Scalable Online Convolutional Sparse Coding
Wang, Yaqing; Yao, Quanming; Kwok, James T.; Ni, Lionel M.
AbstractConvolutional sparse coding (CSC) improves sparse coding by learning a shift-invariant dictionary from the data. However, most existing CSC algorithms operate in the batch mode and are computationally expensive. In this paper, we alleviate this problem by online learning. The key is a reformulation of the CSC objective so that convolution can be handled easily in the frequency domain, and much smaller history matrices are needed. To solve the resultant optimization problem, we use the alternating direction method of multipliers (ADMMs), and its subproblems have efficient closed-form solutions. Theoretical analysis shows that the learned dictionary converges to a stationary point of the optimization problem. Extensive experiments are performed on both the standard CSC benchmark data sets and much larger data sets such as the ImageNet. Results show that the proposed algorithm outperforms the state-of-the-art batch and online CSC methods. It is more scalable, has faster convergence, and better reconstruction performance.
KeywordOnline learning convolutional sparse coding dictionary learning
URLView the original
Indexed BySCIE
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS IDWOS:000437412500004
The Source to ArticleWOS
Fulltext Access
Citation statistics
Cited Times [WOS]:10   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionUniversity of Macau
Recommended Citation
GB/T 7714
Wang, Yaqing,Yao, Quanming,Kwok, James T.,et al. Scalable Online Convolutional Sparse Coding[J]. IEEE TRANSACTIONS ON IMAGE PROCESSING,2018,27(10):4850-4859.
APA Wang, Yaqing,Yao, Quanming,Kwok, James T.,&Ni, Lionel M..(2018).Scalable Online Convolutional Sparse Coding.IEEE TRANSACTIONS ON IMAGE PROCESSING,27(10),4850-4859.
MLA Wang, Yaqing,et al."Scalable Online Convolutional Sparse Coding".IEEE TRANSACTIONS ON IMAGE PROCESSING 27.10(2018):4850-4859.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Wang, Yaqing]'s Articles
[Yao, Quanming]'s Articles
[Kwok, James T.]'s Articles
Baidu academic
Similar articles in Baidu academic
[Wang, Yaqing]'s Articles
[Yao, Quanming]'s Articles
[Kwok, James T.]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Wang, Yaqing]'s Articles
[Yao, Quanming]'s Articles
[Kwok, James T.]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.