Multi-View Learning With Incomplete Views

doi:10.1109/TIP.2015.2490539

CORC > 北京大学 > 信息科学技术学院

	Multi-View Learning With Incomplete Views
	Xu, Chang ; Tao, Dacheng ; Xu, Chao
刊名	IEEE TRANSACTIONS ON IMAGE PROCESSING
	2015
关键词	Multi-view learning incomplete views REPRESENTATION RECOGNITION HISTOGRAM MATRIX IMAGES
DOI	10.1109/TIP.2015.2490539
英文摘要	One underlying assumption of the conventional multi-view learning algorithms is that all examples can be successfully observed on all the views. However, due to various failures or faults in collecting and pre-processing the data on different views, we are more likely to be faced with an incomplete-view setting, where an example could be missing its representation on one view (i.e., missing view) or could be only partially observed on that view (i.e., missing variables). Low-rank assumption used to be effective for recovering the random missing variables of features, but it is disabled by concentrated missing variables and has no effect on missing views. This paper suggests that the key to handling the incomplete-view problem is to exploit the connections between multiple views, enabling the incomplete views to be restored with the help of the complete views. We propose an effective algorithm to accomplish multi-view learning with incomplete views by assuming that different views are generated from a shared subspace. To handle the large-scale problem and obtain fast convergence, we investigate a successive over-relaxation method to solve the objective function. Convergence of the optimization technique is theoretically analyzed. The experimental results on toy data and real-world data sets suggest that studying the incomplete-view problem in multi-view learning is significant and that the proposed algorithm can effectively handle the incomplete views in different applications.; National Basic Research Program, China [2011CB302400]; National Key Technology Research and Development Program [2015BAF15B00]; Shenzhen City Techonology Basic Research Program [JCYJ 20120614152136201]; National Natural Science Foundation of China [NSFC 61375026]; Australian Research Council [DP-140102164, FT-130101457, LP-140100569]; SCI(E); EI; ARTICLE; xuchang@pku.edu.cn; dacheng.tao@uts.edu.au; xuchao@cis.pku.edu.cn; 12; 5812-5825; 24
语种	英语
内容类型	期刊论文
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/435659]
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 Learning With Incomplete Views[J]. IEEE TRANSACTIONS ON IMAGE PROCESSING,2015.
APA	Xu, Chang,Tao, Dacheng,&Xu, Chao.(2015).Multi-View Learning With Incomplete Views.IEEE TRANSACTIONS ON IMAGE PROCESSING.
MLA	Xu, Chang,et al."Multi-View Learning With Incomplete Views".IEEE TRANSACTIONS ON IMAGE PROCESSING (2015).