Zhao, Changlong Sun, Yao Lu, Xiaozhong Liu
Cross-domain Aspect Category Transfer and Detection via Traceable Heterogeneous Graph Representation Learning
Accepted as a full paper of The 28th ACM International Conference on Information and Knowledge Management (CIKM '19)
null
10.1145/3357384.3357989
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Aspect category detection is an essential task for sentiment analysis and opinion mining. However, the cost of categorical data labeling, e.g., label the review aspect information for a large number of product domains, can be inevitable but unaffordable. In this study, we propose a novel problem, cross-domain aspect ...
[ { "created": "Fri, 30 Aug 2019 09:30:38 GMT", "version": "v1" } ]
2019-09-02
[ [ "Jiang", "Zhuoren", "" ], [ "Wang", "Jian", "" ], [ "Zhao", "Lujun", "" ], [ "Sun", "Changlong", "" ], [ "Lu", "Yao", "" ], [ "Liu", "Xiaozhong", "" ] ]
Aspect category detection is an essential task for sentiment analysis and opinion mining. However, the cost of categorical data labeling, e.g., label the review aspect information for a large number of product domains, can be inevitable but unaffordable. In this study, we propose a novel problem, cross-domain aspect ca...
1802.00912
Zongwei Zhou
Zongwei Zhou, Jae Y. Shin, Suryakanth R. Gurudu, Michael B. Gotway, Jianming Liang
Active, Continual Fine Tuning of Convolutional Neural Networks for Reducing Annotation Efforts
null
null
10.1016/j.media.2021.101997
null
cs.LG cs.CV stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The splendid success of convolutional neural networks (CNNs) in computer vision is largely attributable to the availability of massive annotated datasets, such as ImageNet and Places. However, in medical imaging, it is challenging to create such large annotated datasets, as annotating medical images is not only tedio...
[ { "created": "Sat, 3 Feb 2018 05:01:17 GMT", "version": "v1" }, { "created": "Wed, 7 Feb 2018 02:13:28 GMT", "version": "v2" }, { "created": "Sat, 23 May 2020 18:03:48 GMT", "version": "v3" }, { "created": "Tue, 30 Mar 2021 00:19:51 GMT", "version": "v4" }, { "cre...
2021-04-13
[ [ "Zhou", "Zongwei", "" ], [ "Shin", "Jae Y.", "" ], [ "Gurudu", "Suryakanth R.", "" ], [ "Gotway", "Michael B.", "" ], [ "Liang", "Jianming", "" ] ]
The splendid success of convolutional neural networks (CNNs) in computer vision is largely attributable to the availability of massive annotated datasets, such as ImageNet and Places. However, in medical imaging, it is challenging to create such large annotated datasets, as annotating medical images is not only tedious...
2201.09769
Martin Bromberger
Martin Bromberger (1), Irina Dragoste (2), Rasha Faqeh (2), Christof Fetzer (2), Larry Gonz\'alez (2), Markus Kr\"otzsch (2), Maximilian Marx (2), Harish K Murali, (1 and 3), Christoph Weidenbach (1) ((1) Max Planck Institute for Informatics, Saarland Informatics Campus, Saarbr\"ucken, Germany, (2) TU Dresden, ...
A Sorted Datalog Hammer for Supervisor Verification Conditions Modulo Simple Linear Arithmetic
34 pages, to be published in the proceedings for TACAS 2022. arXiv admin note: text overlap with arXiv:2107.03189
null
null
null
cs.LO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In a previous paper, we have shown that clause sets belonging to the Horn Bernays-Sch\"onfinkel fragment over simple linear real arithmetic (HBS(SLR)) can be translated into HBS clause sets over a finite set of first-order constants. The translation preserves validity and satisfiability and it is still applicable if ...
[ { "created": "Mon, 24 Jan 2022 15:58:37 GMT", "version": "v1" } ]
2022-01-25
[ [ "Bromberger", "Martin", "" ], [ "Dragoste", "Irina", "" ], [ "Faqeh", "Rasha", "" ], [ "Fetzer", "Christof", "" ], [ "González", "Larry", "" ], [ "Krötzsch", "Markus", "" ], [ "Marx", "Maximilian", "" ], ...
In a previous paper, we have shown that clause sets belonging to the Horn Bernays-Sch\"onfinkel fragment over simple linear real arithmetic (HBS(SLR)) can be translated into HBS clause sets over a finite set of first-order constants. The translation preserves validity and satisfiability and it is still applicable if we...
2006.09645
Atsuya Kobayashi
Atsuya Kobayashi, Reo Anzai, Nao Tokui
ExSampling: a system for the real-time ensemble performance of field-recorded environmental sounds
The International Conference on New Interfaces for Musical Expression 2020 poster presentation. 4 pages
null
null
null
cs.HC cs.SD eess.AS
http://creativecommons.org/licenses/by/4.0/
We propose ExSampling: an integrated system of recording application and Deep Learning environment for a real-time music performance of environmental sounds sampled by field recording. Automated sound mapping to Ableton Live tracks by Deep Learning enables field recording to be applied to real-time performance, and c...
[ { "created": "Wed, 17 Jun 2020 04:07:13 GMT", "version": "v1" } ]
2020-06-18
[ [ "Kobayashi", "Atsuya", "" ], [ "Anzai", "Reo", "" ], [ "Tokui", "Nao", "" ] ]
We propose ExSampling: an integrated system of recording application and Deep Learning environment for a real-time music performance of environmental sounds sampled by field recording. Automated sound mapping to Ableton Live tracks by Deep Learning enables field recording to be applied to real-time performance, and cre...
1402.2941
Zohaib Khan
Zohaib Khan, Faisal Shafait, Yiqun Hu, Ajmal Mian
Multispectral Palmprint Encoding and Recognition
Preliminary version of this manuscript was published in ICCV 2011. Z. Khan A. Mian and Y. Hu, "Contour Code: Robust and Efficient Multispectral Palmprint Encoding for Human Recognition", International Conference on Computer Vision, 2011. MATLAB Code available: https://sites.google.com/site/zohaibnet/Home/codes
null
null
null
cs.CV
http://creativecommons.org/licenses/by-nc-sa/3.0/
Palmprints are emerging as a new entity in multi-modal biometrics for human identification and verification. Multispectral palmprint images captured in the visible and infrared spectrum not only contain the wrinkles and ridge structure of a palm, but also the underlying pattern of veins; making them a highly discrimi...
[ { "created": "Thu, 6 Feb 2014 06:35:51 GMT", "version": "v1" } ]
2014-02-13
[ [ "Khan", "Zohaib", "" ], [ "Shafait", "Faisal", "" ], [ "Hu", "Yiqun", "" ], [ "Mian", "Ajmal", "" ] ]
Palmprints are emerging as a new entity in multi-modal biometrics for human identification and verification. Multispectral palmprint images captured in the visible and infrared spectrum not only contain the wrinkles and ridge structure of a palm, but also the underlying pattern of veins; making them a highly discrimina...
