Dynamic matrix factorization: A state space approach

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

Volumn , Issue , 2012, Pages 1897-1900

  Sun, John Z ^a,b   Varshney, Kush R ^b   Subbian, Karthik ^b  

^a MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^b IBM T J WATSON RESEARCH CENTER   (United States)

Author keywords

collaborative filtering; expectation maximization; Kalman filtering; learning; recommendation systems

Indexed keywords

BAYESIAN MODEL; COLLABORATIVE FILTERING; DYNAMICAL STATE; EXPECTATION MAXIMIZATION; GAUSSIANS; KALMAN-FILTERING; LEARNING; MATRIX FACTORIZATIONS; MEASUREMENT NOISE; STATE SPACE APPROACH; STATE TRACKING; TIME-DEPENDENT STRUCTURE;

BAYESIAN NETWORKS; KALMAN FILTERS; MAXIMUM PRINCIPLE; SIGNAL PROCESSING; STATE SPACE METHODS;

RECOMMENDER SYSTEMS;

EID: 84867610178     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICASSP.2012.6288274     Document Type: Conference Paper

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