Discrete and Parameter-Free Multiple Kernel k-Means

被引：0
|
作者：
Wang, Rong [1 ]
Lu, Jitao [2 ]
Lu, Yihang [2 ]
Nie, Feiping [2 ]
Li, Xuelong [1 ]
机构：
[1] School of Artificial Intelligence, Optics and Electronics (IOPEN), Key Laboratory of Intelligent Interaction and Applications, Ministry of Industry and Information Technology, Northwestern Polytechnical University, Shaanxi, Xi'an,710072, China
[2] School of Computer Science, School of Artificial Intelligence, Optics and Electronics (IOPEN), Key Laboratory of Intelligent Interaction and Applications, Ministry of Industry and Information Technology, Northwestern Polytechnical University, Shaanxi, Xi'a
来源：
IEEE Transactions on Image Processing | 2022年 / 31卷
关键词：
This work was supported in part by the National Key Research and Development Program of China under Grant 2018AAA0101902; in part by the Natural Science Basic Research Program of Shaanxi under Grant 2021JM-071; in part by the National Natural Science Foundation of China under Grant 62176212; Grant; 61936014; and Grant 61772427; and in part by the Fundamental Research Funds for the Central Universities under Grant G2019KY0501;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
引用
收藏
页码：2796 / 2808
相关论文
共 50 条
  • [41] Multiple Kernel k-Means Clustering with Matrix-Induced Regularization
    Liu, Xinwang
    Dou, Yong
    Yin, Jianping
    Wang, Lei
    Zhu, En
    THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, 2016, : 1888 - 1894
  • [42] Unified and View-Specific Multiple Kernel K-Means Clustering
    Zhang, Yujing
    Wang, Siwei
    Zhu, En
    DATABASE AND EXPERT SYSTEMS APPLICATIONS, DEXA 2021, PT I, 2021, 12923 : 51 - 62
  • [43] On the Existence of Kernel Function for Kernel-Trick of k-Means
    Klopotek, Mieczyslaw A.
    FOUNDATIONS OF INTELLIGENT SYSTEMS, ISMIS 2017, 2017, 10352 : 97 - 104
  • [44] A new formulation of sparse multiple kernel k-means clustering and its applications
    Qu, Wentao
    Xiu, Xianchao
    Sun, Jun
    Kong, Lingchen
    STATISTICAL ANALYSIS AND DATA MINING, 2023, 16 (05) : 436 - 455
  • [45] ELM based Multiple Kernel k-means with Diversity-Induced Regularization
    Zhao, Yang
    Dou, Yong
    Liu, Xinwang
    Li, Teng
    2016 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2016, : 2699 - 2705
  • [46] Approximation of Kernel k-Means for Streaming Data
    Havens, Timothy C.
    2012 21ST INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR 2012), 2012, : 509 - 512
  • [47] Supervised kernel density estimation K-means
    Bortoloti, Frederico Damasceno
    de Oliveira, Elias
    Ciarelli, Patrick Marques
    EXPERT SYSTEMS WITH APPLICATIONS, 2021, 168
  • [48] KERNEL MATRIX TRIMMING FOR IMPROVED KERNEL K-MEANS CLUSTERING
    Tsapanos, Nikolaos
    Tefas, Anastasios
    Nikolaidis, Nikolaos
    Pitas, Ioannis
    2015 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP), 2015, : 2285 - 2289
  • [49] Localized Incomplete Multiple Kernel k-Means With Matrix-Induced Regularization
    Li, Miaomiao
    Xia, Jingyuan
    Xu, Huiying
    Liao, Qing
    Zhu, Xinzhong
    Liu, Xinwang
    IEEE TRANSACTIONS ON CYBERNETICS, 2023, 53 (06) : 3479 - 3492
  • [50] Kernel K-Means Sampling for Nystrom Approximation
    He, Li
    Zhang, Hong
    IEEE TRANSACTIONS ON IMAGE PROCESSING, 2018, 27 (05) : 2108 - 2120
12345