|
|
【答案】应助回帖
★ ★ ★ ★ ★
baroshi: 金币+5, ★★★★★最佳答案 2014-09-21 18:56:25
sunshan4379: LS-EPI+1, 感谢应助！ 2014-09-21 19:36:28
Selective multiple kernel learning for classification with ensemble strategy
作者:Sun, T (Sun, Tao)[ 1 ] ; Jiao, LC (Jiao, Licheng)[ 1 ] ; Liu, F (Liu, Fang)[ 2 ] ; Wang, S (Wang, Shuang)[ 1 ] ; Feng, J (Feng, Jie)[ 1 ]
PATTERN RECOGNITION
卷: 46
期: 11
页: 3081-3090
DOI: 10.1016/j.patcog.2013.04.003
出版年: NOV 2013
查看期刊信息
摘要
Multiple Kernel Learning (MKL) aims to seek a better result than single kernel learning by combining a compact set of sub-kernels. However, MKL. with L1-norm easily discards the sub-kernels with complementary information and MKL with Lp-norm(p >= 2) often gets the redundant solution. To address these problems, a Selective Multiple Kernel Learning (SMKL) method, inspired by Ensemble Learning (EL), is proposed. Comparing MKL with Lp-norm(p >= 2), SMKL obtains a sparse solution by a pre-selection procedure. Comparing MKL with Lp-norm, SMKL preserves the sub-kernels with complementary information by guaranteeing the high discrimination and large diversity of pre-selected sub-kernels. For quantifying the discrimination and diversity of sub-kernels, a new kernel evaluation is designed. SMKL reduces the scale of MKL optimization and saves the memory storing of the sub-kernels, which extends the scale of problem that MKL could solve. Specially, a fast SMKL method using L infinity-norm constraint is focused, which needs no MIC optimization process. It means that the memory is hardly a limitation for MKL with the large scale problem. Experiments state that our method is effective for classification. (C) 2013 Elsevier Ltd. All rights reserved.
关键词
作者关键词:Ensemble learning; Kernel evaluation; Multiple kernel learning; Selective multiple kernel learning; Fast selective multiple kernel learning
KeyWords Plus IMENSIONALITY REDUCTION
作者信息
通讯作者地址: Feng, J (通讯作者)
[显示增强组织信息的名称] Xidian Univ, Minist Educ China, Key Lab Intelligent Percept & Image Understanding, Xian 710071, Peoples R China.
地址:
[显示增强组织信息的名称] [ 1 ] Xidian Univ, Minist Educ China, Key Lab Intelligent Percept & Image Understanding, Xian 710071, Peoples R China
[显示增强组织信息的名称] [ 2 ] Xidian Univ, Sch Comp Sci & Technol, Xian 710071, Peoples R China
电子邮件地址:taosun@mail.xidian.edu.cn; lchjiao@mail.xidian.edu.cn; f63liu@163.com; shwang@mail.xidian.edu.cn; jiefeng0109@163.com
基金资助致谢
基金资助机构 授权号
National Basic Research Program (973 Program) of China
2013CB329402
National Natural Science Foundation of China
61173092
61072106
61003198
Program for New Century Excellent Talents in University
NCET-11-0692
Fundamental Research Funds for the Central Universities
K50510020001
K50513100012
查看基金资助信息
出版商
ELSEVIER SCI LTD, THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND
类别 / 分类
研究方向:Computer Science; Engineering
Web of Science 类别:Computer Science, Artificial Intelligence; Engineering, Electrical & Electronic
文献信息
文献类型:Article
语种:English
入藏号: WOS:000321232900017
ISSN: 0031-3203
期刊信息
目录： Current Contents Connect®
Impact Factor (影响因子): Journal Citation Reports®
其他信息
IDS 号: 175LT
Web of Science 核心合集中的 "引用的参考文献": 32
Web of Science 核心合集中的 "被引频次": 2 |
|
回复此楼