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检索条件"机构=Research Laboratory of Machine Learning and Pervasive Computing"
75 条 记 录,以下是41-50 订阅
排序:
Improving Generative Model-based Unfolding with Schrödinger Bridges
arXiv
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arXiv 2023年
作者: Diefenbacher, Sascha Liu, Guan-Horng Mikuni, Vinicius Nachman, Benjamin Nie, Weili Physics Division Lawrence Berkeley National Laboratory BerkeleyCA94720 United States Autonomous Control and Decision Systems Laboratory Georgia Institute of Technology AtlantaGA30332 United States National Energy Research Scientific Computing Center Berkeley Lab BerkeleyCA94720 United States Berkeley Institute for Data Science University of California BerkeleyCA94720 United States Machine Learning Research Group NVIDIA Research United States
machine learning-based unfolding has enabled unbinned and high-dimensional differential cross section measurements. Two main approaches have emerged in this research area: one based on discriminative models and one ba... 详细信息
来源: 评论
Consensus-Based Optimization Methods Converge Globally
arXiv
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arXiv 2021年
作者: Fornasier, Massimo Klock, Timo Riedl, Konstantin Technical University of Munich School of Computation Information and Technology Department of Mathematics Munich Germany Munich Center for Machine Learning Munich Germany Munich Data Science Institute Munich Germany Simula Research Laboratory Department of Numerical Analysis and Scientific Computing Oslo Norway University of San Diego Department of Mathematics San DiegoCA United States
In this paper, we study consensus-based optimization (CBO), which is a multi-agent metaheuristic derivative-free optimization method that can globally minimize nonconvex nonsmooth functions and is amenable to theoreti... 详细信息
来源: 评论
Primal Characterizations of Stability of Error Bounds for Semi-infinite Convex Constraint Systems in Banach Spaces
arXiv
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arXiv 2023年
作者: Wei, Zhou Théra, Michel Yao, Jen-Chih Hebei Key Laboratory of Machine Learning and Computational Intelligence College of Mathematics and Information Science Hebei University Baoding071002 China XLIM UMR CNRS 7252 Université de Limoges Limoges France Federation University Australia Ballarat Australia Research Center for Interneural Computing China Medical University Hospital China Medical University Taichung Taiwan
This article is devoted to the stability of error bounds (local and global) for semi-infinite convex constraint systems in Banach spaces. We provide primal characterizations of the stability of local and global error ... 详细信息
来源: 评论
Cooperative Co-evolution for large scale optimization through more frequent random grouping
Cooperative Co-evolution for large scale optimization throug...
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Congress on Evolutionary Computation
作者: Mohammad Nabi Omidvar Xiaodong Li Zhenyu Yang Xin Yao Evolutionary Computing and Machine Learning Group (ECML) the School of Computer Science and IT RMIT University Melbourne VIC Australia Nature Inspired Computation and Application Laboratory Department of Computer Science and Technology University of Science and Technology Hefei Anhui China Centre of Excellence of Research in Computational Intelligence and Applications (CERCIA) School of Computer Science University of Binningham Birmingham UK
In this paper we propose three techniques to improve the performance of one of the major algorithms for large scale continuous global function optimization. Multilevel Cooperative Co-evolution (MLCC) is based on a Coo... 详细信息
来源: 评论
Perturbation Analysis of Error Bounds for Convex Functions on Banach Spaces
arXiv
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arXiv 2024年
作者: Wei, Zhou Théra, Michel Yao, Jen-Chih Hebei Key Laboratory of Machine Learning and Computational Intelligence College of Mathematics and Information Science Hebei University Baoding071002 China XLIM UMR CNRS 7252 Université de Limoges Limoges France Research Center for Interneural Computing China Medical University Hospital China Medical University Taichung Taiwan Academy of Romanian Scientists Bucharest50044 Romania
This paper focuses on the stability of both local and global error bounds for a proper lower semicontinuous convex function defined on a Banach space. Without relying on any dual space information, we first provide pr... 详细信息
来源: 评论
Subtransversality and Strong CHIP of Closed Sets in Asplund Spaces
arXiv
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arXiv 2023年
作者: Wei, Zhou Théra, Michel Yao, Jen-Chih Hebei Key Laboratory of Machine Learning and Computational Intelligence College of Mathematics and Information Science Hebei University Baoding071002 China XLIM UMR CNRS 7252 Université de Limoges Limoges France Research Center for Interneural Computing China Medical University Hospital China Medical University Taichung Taiwan Academy of Romanian Scientists Bucharest50044 Romania
In this paper, we mainly study subtransversality and two types of strong CHIP (given via Fréchet and limiting normal cones) for a collection of finitely many closed sets. We first prove characterizations of Asplu... 详细信息
来源: 评论
Deep Sensor Fusion with Pyramid Fusion Networks for 3D Semantic Segmentation
Deep Sensor Fusion with Pyramid Fusion Networks for 3D Seman...