1902.05718
Justinas Miseikis
Justinas Miseikis, Inka Brijacak, Saeed Yahyanejad, Kyrre Glette, Ole Jakob Elle, Jim Torresen
Two-Stage Transfer Learning for Heterogeneous Robot Detection and 3D Joint Position Estimation in a 2D Camera Image using CNN
6+n pages, ICRA 2019 submission
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Collaborative robots are becoming more common on factory floors as well as regular environments, however, their safety still is not a fully solved issue. Collision detection does not always perform as expected and collision avoidance is still an active research area. Collision avoidance works well for fixed robot-cam...
[ { "created": "Fri, 15 Feb 2019 08:25:02 GMT", "version": "v1" } ]
2019-02-18
[ [ "Miseikis", "Justinas", "" ], [ "Brijacak", "Inka", "" ], [ "Yahyanejad", "Saeed", "" ], [ "Glette", "Kyrre", "" ], [ "Elle", "Ole Jakob", "" ], [ "Torresen", "Jim", "" ] ]
Collaborative robots are becoming more common on factory floors as well as regular environments, however, their safety still is not a fully solved issue. Collision detection does not always perform as expected and collision avoidance is still an active research area. Collision avoidance works well for fixed robot-camer...
2308.07496
Yuqi Nie
Zepu Wang, Yuqi Nie, Peng Sun, Nam H. Nguyen, John Mulvey, H. Vincent Poor
ST-MLP: A Cascaded Spatio-Temporal Linear Framework with Channel-Independence Strategy for Traffic Forecasting
null
null
null
null
cs.LG cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The criticality of prompt and precise traffic forecasting in optimizing traffic flow management in Intelligent Transportation Systems (ITS) has drawn substantial scholarly focus. Spatio-Temporal Graph Neural Networks (STGNNs) have been lauded for their adaptability to road graph structures. Yet, current research on S...
[ { "created": "Mon, 14 Aug 2023 23:34:59 GMT", "version": "v1" } ]
2023-08-16
[ [ "Wang", "Zepu", "" ], [ "Nie", "Yuqi", "" ], [ "Sun", "Peng", "" ], [ "Nguyen", "Nam H.", "" ], [ "Mulvey", "John", "" ], [ "Poor", "H. Vincent", "" ] ]
The criticality of prompt and precise traffic forecasting in optimizing traffic flow management in Intelligent Transportation Systems (ITS) has drawn substantial scholarly focus. Spatio-Temporal Graph Neural Networks (STGNNs) have been lauded for their adaptability to road graph structures. Yet, current research on STG...
2203.05782
Michael Mozer
Shruthi Sukumar, Adrian F. Ward, Camden Elliott-Williams, Shabnam Hakimi, Michael C. Mozer
Overcoming Temptation: Incentive Design For Intertemporal Choice
null
null
null
null
cs.LG q-bio.NC
http://creativecommons.org/licenses/by-nc-nd/4.0/
Individuals are often faced with temptations that can lead them astray from long-term goals. We're interested in developing interventions that steer individuals toward making good initial decisions and then maintaining those decisions over time. In the realm of financial decision making, a particularly successful app...
[ { "created": "Fri, 11 Mar 2022 07:42:07 GMT", "version": "v1" }, { "created": "Mon, 14 Mar 2022 04:47:31 GMT", "version": "v2" } ]
2022-03-15
[ [ "Sukumar", "Shruthi", "" ], [ "Ward", "Adrian F.", "" ], [ "Elliott-Williams", "Camden", "" ], [ "Hakimi", "Shabnam", "" ], [ "Mozer", "Michael C.", "" ] ]
Individuals are often faced with temptations that can lead them astray from long-term goals. We're interested in developing interventions that steer individuals toward making good initial decisions and then maintaining those decisions over time. In the realm of financial decision making, a particularly successful appro...
1509.07813
Jacopo Baggio
Kehinde R. Salau, Jacopo A. Baggio, Marco A. Janssen, Joshua K. Abbott, Eli P. Fenichel
Taking a moment to measure Networks - A hierarchical approach
Main Paper: 32 Pages, Suppl0Material: 9 pages
null
null
null
cs.SI physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Network-theoretic tools contribute to understanding real-world system dynamics, e.g., in wildlife conservation, epidemics, and power outages. Network visualization helps illustrate structural heterogeneity; however, details about heterogeneity are lost when summarizing networks with a single mean-style measure. Resea...
[ { "created": "Fri, 25 Sep 2015 18:00:01 GMT", "version": "v1" } ]
2015-09-28
[ [ "Salau", "Kehinde R.", "" ], [ "Baggio", "Jacopo A.", "" ], [ "Janssen", "Marco A.", "" ], [ "Abbott", "Joshua K.", "" ], [ "Fenichel", "Eli P.", "" ] ]
Network-theoretic tools contribute to understanding real-world system dynamics, e.g., in wildlife conservation, epidemics, and power outages. Network visualization helps illustrate structural heterogeneity; however, details about heterogeneity are lost when summarizing networks with a single mean-style measure. Researc...
2110.01774
Uttaran Bhattacharya
Uttaran Bhattacharya and Gang Wu and Stefano Petrangeli and Viswanathan Swaminathan and Dinesh Manocha
HighlightMe: Detecting Highlights from Human-Centric Videos
10 pages, 5 figures, 5 tables. In Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2021
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
We present a domain- and user-preference-agnostic approach to detect highlightable excerpts from human-centric videos. Our method works on the graph-based representation of multiple observable human-centric modalities in the videos, such as poses and faces. We use an autoencoder network equipped with spatial-temporal...
[ { "created": "Tue, 5 Oct 2021 01:18:15 GMT", "version": "v1" } ]
2021-10-06
[ [ "Bhattacharya", "Uttaran", "" ], [ "Wu", "Gang", "" ], [ "Petrangeli", "Stefano", "" ], [ "Swaminathan", "Viswanathan", "" ], [ "Manocha", "Dinesh", "" ] ]
We present a domain- and user-preference-agnostic approach to detect highlightable excerpts from human-centric videos. Our method works on the graph-based representation of multiple observable human-centric modalities in the videos, such as poses and faces. We use an autoencoder network equipped with spatial-temporal g...
2107.11817
Fuzhao Xue
Fuzhao Xue, Ziji Shi, Futao Wei, Yuxuan Lou, Yong Liu, Yang You
Go Wider Instead of Deeper
null
null
null
null
cs.LG cs.AI cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
More transformer blocks with residual connections have recently achieved impressive results on various tasks. To achieve better performance with fewer trainable parameters, recent methods are proposed to go shallower by parameter sharing or model compressing along with the depth. However, weak modeling capacity limit...
[ { "created": "Sun, 25 Jul 2021 14:44:24 GMT", "version": "v1" }, { "created": "Thu, 29 Jul 2021 10:17:23 GMT", "version": "v2" }, { "created": "Tue, 7 Sep 2021 11:58:00 GMT", "version": "v3" } ]
2021-09-08
[ [ "Xue", "Fuzhao", "" ], [ "Shi", "Ziji", "" ], [ "Wei", "Futao", "" ], [ "Lou", "Yuxuan", "" ], [ "Liu", "Yong", "" ], [ "You", "Yang", "" ] ]
More transformer blocks with residual connections have recently achieved impressive results on various tasks. To achieve better performance with fewer trainable parameters, recent methods are proposed to go shallower by parameter sharing or model compressing along with the depth. However, weak modeling capacity limits ...
