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FAST EXEMPLAR SELECTION ALGORITHM FOR MATRIX APPROXIMATION AND REPRESENTATION: A VARIANT oASIS ALGORITHM
Abrol, V.; Sharma, P.; Sao, A. K.
通讯作者Abrol, V.
会议名称IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
会议日期MAR 05-09, 2017
会议地点New Orleans, LA
英文摘要

Extracting inherent patterns from large data using decompositions of data matrix by a sampled subset of exemplars has found many applications in machine learning. We propose a computationally efficient algorithm for adaptive exemplar sampling, called fast exemplar selection (FES). The proposed algorithm can be seen as an efficient variant of the oASIS algorithm [1]. FES iteratively selects incoherent exemplars based on the exemplars that are already sampled. This is done by ensuring that the selected exemplars forms a positive definite Gram matrix which is checked by exploiting its Cholesky factorization in an incremental manner. FES is a deterministic rank revealing algorithm delivering a tighter matrix approximation bound. Further, FES can also be used to exactly represent low rank matrices and signals sampled from a unions of independent subspaces. Experimental results show that FES performs comparable to existing methods for tasks such as matrix approximation, feature selection, outlier detection, and elustering.


英文关键词Matrix factorization exemplar selection low rank approximation sparse coding
来源出版物2017 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP)
ISSN1520-6149
出版年2017
页码4436-4440
EISBN978-1-5090-4117-6
出版者IEEE
类型Proceedings Paper
语种英语
国家India
收录类别CPCI-S
WOS记录号WOS:000414286204120
WOS关键词SPARSE REPRESENTATION ; SUBSET-SELECTION ; FACE RECOGNITION
WOS类目Acoustics ; Engineering, Electrical & Electronic
WOS研究方向Acoustics ; Engineering
资源类型会议论文
条目标识符http://119.78.100.177/qdio/handle/2XILL650/306599
作者单位Indian Inst Technol, Sch Comp & Elect Engn, Mandi, India
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Abrol, V.,Sharma, P.,Sao, A. K.. FAST EXEMPLAR SELECTION ALGORITHM FOR MATRIX APPROXIMATION AND REPRESENTATION: A VARIANT oASIS ALGORITHM[C]:IEEE,2017:4436-4440.
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