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IEEE Symposium on Intelligent Vehicle
作者: Hannah Schieber Fabian Duerr Torsten Schoen rgen Beyerer Human-Centered Computing and Extended Reality Friedrich-Alexander University (FAU) Erlangen-N&#x00FC rnberg Erlangen Germany Vision and Fusion Laboratory Karlsruhe Institute of Technology Karlsruhe Germany Research Institute Almotion Bavaria Technische Hochschule Ingolstadt Ingolstadt Germany Fraunhofer Institute of Optronics System Technologies and Image Exploitation (IOSB) Fraunhofer Center of Machine Learning Karlsruhe Germany
Robust environment perception for autonomous vehicles is a tremendous challenge, which makes a diverse sensor set with e.g. camera, lidar and radar crucial. In the process of understanding the recorded sensor data, 3D... 详细信息
来源: 评论
Decision-based black-box attack against vision transformers via patch-wise adversarial removal  22
Decision-based black-box attack against vision transformers ...
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Proceedings of the 36th International Conference on Neural Information Processing Systems
作者: Yucheng Shi Yahong Han Yu-an Tan Xiaohui Kuang College of Intelligence and Computing and Tianjin Key Lab of Machine Learning Tianjin University Tianjin China and Engineering Research Center of City Intelligence and Digital Governance Ministry of Education of the People's Republic of China School of Cyberspace Science and Technology Beijing Institute of Technology Beijing China National Key Laboratory of Science and Technology on Information System Security Beijing China
Vision transformers (ViTs) have demonstrated impressive performance and stronger adversarial robustness compared to Convolutional Neural Networks (CNNs). On the one hand, ViTs' focus on global interaction between ...
来源: 评论
GSLB: The Graph Structure learning Benchmark  37
GSLB: The Graph Structure Learning Benchmark
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37th Conference on Neural Information Processing Systems, NeurIPS 2023
作者: Li, Zhixun Wang, Liang Sun, Xin Luo, Yifan Zhu, Yanqiao Chen, Dingshuo Luo, Yingtao Zhou, Xiangxin Liu, Qiang Wu, Shu Yu, Jeffrey Xu Department of Systems Engineering and Engineering Management The Chinese University of Hong Kong Hong Kong Center for Research on Intelligent Perception and Computing State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences China School of Artificial Intelligence University of Chinese Academy of Sciences China Department of Automation University of Science and Technology of China China School of Cyberspace Security Beijing University of Posts and Telecommunications China Department of Computer Science University of California Los Angeles United States Heinz College of Information Systems and Public Policy Machine Learning Department School of Computer Science Carnegie Mellon University United States
Graph Structure learning (GSL) has recently garnered considerable attention due to its ability to optimize both the parameters of Graph Neural Networks (GNNs) and the computation graph structure simultaneously. Despit... 详细信息
来源: 评论
Predicting Response to Patients with Gastric Cancer Via a Dynamic-Aware Model with Longitudinal Liquid Biopsy Data
SSRN
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SSRN 2024年
作者: Chen, Zifan Zhao, Jie Li, Yanyan Li, Yilin Liu, Huimin Feng, Xujiao Nan, Xinyu Dong, Bin Shen, Lin Chen, Yang Zhang, Li Center for Data Science Peking University Beijing China Department of Gastrointestinal Oncology Key Laboratory of Carcinogenesis and Translational Research Ministry of Education Peking University Cancer Hospital and Institute Beijing China National Engineering Laboratory for Big Data Analysis and Applications Peking University Beijing China Guangzhou Medical University Guangzhou China Peking University Beijing China Center for Machine Learning Research Peking University Beijing China Peking University Changsha Institute for Computing and Digital Economy Changsha China
Gastric cancer (GC) presents challenges in predicting treatment responses due to its patient-specific heterogeneity. Recently, liquid biopsies have become recognized as a valuable data modality, offering essential cel... 详细信息
来源: 评论