2011.11688
Kenneth Joseph
Zijian An, Kenneth Joseph
An analysis of replies to Trump's tweets
Accepted at ICWSM'21
null
null
null
cs.CY
http://creativecommons.org/licenses/by/4.0/
Donald Trump has tweeted thousands of times during his presidency. These public statements are an increasingly important way through which Trump communicates his political and personal views. A better understanding of the way the American public consumes and responds to these tweets is therefore critical. In the pres...
[ { "created": "Mon, 23 Nov 2020 19:29:29 GMT", "version": "v1" } ]
2020-11-25
[ [ "An", "Zijian", "" ], [ "Joseph", "Kenneth", "" ] ]
Donald Trump has tweeted thousands of times during his presidency. These public statements are an increasingly important way through which Trump communicates his political and personal views. A better understanding of the way the American public consumes and responds to these tweets is therefore critical. In the presen...
2111.03977
Robert Wilson
Robert L. Wilson, Daniel Browne, Jonathan Wagstaff, and Steve McGuire
A Virtual Reality Simulation Pipeline for Online Mental Workload Modeling
7 pages, 4 figures, and 1 table Currently under review as a conference paper for IEEE VR 2022, v2 - Spelling Corrections
null
null
null
cs.HC cs.RO
http://creativecommons.org/licenses/by/4.0/
Seamless human robot interaction (HRI) and cooperative human-robot (HR) teaming critically rely upon accurate and timely human mental workload (MW) models. Cognitive Load Theory (CLT) suggests representative physical environments produce representative mental processes; physical environment fidelity corresponds with ...
[ { "created": "Sun, 7 Nov 2021 00:50:39 GMT", "version": "v1" }, { "created": "Wed, 24 Nov 2021 16:09:45 GMT", "version": "v2" } ]
2021-11-25
[ [ "Wilson", "Robert L.", "" ], [ "Browne", "Daniel", "" ], [ "Wagstaff", "Jonathan", "" ], [ "McGuire", "Steve", "" ] ]
Seamless human robot interaction (HRI) and cooperative human-robot (HR) teaming critically rely upon accurate and timely human mental workload (MW) models. Cognitive Load Theory (CLT) suggests representative physical environments produce representative mental processes; physical environment fidelity corresponds with im...
2404.17697
Thomas Billington
Thomas Billington, Ansh Gwash, Aadi Kothari, Lucas Izquierdo, Timothy Talty
Enhancing Track Management Systems with Vehicle-To-Vehicle Enabled Sensor Fusion
6 pages, 5 figures
null
null
null
cs.RO cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In the rapidly advancing landscape of connected and automated vehicles (CAV), the integration of Vehicle-to-Everything (V2X) communication in traditional fusion systems presents a promising avenue for enhancing vehicle perception. Addressing current limitations with vehicle sensing, this paper proposes a novel Vehicl...
[ { "created": "Fri, 26 Apr 2024 20:54:44 GMT", "version": "v1" } ]
2024-04-30
[ [ "Billington", "Thomas", "" ], [ "Gwash", "Ansh", "" ], [ "Kothari", "Aadi", "" ], [ "Izquierdo", "Lucas", "" ], [ "Talty", "Timothy", "" ] ]
In the rapidly advancing landscape of connected and automated vehicles (CAV), the integration of Vehicle-to-Everything (V2X) communication in traditional fusion systems presents a promising avenue for enhancing vehicle perception. Addressing current limitations with vehicle sensing, this paper proposes a novel Vehicle-...
2312.15122
Andreas Pasternak
Moritz Harmel, Anubhav Paras, Andreas Pasternak, Nicholas Roy, Gary Linscott
Scaling Is All You Need: Autonomous Driving with JAX-Accelerated Reinforcement Learning
null
null
null
null
cs.LG cs.AI cs.RO
http://creativecommons.org/licenses/by-nc-nd/4.0/
Reinforcement learning has been demonstrated to outperform even the best humans in complex domains like video games. However, running reinforcement learning experiments on the required scale for autonomous driving is extremely difficult. Building a large scale reinforcement learning system and distributing it across ...
[ { "created": "Sat, 23 Dec 2023 00:07:06 GMT", "version": "v1" }, { "created": "Tue, 6 Feb 2024 00:07:19 GMT", "version": "v2" }, { "created": "Thu, 8 Feb 2024 19:39:19 GMT", "version": "v3" } ]
2024-02-12
[ [ "Harmel", "Moritz", "" ], [ "Paras", "Anubhav", "" ], [ "Pasternak", "Andreas", "" ], [ "Roy", "Nicholas", "" ], [ "Linscott", "Gary", "" ] ]
Reinforcement learning has been demonstrated to outperform even the best humans in complex domains like video games. However, running reinforcement learning experiments on the required scale for autonomous driving is extremely difficult. Building a large scale reinforcement learning system and distributing it across ma...
2111.11703
Taketo Akama
Taketo Akama
A Contextual Latent Space Model: Subsequence Modulation in Melodic Sequence
22nd International Society for Music Information Retrieval Conference (ISMIR), 2021; 8 pages
null
null
null
cs.LG cs.AI cs.SD eess.AS stat.ML
http://creativecommons.org/licenses/by/4.0/
Some generative models for sequences such as music and text allow us to edit only subsequences, given surrounding context sequences, which plays an important part in steering generation interactively. However, editing subsequences mainly involves randomly resampling subsequences from a possible generation space. We p...
[ { "created": "Tue, 23 Nov 2021 07:51:39 GMT", "version": "v1" } ]
2021-11-24
[ [ "Akama", "Taketo", "" ] ]
Some generative models for sequences such as music and text allow us to edit only subsequences, given surrounding context sequences, which plays an important part in steering generation interactively. However, editing subsequences mainly involves randomly resampling subsequences from a possible generation space. We pro...
2309.08585
Yuan Jianlong
Xiaonan Lu, Jianlong Yuan, Ruigang Niu, Yuan Hu, Fan Wang
Viewpoint Integration and Registration with Vision Language Foundation Model for Image Change Understanding
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recently, the development of pre-trained vision language foundation models (VLFMs) has led to remarkable performance in many tasks. However, these models tend to have strong single-image understanding capability but lack the ability to understand multiple images. Therefore, they cannot be directly applied to cope wit...
[ { "created": "Fri, 15 Sep 2023 17:41:29 GMT", "version": "v1" } ]
2023-09-18
[ [ "Lu", "Xiaonan", "" ], [ "Yuan", "Jianlong", "" ], [ "Niu", "Ruigang", "" ], [ "Hu", "Yuan", "" ], [ "Wang", "Fan", "" ] ]
Recently, the development of pre-trained vision language foundation models (VLFMs) has led to remarkable performance in many tasks. However, these models tend to have strong single-image understanding capability but lack the ability to understand multiple images. Therefore, they cannot be directly applied to cope with ...
2304.10996
Maryem Rhanoui
Ayoub Harnoune and Maryem Rhanoui and Mounia Mikram and Siham Yousfi and Zineb Elkaimbillah and Bouchra El Asri
BERT Based Clinical Knowledge Extraction for Biomedical Knowledge Graph Construction and Analysis
null
null
10.1016/j.cmpbup.2021.100042
null
cs.CL cs.AI
http://creativecommons.org/licenses/by-nc-sa/4.0/
Background : Knowledge is evolving over time, often as a result of new discoveries or changes in the adopted methods of reasoning. Also, new facts or evidence may become available, leading to new understandings of complex phenomena. This is particularly true in the biomedical field, where scientists and physicians ar...
