Multi-View Intact Space Learning

doi:10.1109/TPAMI.2015.2417578

CORC > 北京大学 > 信息科学技术学院

	Multi-View Intact Space Learning
	Xu, Chang ; Tao, Dacheng ; Xu, Chao
刊名	IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
	2015
关键词	Multi-view learning robust algorithms IMAGE CLASSIFICATION BREAKDOWN POINTS COVERING NUMBER REGULARIZATION ESTIMATORS
DOI	10.1109/TPAMI.2015.2417578
英文摘要	It is practical to assume that an individual view is unlikely to be sufficient for effective multi-view learning. Therefore, integration of multi-view information is both valuable and necessary. In this paper, we propose the Multi-view Intact Space Learning (MISL) algorithm, which integrates the encoded complementary information in multiple views to discover a latent intact representation of the data. Even though each view on its own is insufficient, we show theoretically that by combing multiple views we can obtain abundant information for latent intact space learning. Employing the Cauchy loss (a technique used in statistical learning) as the error measurement strengthens robustness to outliers. We propose a new definition of multi-view stability and then derive the generalization error bound based on multi-view stability and Rademacher complexity, and show that the complementarity between multiple views is beneficial for the stability and generalization. MISL is efficiently optimized using a novel Iteratively Reweight Residuals (IRR) technique, whose convergence is theoretically analyzed. Experiments on synthetic data and real-world datasets demonstrate that MISL is an effective and promising algorithm for practical applications.; Australian Research Council [FT-130101457, DP-140102164]; NSFC [61375026, 2015BAF15B00]; JCYJ [20120614152136201]; SCI(E); EI; ARTICLE; xuchang@pku.edu.cn; dacheng.tao@uts.edu.au; xuchao@cis.pku.edu.cn; 12; 2531-2544; 37
语种	英语
内容类型	期刊论文
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/435664]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Xu, Chang,Tao, Dacheng,Xu, Chao. Multi-View Intact Space Learning[J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE,2015.
APA	Xu, Chang,Tao, Dacheng,&Xu, Chao.(2015).Multi-View Intact Space Learning.IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE.
MLA	Xu, Chang,et al."Multi-View Intact Space Learning".IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2015).