NDLI: Variational Bayesian View of Weighted Trace Norm Regularization for Matrix Factorization

Content Provider	IEEE Xplore Digital Library
Author	Yong-Deok Kim Seungjin Choi
Copyright Year	1994
Abstract	Matrix factorization with trace norm regularization is a popular approach to matrix completion and collaborative filtering. When entries of the matrix are sampled non-uniformly (which is the case for collaborative prediction), a properly weighted correction to the trace norm regularization is known to improve the performance dramatically. While the weighted trace norm regularization has been rigorously studied, its generative counterpart is not known yet. In this paper we show that the weighted trace norm regularization emerges from variational Bayesian matrix factorization where variational distributions over factor matrices are restricted to be isotropic Gaussians with the common variance. We show that variational variance corresponds to the regularization parameter. Thus, the regularization parameter can be automatically learned by variational inference rather than cross-validation. Experiments on MovieLens and Netflix datasets confirm the variational Bayesian perspective of the weighted trace norm regularization, demonstrating that variational parameter learned by variational inference agrees with the value of the regularization parameter found by cross-validation.
Sponsorship	IEEE Signal Processing Society
Starting Page	261
Ending Page	264
Page Count	4
File Size	1089849
File Format	PDF
ISSN	10709908
Volume Number	20
Issue Number	3
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Bayesian methods Matrix decomposition Collaboration Covariance matrix Educational institutions Materials Computer science variational Bayesian inference Collaborative prediction matrix completion matrix factorization trace norm regularization
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Signal Processing Electrical and Electronic Engineering

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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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