[ { "created": "Fri, 21 Apr 2023 14:45:33 GMT", "version": "v1" } ]
2023-04-24
[ [ "Harnoune", "Ayoub", "" ], [ "Rhanoui", "Maryem", "" ], [ "Mikram", "Mounia", "" ], [ "Yousfi", "Siham", "" ], [ "Elkaimbillah", "Zineb", "" ], [ "Asri", "Bouchra El", "" ] ]
Background : Knowledge is evolving over time, often as a result of new discoveries or changes in the adopted methods of reasoning. Also, new facts or evidence may become available, leading to new understandings of complex phenomena. This is particularly true in the biomedical field, where scientists and physicians are ...
1903.07507
Ishan Jindal
Ishan Jindal, Daniel Pressel, Brian Lester, Matthew Nokleby
An Effective Label Noise Model for DNN Text Classification
Accepted at NAACL-HLT 2019 Main Conference Long paper
null
null
null
cs.LG cs.CL cs.IR stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Because large, human-annotated datasets suffer from labeling errors, it is crucial to be able to train deep neural networks in the presence of label noise. While training image classification models with label noise have received much attention, training text classification models have not. In this paper, we propose ...
[ { "created": "Mon, 18 Mar 2019 15:27:50 GMT", "version": "v1" } ]
2019-03-19
[ [ "Jindal", "Ishan", "" ], [ "Pressel", "Daniel", "" ], [ "Lester", "Brian", "" ], [ "Nokleby", "Matthew", "" ] ]
Because large, human-annotated datasets suffer from labeling errors, it is crucial to be able to train deep neural networks in the presence of label noise. While training image classification models with label noise have received much attention, training text classification models have not. In this paper, we propose an...
2312.13770
Zheheng Jiang
Zheheng Jiang, Hossein Rahmani, Sue Black, Bryan M. Williams
3D Points Splatting for Real-Time Dynamic Hand Reconstruction
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present 3D Points Splatting Hand Reconstruction (3D-PSHR), a real-time and photo-realistic hand reconstruction approach. We propose a self-adaptive canonical points upsampling strategy to achieve high-resolution hand geometry representation. This is followed by a self-adaptive deformation that deforms the hand fro...
[ { "created": "Thu, 21 Dec 2023 11:50:49 GMT", "version": "v1" } ]
2023-12-22
[ [ "Jiang", "Zheheng", "" ], [ "Rahmani", "Hossein", "" ], [ "Black", "Sue", "" ], [ "Williams", "Bryan M.", "" ] ]
We present 3D Points Splatting Hand Reconstruction (3D-PSHR), a real-time and photo-realistic hand reconstruction approach. We propose a self-adaptive canonical points upsampling strategy to achieve high-resolution hand geometry representation. This is followed by a self-adaptive deformation that deforms the hand from ...
1412.7664
Roshan Ragel
M.G.G.C.R. Salgado and R. G. Ragel
Register Spilling for Specific Application Domains in Application Specific Instruction-set Processors
The 7th International Conference on Information and Automation for Sustainability (ICIAfS) 2014
null
null
null
cs.PL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
An Application Specific Instruction set Processor (ASIP) is an important component in designing embedded systems. One of the problems in designing an instruction set for such processors is determining the number of registers is needed in the processor that will optimize the computational time and the cost. The perfor...
[ { "created": "Wed, 24 Dec 2014 14:15:19 GMT", "version": "v1" } ]
2014-12-25
[ [ "Salgado", "M. G. G. C. R.", "" ], [ "Ragel", "R. G.", "" ] ]
An Application Specific Instruction set Processor (ASIP) is an important component in designing embedded systems. One of the problems in designing an instruction set for such processors is determining the number of registers is needed in the processor that will optimize the computational time and the cost. The performa...
1005.2894
Fabian Kuhn
Fabian Kuhn, Christoph Lenzen, Thomas Locher, Rotem Oshman
Optimal Gradient Clock Synchronization in Dynamic Networks
68 pages; conference version: 29th Annual ACM Symposium on Principles of Distributed Computing (PODC 2010)
null
null
null
cs.DC cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We study the problem of clock synchronization in highly dynamic networks, where communication links can appear or disappear at any time. The nodes in the network are equipped with hardware clocks, but the rate of the hardware clocks can vary arbitrarily within specific bounds, and the estimates that nodes can obtain ...
[ { "created": "Mon, 17 May 2010 11:56:31 GMT", "version": "v1" }, { "created": "Tue, 17 Aug 2010 08:01:04 GMT", "version": "v2" }, { "created": "Sat, 8 Dec 2018 13:00:54 GMT", "version": "v3" } ]
2018-12-11
[ [ "Kuhn", "Fabian", "" ], [ "Lenzen", "Christoph", "" ], [ "Locher", "Thomas", "" ], [ "Oshman", "Rotem", "" ] ]
We study the problem of clock synchronization in highly dynamic networks, where communication links can appear or disappear at any time. The nodes in the network are equipped with hardware clocks, but the rate of the hardware clocks can vary arbitrarily within specific bounds, and the estimates that nodes can obtain ab...
2011.05519
Dilusha Weeraddana Dr
Dilusha Weeraddana, Nguyen Lu Dang Khoa, Lachlan O Neil, Weihong Wang, and Chen Cai
Energy consumption forecasting using a stacked nonparametric Bayesian approach
Conference: ECML-PKDD 2020
null
null
null
cs.LG cs.AI
http://creativecommons.org/licenses/by/4.0/
In this paper, the process of forecasting household energy consumption is studied within the framework of the nonparametric Gaussian Process (GP), using multiple short time series data. As we begin to use smart meter data to paint a clearer picture of residential electricity use, it becomes increasingly apparent that...
[ { "created": "Wed, 11 Nov 2020 02:27:00 GMT", "version": "v1" } ]
2020-11-12
[ [ "Weeraddana", "Dilusha", "" ], [ "Khoa", "Nguyen Lu Dang", "" ], [ "Neil", "Lachlan O", "" ], [ "Wang", "Weihong", "" ], [ "Cai", "Chen", "" ] ]
In this paper, the process of forecasting household energy consumption is studied within the framework of the nonparametric Gaussian Process (GP), using multiple short time series data. As we begin to use smart meter data to paint a clearer picture of residential electricity use, it becomes increasingly apparent that w...
2102.07515
Pierre Vial
Pierre Vial
Sequence Types and Infinitary Semantics
68 pages, 18 figures
null
null
null
cs.LO cs.PL
http://creativecommons.org/licenses/by/4.0/
We introduce a new representation of non-idempotent intersection types, using \textbf{sequences} (families indexed with natural numbers) instead of lists or multisets. This allows scaling up \textbf{intersection type} theory to the infinitary $\lambda$-calculus. We thus characterize hereditary head normalization, whi...
[ { "created": "Mon, 15 Feb 2021 12:33:41 GMT", "version": "v1" }, { "created": "Wed, 15 Dec 2021 09:12:09 GMT", "version": "v2" } ]
2021-12-16
[ [ "Vial", "Pierre", "" ] ]
We introduce a new representation of non-idempotent intersection types, using \textbf{sequences} (families indexed with natural numbers) instead of lists or multisets. This allows scaling up \textbf{intersection type} theory to the infinitary $\lambda$-calculus. We thus characterize hereditary head normalization, which...
