Kernel Regularized Nonlinear Dictionary Learning for Sparse Coding

doi:10.1109/TSMC.2017.2736248

	Kernel Regularized Nonlinear Dictionary Learning for Sparse Coding
	Liu, Huaping 1,2,3; Liu, He 1,2,3; Sun, Fuchun 1,2,3; Fang, Bin 1,2,3
刊名	IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
	2019-04-01
卷号	49 期号:4 页码:766-775
关键词	Kernel dictionary learning kernel sparse coding stacked auto-encoder (SAE)
ISSN号	2168-2216
DOI	10.1109/TSMC.2017.2736248
通讯作者	Liu, Huaping(hpliu@tsinghua.edu.cn)
英文摘要	For most sparse coding methods, data samples are first encoded as hand-crafted features, followed by another separate learning step that generates dictionary and sparse codes. However, such feature representations may not be optimally compatible with the learning process, thus producing suboptimal results. In this paper, we propose a new architecture for non-linear dictionary learning with sparse coding, in which samples are mapped into sparse codes via carefully designed stacked auto-encoder (SAE) networks. We jointly learn a low-dimensional embedding of the data samples by means of an SAE and a dictionary in the low-dimensional space. Further, to leverage the prior knowledge, we develop a kernel regularized nonlinear dictionary learning method, which effectively incorporates the knowledge provided by the hand-crafted kernel. An iterative algorithm is developed to jointly search the solutions of the associated optimization problem and extensive experimental validations are performed to show that the proposed kernel regularized dictionary learning method achieves satisfactory performance.
资助项目	National Natural Science Foundation of China[U1613212] ; National Natural Science Foundation of China[61673238] ; National Natural Science Foundation of China[91420302] ; National Natural Science Foundation of China[61327809] ; National High-Tech Research and Development Plan[2015AA042306] ; Beijing Municipal Science and Technology Commission[D171100005017002]
WOS关键词	REPRESENTATION ; MACHINE ; RECOGNITION ; ALGORITHMS
WOS研究方向	Automation & Control Systems ; Computer Science
语种	英语
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号	WOS:000461854900009
资助机构	National Natural Science Foundation of China ; National High-Tech Research and Development Plan ; Beijing Municipal Science and Technology Commission
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/28052]
专题	中国科学院自动化研究所
通讯作者	Liu, Huaping
作者单位	1.Tsinghua Univ, Dept Comp Sci & Technol, Beijing 100084, Peoples R China 2.Tsinghua Univ, State Key Lab Intelligent Technol & Syst, TNLIST, Beijing 100084, Peoples R China 3.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Liu, Huaping,Liu, He,Sun, Fuchun,et al. Kernel Regularized Nonlinear Dictionary Learning for Sparse Coding[J]. IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS,2019,49(4):766-775.
APA	Liu, Huaping,Liu, He,Sun, Fuchun,&Fang, Bin.(2019).Kernel Regularized Nonlinear Dictionary Learning for Sparse Coding.IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS,49(4),766-775.
MLA	Liu, Huaping,et al."Kernel Regularized Nonlinear Dictionary Learning for Sparse Coding".IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 49.4(2019):766-775.