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检索条件"机构=Key Laboratory of Data Mining and Knowledge Engineering"
1784 条 记 录,以下是1651-1660 订阅
排序:
Neural Combinatorial Optimization Algorithms for Solving Vehicle Routing Problems: A Comprehensive Survey with Perspectives
arXiv
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arXiv 2024年
作者: Wu, Xuan Wang, Di Wen, Lijie Xiao, Yubin Wu, Chunguo Wu, Yuesong Yu, Chaoyu Maskell, Douglas L. Zhou, You The Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education College of Computer Science and Technology Jilin university Changchun130012 China The Joint NTU-UBC Research Centre of Excellence in Active Living for the Elderly Nanyang Technological University 639798 Singapore The School of Software Tsinghua University Beijing100084 China The College of Computing and Data Science Nanyang Technological University 639798 Singapore
Although several surveys on Neural Combinatorial Optimization (NCO) solvers specifically designed to solve Vehicle Routing Problems (VRPs) have been conducted. These existing surveys did not cover the state-of-the-art... 详细信息
来源: 评论
Adaptive structure-constrained robust latent low-rank coding for image recovery
arXiv
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arXiv 2019年
作者: Zhang, Zhao Wang, Lei Li, Sheng Wang, Yang Zhang, Zheng Zha, Zhengjun Wang, Meng School of Computer Science and Technology Soochow University Suzhou215006 China Key Laboratory of Knowledge Engineering with Big Data Ministry of Education Hefei University of Technology School of Computer Science and Information Engineering Hefei University of Technology Hefei China Department of Computer Science University of Georgia 549 Boyd GSRC AthensGA30602 Shenzhen China School of Information Science and Technology University of Science and Technology of China Hefei China
In this paper, we propose a robust representation learning model called Adaptive Structure-constrained Low-Rank Coding (AS-LRC) for the latent representation of data. To recover the underlying subspaces more accuratel... 详细信息
来源: 评论
How likely is a random graph shift-enabled?
arXiv
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arXiv 2021年
作者: Chen, Liyan Cheng, Samuel Stankovic, Vladimir Stankovic, Lina Key Laboratory of Oceanographic Big Data Mining & Application of Zhejiang Province Zhejiang Ocean University Zhejiang Zhoushan316022 China Department of Computer Science and Technology Tongji University Shanghai201804 China School of Electrical and Computer Engineering University of Oklahoma OK74105 United States Department of Electronic and Electrical Engineering University of Strathclyde GlasgowG1 1XW United Kingdom
The shift-enabled property of an underlying graph is essential in designing distributed filters. This article discusses when a random graph is shift-enabled. In particular, popular graph models Erdős–Rényi (ER),... 详细信息
来源: 评论
Dense residual network: Enhancing global dense feature flow for character recognition
arXiv
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arXiv 2020年
作者: Zhang, Zhao Tang, Zemin Wang, Yang Zhang, Zheng Zhan, Choujun Zha, Zhengjun Wang, Meng School of Computer Science and Information Engineering Hefei University of Technology Hefei230009 China Key Laboratory of Knowledge Engineering with Big Data Ministry of Education Intelligent Interconnected Systems Laboratory of Anhui Province Hefei University of Technology Hefei230009 China School of Computer Science and Technology Soochow University Suzhou215006 China Shenzhen China School of Computer South China Normal University Guangzhou510631 China Deparmtment of Computer Science and Technology University of Science and Technology of China Hefei China
Deep Convolutional Neural Networks (CNNs), such as Dense Convolutional Network (DenseNet), have achieved great success for image representation learning by capturing deep hierarchical features. However, most existing ... 详细信息
来源: 评论
Triplet Deep Subspace Clustering via Self-Supervised data Augmentation
Triplet Deep Subspace Clustering via Self-Supervised Data Au...