1111.4045
Javier Parra-Arnau
David Rebollo-Monedero, Javier Parra-Arnau, Jordi Forn\'e
An Information-Theoretic Privacy Criterion for Query Forgery in Information Retrieval
This paper has 15 pages and 1 figure
null
null
null
cs.IT cs.CR math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In previous work, we presented a novel information-theoretic privacy criterion for query forgery in the domain of information retrieval. Our criterion measured privacy risk as a divergence between the user's and the population's query distribution, and contemplated the entropy of the user's distribution as a particul...
[ { "created": "Thu, 17 Nov 2011 10:06:49 GMT", "version": "v1" } ]
2015-03-19
[ [ "Rebollo-Monedero", "David", "" ], [ "Parra-Arnau", "Javier", "" ], [ "Forné", "Jordi", "" ] ]
In previous work, we presented a novel information-theoretic privacy criterion for query forgery in the domain of information retrieval. Our criterion measured privacy risk as a divergence between the user's and the population's query distribution, and contemplated the entropy of the user's distribution as a particular...
2308.07522
Victor Zitian Chen
Victor Zitian Chen
Finding Stakeholder-Material Information from 10-K Reports using Fine-Tuned BERT and LSTM Models
null
null
null
null
cs.CL cs.CE
http://creativecommons.org/licenses/by/4.0/
All public companies are required by federal securities law to disclose their business and financial activities in their annual 10-K reports. Each report typically spans hundreds of pages, making it difficult for human readers to identify and extract the material information efficiently. To solve the problem, I have ...
[ { "created": "Tue, 15 Aug 2023 01:25:34 GMT", "version": "v1" } ]
2023-08-16
[ [ "Chen", "Victor Zitian", "" ] ]
All public companies are required by federal securities law to disclose their business and financial activities in their annual 10-K reports. Each report typically spans hundreds of pages, making it difficult for human readers to identify and extract the material information efficiently. To solve the problem, I have fi...
2112.11701
Rui Zhao
Rui Zhao, Jinming Song, Yufeng Yuan, Hu Haifeng, Yang Gao, Yi Wu, Zhongqian Sun, Yang Wei
Maximum Entropy Population-Based Training for Zero-Shot Human-AI Coordination
Accepted by NeurIPS Cooperative AI Workshop, 2021, link: https://www.cooperativeai.com/workshop/neurips-2021#Workshop-Papers. Under review at a conference
null
null
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We study the problem of training a Reinforcement Learning (RL) agent that is collaborative with humans without using any human data. Although such agents can be obtained through self-play training, they can suffer significantly from distributional shift when paired with unencountered partners, such as humans. To miti...
[ { "created": "Wed, 22 Dec 2021 07:19:36 GMT", "version": "v1" }, { "created": "Mon, 23 May 2022 06:43:58 GMT", "version": "v2" }, { "created": "Mon, 27 Jun 2022 05:15:20 GMT", "version": "v3" } ]
2022-06-28
[ [ "Zhao", "Rui", "" ], [ "Song", "Jinming", "" ], [ "Yuan", "Yufeng", "" ], [ "Haifeng", "Hu", "" ], [ "Gao", "Yang", "" ], [ "Wu", "Yi", "" ], [ "Sun", "Zhongqian", "" ], [ "Wei", "Yang", "" ...
We study the problem of training a Reinforcement Learning (RL) agent that is collaborative with humans without using any human data. Although such agents can be obtained through self-play training, they can suffer significantly from distributional shift when paired with unencountered partners, such as humans. To mitiga...
2009.11465
Yanshi Luo
Yanshi Luo, Abdeslam Boularias and Mridul Aanjaneya
Model Identification and Control of a Low-Cost Wheeled Mobile Robot Using Differentiable Physics
null
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present the design of a low-cost wheeled mobile robot, and an analytical model for predicting its motion under the influence of motor torques and friction forces. Using our proposed model, we show how to analytically compute the gradient of an appropriate loss function, that measures the deviation between predicte...
[ { "created": "Thu, 24 Sep 2020 03:27:28 GMT", "version": "v1" } ]
2020-09-25
[ [ "Luo", "Yanshi", "" ], [ "Boularias", "Abdeslam", "" ], [ "Aanjaneya", "Mridul", "" ] ]
We present the design of a low-cost wheeled mobile robot, and an analytical model for predicting its motion under the influence of motor torques and friction forces. Using our proposed model, we show how to analytically compute the gradient of an appropriate loss function, that measures the deviation between predicted ...
2210.15593
Shikhar Makhija
Udit Kumar Agarwal, Shikhar Makhija, Varun Tripathi and Kunwar Singh
An Investigation into Neuromorphic ICs using Memristor-CMOS Hybrid Circuits
Bachelor's thesis
null
null
null
cs.NE cs.AR eess.IV eess.SP
http://creativecommons.org/licenses/by/4.0/
The memristance of a memristor depends on the amount of charge flowing through it and when current stops flowing through it, it remembers the state. Thus, memristors are extremely suited for implementation of memory units. Memristors find great application in neuromorphic circuits as it is possible to couple memory a...
[ { "created": "Fri, 19 Aug 2022 18:04:03 GMT", "version": "v1" } ]
2022-10-28
[ [ "Agarwal", "Udit Kumar", "" ], [ "Makhija", "Shikhar", "" ], [ "Tripathi", "Varun", "" ], [ "Singh", "Kunwar", "" ] ]
The memristance of a memristor depends on the amount of charge flowing through it and when current stops flowing through it, it remembers the state. Thus, memristors are extremely suited for implementation of memory units. Memristors find great application in neuromorphic circuits as it is possible to couple memory and...
1304.6777
Tauhid Zaman
Tauhid Zaman, Emily B. Fox, Eric T. Bradlow
A Bayesian approach for predicting the popularity of tweets
Published in at http://dx.doi.org/10.1214/14-AOAS741 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org)
Annals of Applied Statistics 2014, Vol. 8, No. 3, 1583-1611
10.1214/14-AOAS741
IMS-AOAS-AOAS741
cs.SI physics.soc-ph stat.AP
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We predict the popularity of short messages called tweets created in the micro-blogging site known as Twitter. We measure the popularity of a tweet by the time-series path of its retweets, which is when people forward the tweet to others. We develop a probabilistic model for the evolution of the retweets using a Baye...
[ { "created": "Thu, 25 Apr 2013 00:26:18 GMT", "version": "v1" }, { "created": "Mon, 3 Mar 2014 04:17:57 GMT", "version": "v2" }, { "created": "Mon, 24 Nov 2014 11:29:48 GMT", "version": "v3" } ]
2014-11-25
[ [ "Zaman", "Tauhid", "" ], [ "Fox", "Emily B.", "" ], [ "Bradlow", "Eric T.", "" ] ]
We predict the popularity of short messages called tweets created in the micro-blogging site known as Twitter. We measure the popularity of a tweet by the time-series path of its retweets, which is when people forward the tweet to others. We develop a probabilistic model for the evolution of the retweets using a Bayesi...
