A New Semidefinite Programming for Semi-supervised Support Vector Machines

被引：0
|
作者：
Chen, Yi [1 ]
Bai, Yanqin [1 ]
机构：
[1] Shanghai Univ, Dept Math, Shanghai 200444, Peoples R China
来源：
PROCEEDINGS OF THE THIRD INTERNATIONAL WORKSHOP ON MATRIX ANALYSIS AND APPPLICATIONS, VOL 1 | 2009年
关键词：
semi-supervised SVMs; semidefinite programming; machine learning; OPTIMIZATION;
D O I：
暂无
中图分类号：
O1 [数学];
学科分类号：
0701 ; 070101 ;
摘要：
The problem of semi-supervised SVMs, which constructs a SVM using both the training data and unlabeled data has been formulated as an integer optimization problem. In this paper, we present a semidefinite programming formation for the problem of semi-supervised SVMs by using the approach based on the convex relaxation. The aim is to use the efficient interior point algorithms to solve SDP model of the problem of semi-supervised SVMs and obtain an approximation of the optimal labeling.
引用
收藏
页码：65 / 68
页数：4
相关论文
共 50 条
  • [11] Conic Relaxations for Semi-supervised Support Vector Machines
    Yanqin Bai
    Xin Yan
    Journal of Optimization Theory and Applications, 2016, 169 : 299 - 313
  • [12] The Model Selection for Semi-supervised Support Vector Machines
    Zhao, Ying
    Zhang, Jian-pei
    Yang, Jing
    ICICSE: 2008 INTERNATIONAL CONFERENCE ON INTERNET COMPUTING IN SCIENCE AND ENGINEERING, PROCEEDINGS, 2008, : 102 - 105
  • [13] Semi-supervised Support Vector Machines - A Genetic Algorithm Approach
    Lazarova, Gergana
    NEURAL INFORMATION PROCESSING, ICONIP 2016, PT II, 2016, 9948 : 241 - 249
  • [14] Semi-supervised support vector machines for unlabeled data classification
    Fung, G
    Mangasarian, OL
    OPTIMIZATION METHODS & SOFTWARE, 2001, 15 (01): : 29 - 44
  • [15] Semi-supervised support vector machines for data classification with uncertainty
    Ling, J
    Li, S
    ICEMS 2005: PROCEEDINGS OF THE EIGHTH INTERNATIONAL CONFERENCE ON ELECTRICAL MACHINES AND SYSTEMS, VOLS 1-3, 2005, : 2278 - 2281
  • [16] Help-Training for semi-supervised support vector machines
    Adankon, Mathias M.
    Cheriet, Mohamed
    PATTERN RECOGNITION, 2011, 44 (09) : 2220 - 2230
  • [17] A fuzzy semi-supervised support vector machines approach to hypertext categorization
    Benbrahim, Houda
    Bramer, Max
    ARTIFICIAL INTELLIGENCE IN THEORY AND PRACTICE II, 2008, 276 : 97 - 106
  • [18] Co-tracking using semi-supervised support vector machines
    Tang, Feng
    Brennan, Shane
    Zhao, Qi
    Tao, Hai
    2007 IEEE 11TH INTERNATIONAL CONFERENCE ON COMPUTER VISION, VOLS 1-6, 2007, : 992 - 999
  • [19] Semi-supervised multitemporal classification with support vector machines and genetic algorithms
    Ghoggali, Noureddine
    Melgani, Farid
    IGARSS: 2007 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-12: SENSING AND UNDERSTANDING OUR PLANET, 2007, : 2577 - 2580
  • [20] Unsupervised and semi-supervised two-class support vector machines
    Kun, Zhao
    Ying-Jie, Tian
    Nai-Yang, Deng
    ICDM 2006: SIXTH IEEE INTERNATIONAL CONFERENCE ON DATA MINING, WORKSHOPS, 2006, : 813 - +
12345