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IEEE International Conference on data mining (ICDM)
作者: Zhao Zhang Xianzhen Li Haijun Zhang Yi Yang Shuicheng Yan Meng Wang School of Computer Science and Information Engineering Hefei University of Technology Hefei China Key Laboratory of Knowledge Engineering with Big Data (Ministry of Education) & Intelligent Interconnected Systems Laboratory of Anhui Province Hefei University of Technology Hefei China School of Computer Science and Technology Soochow University Suzhou China Harbin Institute of Technology (Shenzhen) Shenzhen China Centre for Artificial Intelligence University of Technology Sydney Sydney NSW Australia Sea AI Lab (SAIL) & National University of Singapore Singapore
Deep subspace clustering (DSC) with the auto-encoder and self-expression layer is of great concern due to encouraging performance. However, existing methods usually adopt a “single-task” strategy based on a single d... 详细信息
来源: 评论
Retracted: Measurement and analysis of Chinese journal discriminative capacity
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Journal of Informetrics 2021年 第1期15卷
作者: Baolong Zhang Hao Wang Sanhong Deng Xinning Su School of Information Management Nanjing University Nanjing 210023 China Jiangsu Key Laboratory of Data Engineering and Knowledge Service Nanjing 210023 China
来源: 评论
knowledge graph enhanced neural collaborative recommendation
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Expert Systems with Applications 2021年 164卷 113992-113992页
作者: Sang, Lei Xu, Min Qian, Shengsheng Wu, Xindong Key Laboratory of Knowledge Engineering with Big Data (Hefei University of Technology) Ministry of Education Hefei 230009 China Faculty of Engineering and Information Technology University of Technology Sydney Sydney 2007 Australia School of Computer Science and Information Engineering Hefei University of Technology Hefei 230009 China Institute of Automation Chinese Academy of Sciences Beijing 100190 China Mininglamp Academy of Sciences Mininglamp Technology Beijing 100084 China
Existing neural collaborative filtering (NCF) recommendation methods suffer from severe sparsity problem. knowledge Graph (KG), which commonly consists of fruitful connected facts about items, presents an unprecedente... 详细信息
来源: 评论
Disentangled Representation Learning with Transmitted Information Bottleneck
arXiv
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arXiv 2023年
作者: Dang, Zhuohang Luo, Minnan Jia, Chengyou Dai, Guang Wang, Jihong Chang, Xiaojun Wang, Jingdong The School of Computer Science and Technology The Ministry of Education Key Laboratory of Intelligent Networks and Network Security The Shaanxi Province Key Laboratory of Big Data Knowledge Engineering Xi'an Jiaotong University Shaanxi Xi’an710049 China The SGIT AI Laboratory Xi’an710048 China The State Grid Shaanxi Electric Power Company Ltd. State Grid Corporation of China Xi’an710048 China The School of Information Science and Technology University of Science and Technology of China Hefei230026 China Abu Dhabi United Arab Emirates Baidu Inc Beijing100085 China
Encoding only the task-related information from the raw data, i.e., disentangled representation learning, can greatly contribute to the robustness and generalizability of models. Although significant advances have bee... 详细信息
来源: 评论
Research on Pre-view Method of Safety Level of Cascading Trip for Power Grid  6th
Research on Pre-view Method of Safety Level of Cascading Tri...
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6th International Conference on Advanced Machine Learning Technologies and Applications, AMLTA 2021
作者: Deng, Huiqiong Li, Qinbin Zheng, Rongjin Li, Peiqiang Chang, Kuo-Chi School of Information Science and Engineering Fujian University of Technology No. 3 Xueyuan Road University Town Minhou Fuzhou Fujian350118 China Fujian Provincial University Engineering Research Center of Smart Grid Simulation Analysis and Integrated Control Fuzhou Fujian350118 China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology No. 3 Xueyuan Road University Town Minhou Fuzhou Fujian350118 China College of Mechanical & Electrical Engineering National Taipei University of Technology No. 1 Section 3 Zhongxiao East Road Taipei10608 Taiwan Department of Business Administration North Borneo University College Lot 47 Block-F Alamesra Permai Plaza 2 Jln Sulaman Kota Kinabalu Sabah88400 Malaysia
This article introduces a method by which the power grid's security level can be observed in advance based on the expected initial failure. Firstly, based on the general form of cascading trip, this paper gives a ... 详细信息
来源: 评论
Biomarker-guided heterogeneity analysis of genetic regulations via multivariate sparse fusion
arXiv
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arXiv 2022年
作者: Zhang, Sanguo Hu, Xiaonan Luo, Ziye Jiang, Yu Sun, Yifan Ma, Shuangge No. 59 Zhongguancun Street Haidian District Beijing100872 China School of Mathematical Sciences Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Science Beijing China Center of Applied Statistics School of Statistics Renmin University of China Beijing China School of Public Health University of Memphis Tennessee United States Department of Biostatistics Yale University Connecticut United States 60 College ST New HavenCT06520 United States
Heterogeneity is a hallmark of many complex diseases. There are multiple ways of defining heterogeneity, among which the heterogeneity in genetic regulations, for example GEs (gene expressions) by CNVs (copy number va... 详细信息
来源: 评论