2312.01315
Wenlong Shi
Wenlong Shi, Changsheng Lu, Ming Shao, Yinjie Zhang, Siyu Xia, Piotr Koniusz
Few-shot Shape Recognition by Learning Deep Shape-aware Features
Accepted by WACV 2024; 8 pages for main paper
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Traditional shape descriptors have been gradually replaced by convolutional neural networks due to their superior performance in feature extraction and classification. The state-of-the-art methods recognize object shapes via image reconstruction or pixel classification. However , these methods are biased toward textu...
[ { "created": "Sun, 3 Dec 2023 08:12:23 GMT", "version": "v1" } ]
2023-12-05
[ [ "Shi", "Wenlong", "" ], [ "Lu", "Changsheng", "" ], [ "Shao", "Ming", "" ], [ "Zhang", "Yinjie", "" ], [ "Xia", "Siyu", "" ], [ "Koniusz", "Piotr", "" ] ]
Traditional shape descriptors have been gradually replaced by convolutional neural networks due to their superior performance in feature extraction and classification. The state-of-the-art methods recognize object shapes via image reconstruction or pixel classification. However , these methods are biased toward texture...
2201.01703
Nishant Sinha
Saurabh Kumar, Nishant Sinha
Probing TryOnGAN
5 pages, to appear in the proceedings of the 9th ACM IKDD CODS and 27th COMAD (CODS-COMAD '22)
null
null
null
cs.CV cs.LG
http://creativecommons.org/licenses/by/4.0/
TryOnGAN is a recent virtual try-on approach, which generates highly realistic images and outperforms most previous approaches. In this article, we reproduce the TryOnGAN implementation and probe it along diverse angles: impact of transfer learning, variants of conditioning image generation with poses and properties ...
[ { "created": "Wed, 5 Jan 2022 16:51:19 GMT", "version": "v1" } ]
2022-01-06
[ [ "Kumar", "Saurabh", "" ], [ "Sinha", "Nishant", "" ] ]
TryOnGAN is a recent virtual try-on approach, which generates highly realistic images and outperforms most previous approaches. In this article, we reproduce the TryOnGAN implementation and probe it along diverse angles: impact of transfer learning, variants of conditioning image generation with poses and properties of...
2307.08575
Romaric Neveu
Nicolas Aragon, Lo\"ic Bidoux, Jes\'us-Javier Chi-Dom\'inguez, Thibauld Feneuil, Philippe Gaborit, Romaric Neveu, Matthieu Rivain
MIRA: a Digital Signature Scheme based on the MinRank problem and the MPC-in-the-Head paradigm
null
null
null
null
cs.CR
http://creativecommons.org/publicdomain/zero/1.0/
We exploit the idea of [Fen22] which proposes to build an efficient signature scheme based on a zero-knowledge proof of knowledge of a solution of a MinRank instance. The scheme uses the MPCitH paradigm, which is an efficient way to build ZK proofs. We combine this idea with another idea, the hypercube technique intr...
[ { "created": "Mon, 17 Jul 2023 15:44:12 GMT", "version": "v1" } ]
2023-07-18
[ [ "Aragon", "Nicolas", "" ], [ "Bidoux", "Loïc", "" ], [ "Chi-Domínguez", "Jesús-Javier", "" ], [ "Feneuil", "Thibauld", "" ], [ "Gaborit", "Philippe", "" ], [ "Neveu", "Romaric", "" ], [ "Rivain", "Matthieu", ...
We exploit the idea of [Fen22] which proposes to build an efficient signature scheme based on a zero-knowledge proof of knowledge of a solution of a MinRank instance. The scheme uses the MPCitH paradigm, which is an efficient way to build ZK proofs. We combine this idea with another idea, the hypercube technique introd...
1606.04288
Polyvios Pratikakis
Alexandros Labrineas, Polyvios Pratikakis, Dimitrios S. Nikolopoulos, Angelos Bilas
BDDT-SCC: A Task-parallel Runtime for Non Cache-Coherent Multicores
null
null
null
null
cs.DC cs.PL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper presents BDDT-SCC, a task-parallel runtime system for non cache-coherent multicore processors, implemented for the Intel Single-Chip Cloud Computer. The BDDT-SCC runtime includes a dynamic dependence analysis and automatic synchronization, and executes OpenMP-Ss tasks on a non cache-coherent architecture. ...
[ { "created": "Tue, 14 Jun 2016 10:09:42 GMT", "version": "v1" } ]
2016-06-15
[ [ "Labrineas", "Alexandros", "" ], [ "Pratikakis", "Polyvios", "" ], [ "Nikolopoulos", "Dimitrios S.", "" ], [ "Bilas", "Angelos", "" ] ]
This paper presents BDDT-SCC, a task-parallel runtime system for non cache-coherent multicore processors, implemented for the Intel Single-Chip Cloud Computer. The BDDT-SCC runtime includes a dynamic dependence analysis and automatic synchronization, and executes OpenMP-Ss tasks on a non cache-coherent architecture. We...
2108.13205
Angel Romero
Angel Romero, Sihao Sun, Philipp Foehn, Davide Scaramuzza
Model Predictive Contouring Control for Time-Optimal Quadrotor Flight
17 pages, 16 figures. Video: https://www.youtube.com/watch?v=mHDQcckqdg4 This paper has been accepted for publication in the IEEE Transactions on Robotics (T-RO), 2022
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We tackle the problem of flying time-optimal trajectories through multiple waypoints with quadrotors. State-of-the-art solutions split the problem into a planning task - where a global, time-optimal trajectory is generated - and a control task - where this trajectory is accurately tracked. However, at the current sta...
[ { "created": "Mon, 30 Aug 2021 13:01:49 GMT", "version": "v1" }, { "created": "Fri, 1 Oct 2021 15:34:38 GMT", "version": "v2" }, { "created": "Thu, 17 Feb 2022 09:12:34 GMT", "version": "v3" }, { "created": "Wed, 4 May 2022 07:06:09 GMT", "version": "v4" } ]
2022-05-05
[ [ "Romero", "Angel", "" ], [ "Sun", "Sihao", "" ], [ "Foehn", "Philipp", "" ], [ "Scaramuzza", "Davide", "" ] ]
We tackle the problem of flying time-optimal trajectories through multiple waypoints with quadrotors. State-of-the-art solutions split the problem into a planning task - where a global, time-optimal trajectory is generated - and a control task - where this trajectory is accurately tracked. However, at the current state...
1911.08650
Jordan MacLachlan
Jordan MacLachlan, Yi Mei, Juergen Branke, Mengjie Zhang
Genetic Programming Hyper-Heuristics with Vehicle Collaboration for Uncertain Capacitated Arc Routing Problems
null
null
10.1162/evco_a_00267
null
cs.NE cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Due to its direct relevance to post-disaster operations, meter reading and civil refuse collection, the Uncertain Capacitated Arc Routing Problem (UCARP) is an important optimisation problem. Stochastic models are critical to study as they more accurately represent the real-world than their deterministic counterparts...
[ { "created": "Wed, 20 Nov 2019 00:55:00 GMT", "version": "v1" } ]
2019-11-21
[ [ "MacLachlan", "Jordan", "" ], [ "Mei", "Yi", "" ], [ "Branke", "Juergen", "" ], [ "Zhang", "Mengjie", "" ] ]
Due to its direct relevance to post-disaster operations, meter reading and civil refuse collection, the Uncertain Capacitated Arc Routing Problem (UCARP) is an important optimisation problem. Stochastic models are critical to study as they more accurately represent the real-world than their deterministic counterparts. ...
