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检索条件"机构=Research Laboratory of Machine Learning and Pervasive Computing"
73 条 记 录,以下是21-30 订阅
排序:
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
RVPD: An Automated System for Calculating the Tortuosity and Bifurcation Angles of Retinal Vessels to Predict Diseases
RVPD: An Automated System for Calculating the Tortuosity and...
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IEEE International Symposium on Biomedical Imaging
作者: Guangzhengao Yang Xingyu Luo Jie Zhao Fangfang Fan Haoshen Li Bin Dong Li Zhang Yan Zhang Center for Data Science Peking University China Department of Cardiology Peking University First Hospital China National Engineering Laboratory for Big Data Analysis and Applications Peking University China Peking University Changsha Institute for Computing and Digital Economy China Beijing International Center for Mathematical Research Peking University China Center for Machine Learning Research Peking University China National Biomedical Imaging Center Peking University China
Hypertension and diabetes are known to potentially cause morphological changes in the retinal capillary system, yet quantifying these changes presents significant challenges. This research addresses this issue by desi... 详细信息
来源: 评论
On Error Bounds of Inequalities 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
Error bounds are central objects in optimization theory and its applications. They were for a long time restricted only to the theory before becoming over the course of time a field of itself. This paper is devoted to... 详细信息
来源: 评论
Time Series Domain Adaptation via Latent Invariant Causal Mechanism
arXiv
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arXiv 2025年
作者: Cai, Ruichu Huang, Junxian Yang, Zhenhui Li, Zijian Eldele, Emadeldeen Wu, Min Sun, Fuchun School of Computer Science Guangdong University of Technology Guangzhou510006 China Peng Cheng Laboratory Shenzhen518066 China School of Computing Guangdong University of Technology Guangzhou510006 China Machine Learning Department Mohamed bin Zayed University of Artificial Intelligence Abu Dhabi United Arab Emirates Institute for Infocomm Research A*STAR Singapore Centre for Frontier AI Research A*STAR Singapore Department of Computer Science and Technology Tsinghua University Beijing China
Time series domain adaptation aims to transfer the complex temporal dependence from the labeled source domain to the unlabeled target domain. Recent advances leverage the stable causal mechanism over observed variable...
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
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
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
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
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
Large language models illuminate a progressive pathway to artificial intelligent healthcare assistant
Medicine Plus
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Medicine Plus 2024年 第2期1卷 102-124页
作者: Mingze Yuan Peng Bao Jiajia Yuan Yunhao Shen Zifan Chen Yi Xie Jie Zhao Quanzheng Li Yang Chen Li Zhang Lin Shen Bin Dong Center for Data Science Peking UniversityBeijing 100871China Department of Gastrointestinal Oncology Key Laboratory of Carcinogenesis and Translational Research(Ministry of Education)Peking University Cancer Hospital and Institute Beijing 100142China National Engineering Laboratory for Big Data Analysis and Applications Peking UniversityBeijing 100871China Beijing International Center for Mathematical Research Peking UniversityBeijing 100871China Center for Machine Learning Research Peking University Beijing 100871China National Biomedical Imaging Center Peking UniversityBeijing 100871China Peking University Changsha Institute for Computing and Digital Economy Changsha 410205China Massachusetts General Hospital Boston MA 02114-2696USA Harvard Medical School BostonMA 02115USA
With the rapid development of artificial intelligence,large language models(LLMs)have shown promising capabilities in mimicking human-level language comprehen-sion and *** has sparked significant interest in applying ... 详细信息
来源: 评论