2211.14383
Yushun Dong
Yushun Dong, Song Wang, Jing Ma, Ninghao Liu, Jundong Li
Interpreting Unfairness in Graph Neural Networks via Training Node Attribution
Published as a conference paper at AAAI 2023
null
null
null
cs.LG cs.CY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Graph Neural Networks (GNNs) have emerged as the leading paradigm for solving graph analytical problems in various real-world applications. Nevertheless, GNNs could potentially render biased predictions towards certain demographic subgroups. Understanding how the bias in predictions arises is critical, as it guides t...
[ { "created": "Fri, 25 Nov 2022 21:52:30 GMT", "version": "v1" } ]
2022-11-29
[ [ "Dong", "Yushun", "" ], [ "Wang", "Song", "" ], [ "Ma", "Jing", "" ], [ "Liu", "Ninghao", "" ], [ "Li", "Jundong", "" ] ]
Graph Neural Networks (GNNs) have emerged as the leading paradigm for solving graph analytical problems in various real-world applications. Nevertheless, GNNs could potentially render biased predictions towards certain demographic subgroups. Understanding how the bias in predictions arises is critical, as it guides the...
2407.14387
Aurelio Sulser
Aurelio Sulser, Johann Wenckstern, Clara Kuempel
GLAudio Listens to the Sound of the Graph
null
ICML 2024 ELLIS Workshop on Geometry-grounded Representation Learning and Generative Modeling
null
null
cs.LG cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We propose GLAudio: Graph Learning on Audio representation of the node features and the connectivity structure. This novel architecture propagates the node features through the graph network according to the discrete wave equation and then employs a sequence learning architecture to learn the target node function fro...
[ { "created": "Fri, 19 Jul 2024 15:13:22 GMT", "version": "v1" } ]
2024-07-22
[ [ "Sulser", "Aurelio", "" ], [ "Wenckstern", "Johann", "" ], [ "Kuempel", "Clara", "" ] ]
We propose GLAudio: Graph Learning on Audio representation of the node features and the connectivity structure. This novel architecture propagates the node features through the graph network according to the discrete wave equation and then employs a sequence learning architecture to learn the target node function from ...
2303.11595
Yiming Chen
Yiming Chen, Jinyu Tian, Xiangyu Chen, and Jiantao Zhou
Effective Ambiguity Attack Against Passport-based DNN Intellectual Property Protection Schemes through Fully Connected Layer Substitution
Accepted to CVPR2023
null
null
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Since training a deep neural network (DNN) is costly, the well-trained deep models can be regarded as valuable intellectual property (IP) assets. The IP protection associated with deep models has been receiving increasing attentions in recent years. Passport-based method, which replaces normalization layers with pass...
[ { "created": "Tue, 21 Mar 2023 04:59:05 GMT", "version": "v1" } ]
2023-03-22
[ [ "Chen", "Yiming", "" ], [ "Tian", "Jinyu", "" ], [ "Chen", "Xiangyu", "" ], [ "Zhou", "Jiantao", "" ] ]
Since training a deep neural network (DNN) is costly, the well-trained deep models can be regarded as valuable intellectual property (IP) assets. The IP protection associated with deep models has been receiving increasing attentions in recent years. Passport-based method, which replaces normalization layers with passpo...
1708.00602
Subhadip Mukherjee
Subhadip Mukherjee and Chandra Sekhar Seelamantula
Phase Retrieval From Binary Measurements
null
null
10.1109/LSP.2018.2791102
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We consider the problem of signal reconstruction from quadratic measurements that are encoded as +1 or -1 depending on whether they exceed a predetermined positive threshold or not. Binary measurements are fast to acquire and inexpensive in terms of hardware. We formulate the problem of signal reconstruction using a ...
[ { "created": "Wed, 2 Aug 2017 04:46:07 GMT", "version": "v1" }, { "created": "Thu, 16 Nov 2017 10:41:25 GMT", "version": "v2" } ]
2018-03-14
[ [ "Mukherjee", "Subhadip", "" ], [ "Seelamantula", "Chandra Sekhar", "" ] ]
We consider the problem of signal reconstruction from quadratic measurements that are encoded as +1 or -1 depending on whether they exceed a predetermined positive threshold or not. Binary measurements are fast to acquire and inexpensive in terms of hardware. We formulate the problem of signal reconstruction using a co...
2205.03198
Paolo Baldi
Paolo Baldi and Hykel Hosni
A Logic-based Tractable Approximation of Probability
null
null
null
null
cs.LO cs.AI
http://creativecommons.org/licenses/by/4.0/
We provide a logical framework in which a resource-bounded agent can be seen to perform approximations of probabilistic reasoning. Our main results read as follows. First we identify the conditions under which propositional probability functions can be approximated by a hierarchy of depth-bounded Belief functions. Se...
[ { "created": "Fri, 6 May 2022 13:25:12 GMT", "version": "v1" } ]
2022-05-09
[ [ "Baldi", "Paolo", "" ], [ "Hosni", "Hykel", "" ] ]
We provide a logical framework in which a resource-bounded agent can be seen to perform approximations of probabilistic reasoning. Our main results read as follows. First we identify the conditions under which propositional probability functions can be approximated by a hierarchy of depth-bounded Belief functions. Seco...
0902.1284
Daniel Hsu
Daniel Hsu, Sham M. Kakade, John Langford, Tong Zhang
Multi-Label Prediction via Compressed Sensing
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We consider multi-label prediction problems with large output spaces under the assumption of output sparsity -- that the target (label) vectors have small support. We develop a general theory for a variant of the popular error correcting output code scheme, using ideas from compressed sensing for exploiting this spar...
[ { "created": "Sun, 8 Feb 2009 02:30:06 GMT", "version": "v1" }, { "created": "Tue, 2 Jun 2009 16:23:28 GMT", "version": "v2" } ]
2009-06-02
[ [ "Hsu", "Daniel", "" ], [ "Kakade", "Sham M.", "" ], [ "Langford", "John", "" ], [ "Zhang", "Tong", "" ] ]
We consider multi-label prediction problems with large output spaces under the assumption of output sparsity -- that the target (label) vectors have small support. We develop a general theory for a variant of the popular error correcting output code scheme, using ideas from compressed sensing for exploiting this sparsi...
2011.11827
Yunzhe Tao
Yunzhe Tao, Sahika Genc, Jonathan Chung, Tao Sun, Sunil Mallya
REPAINT: Knowledge Transfer in Deep Reinforcement Learning
Published at ICML 2021
null
null
null
cs.LG cs.AI cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Accelerating learning processes for complex tasks by leveraging previously learned tasks has been one of the most challenging problems in reinforcement learning, especially when the similarity between source and target tasks is low. This work proposes REPresentation And INstance Transfer (REPAINT) algorithm for knowl...
[ { "created": "Tue, 24 Nov 2020 01:18:32 GMT", "version": "v1" }, { "created": "Fri, 5 Feb 2021 18:57:25 GMT", "version": "v2" }, { "created": "Wed, 26 May 2021 05:25:23 GMT", "version": "v3" } ]
2021-05-27
[ [ "Tao", "Yunzhe", "" ], [ "Genc", "Sahika", "" ], [ "Chung", "Jonathan", "" ], [ "Sun", "Tao", "" ], [ "Mallya", "Sunil", "" ] ]
Accelerating learning processes for complex tasks by leveraging previously learned tasks has been one of the most challenging problems in reinforcement learning, especially when the similarity between source and target tasks is low. This work proposes REPresentation And INstance Transfer (REPAINT) algorithm for knowled...
2201.05478
Dinesh Garg
Philip Tetlow, Dinesh Garg, Leigh Chase, Mark Mattingley-Scott, Nicholas Bronn, Kugendran Naidoo, Emil Reinert
Towards a Semantic Information Theory (Introducing Quantum Corollas)
null
null
null
null
cs.IT math.IT quant-ph
http://creativecommons.org/licenses/by-sa/4.0/
The field of Information Theory is founded on Claude Shannon's seminal ideas relating to entropy. Nevertheless, his well-known avoidance of meaning (Shannon, 1948) still persists to this day, so that Information Theory remains poorly connected to many fields with clear informational content and a dependence on semant...
[ { "created": "Fri, 14 Jan 2022 14:33:13 GMT", "version": "v1" } ]
2022-01-17
[ [ "Tetlow", "Philip", "" ], [ "Garg", "Dinesh", "" ], [ "Chase", "Leigh", "" ], [ "Mattingley-Scott", "Mark", "" ], [ "Bronn", "Nicholas", "" ], [ "Naidoo", "Kugendran", "" ], [ "Reinert", "Emil", "" ] ]
The field of Information Theory is founded on Claude Shannon's seminal ideas relating to entropy. Nevertheless, his well-known avoidance of meaning (Shannon, 1948) still persists to this day, so that Information Theory remains poorly connected to many fields with clear informational content and a dependence on semantic...
2005.01889
Seonho Park
Seonho Park, George Adosoglou, Panos M. Pardalos
Interpreting Rate-Distortion of Variational Autoencoder and Using Model Uncertainty for Anomaly Detection
Corrected typos
null
null
null
cs.LG cs.IT math.IT stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Building a scalable machine learning system for unsupervised anomaly detection via representation learning is highly desirable. One of the prevalent methods is using a reconstruction error from variational autoencoder (VAE) via maximizing the evidence lower bound. We revisit VAE from the perspective of information th...
[ { "created": "Tue, 5 May 2020 00:03:48 GMT", "version": "v1" }, { "created": "Thu, 7 May 2020 16:59:36 GMT", "version": "v2" } ]
2020-05-08
[ [ "Park", "Seonho", "" ], [ "Adosoglou", "George", "" ], [ "Pardalos", "Panos M.", "" ] ]
Building a scalable machine learning system for unsupervised anomaly detection via representation learning is highly desirable. One of the prevalent methods is using a reconstruction error from variational autoencoder (VAE) via maximizing the evidence lower bound. We revisit VAE from the perspective of information theo...
2012.04767
Clement Moreau
Clement Moreau and Thomas Devogele and Laurent Etienne and Veronika Peralta and Cyril de Runz
Methodology for Mining, Discovering and Analyzing Semantic Human Mobility Behaviors
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Various institutes produce large semantic datasets containing information regarding daily activities and human mobility. The analysis and understanding of such data are crucial for urban planning, socio-psychology, political sciences, and epidemiology. However, none of the typical data mining processes have been cust...
[ { "created": "Tue, 8 Dec 2020 22:24:19 GMT", "version": "v1" }, { "created": "Sun, 20 Dec 2020 17:23:48 GMT", "version": "v2" } ]
2020-12-22
[ [ "Moreau", "Clement", "" ], [ "Devogele", "Thomas", "" ], [ "Etienne", "Laurent", "" ], [ "Peralta", "Veronika", "" ], [ "de Runz", "Cyril", "" ] ]
Various institutes produce large semantic datasets containing information regarding daily activities and human mobility. The analysis and understanding of such data are crucial for urban planning, socio-psychology, political sciences, and epidemiology. However, none of the typical data mining processes have been custom...
1011.4597
Elena Veronica Belmega
E. V. Belmega and S. Lasaulce
Energy-Efficient Precoding for Multiple-Antenna Terminals
null
null
10.1109/TSP.2010.2086451
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The problem of energy-efficient precoding is investigated when the terminals in the system are equipped with multiple antennas. Considering static and fast-fading multiple-input multiple-output (MIMO) channels, the energy-efficiency is defined as the transmission rate to power ratio and shown to be maximized at low t...
[ { "created": "Sat, 20 Nov 2010 18:45:23 GMT", "version": "v1" } ]
2015-05-20
[ [ "Belmega", "E. V.", "" ], [ "Lasaulce", "S.", "" ] ]
The problem of energy-efficient precoding is investigated when the terminals in the system are equipped with multiple antennas. Considering static and fast-fading multiple-input multiple-output (MIMO) channels, the energy-efficiency is defined as the transmission rate to power ratio and shown to be maximized at low tra...
1702.04510
Christian Hadiwinoto
Christian Hadiwinoto, Hwee Tou Ng
A Dependency-Based Neural Reordering Model for Statistical Machine Translation
7 pages, 3 figures, Proceedings of AAAI-17
Proceedings of AAAI-17 (2017)
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In machine translation (MT) that involves translating between two languages with significant differences in word order, determining the correct word order of translated words is a major challenge. The dependency parse tree of a source sentence can help to determine the correct word order of the translated words. In t...
[ { "created": "Wed, 15 Feb 2017 09:08:21 GMT", "version": "v1" } ]
2017-02-16
[ [ "Hadiwinoto", "Christian", "" ], [ "Ng", "Hwee Tou", "" ] ]
In machine translation (MT) that involves translating between two languages with significant differences in word order, determining the correct word order of translated words is a major challenge. The dependency parse tree of a source sentence can help to determine the correct word order of the translated words. In thi...
1804.10123
Sam Leroux
Sam Leroux, Pavlo Molchanov, Pieter Simoens, Bart Dhoedt, Thomas Breuel, Jan Kautz
IamNN: Iterative and Adaptive Mobile Neural Network for Efficient Image Classification
ICLR 2018 Workshop track
null
null
null
cs.CV cs.NE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Deep residual networks (ResNets) made a recent breakthrough in deep learning. The core idea of ResNets is to have shortcut connections between layers that allow the network to be much deeper while still being easy to optimize avoiding vanishing gradients. These shortcut connections have interesting side-effects that ...
[ { "created": "Thu, 26 Apr 2018 15:57:00 GMT", "version": "v1" } ]
2018-04-30
[ [ "Leroux", "Sam", "" ], [ "Molchanov", "Pavlo", "" ], [ "Simoens", "Pieter", "" ], [ "Dhoedt", "Bart", "" ], [ "Breuel", "Thomas", "" ], [ "Kautz", "Jan", "" ] ]
Deep residual networks (ResNets) made a recent breakthrough in deep learning. The core idea of ResNets is to have shortcut connections between layers that allow the network to be much deeper while still being easy to optimize avoiding vanishing gradients. These shortcut connections have interesting side-effects that ma...