Math @ Duke

Publications [#319367] of Henry Pfister
Papers Published
 Kim, BH; Yedla, A; Pfister, HD, IMP: A messagepassing algorithm for matrix completion,
6th International Symposium on Turbo Codes and Iterative Information Processing, ISTC 2010
(November, 2010),
pp. 462466, ISBN 9781424467457 [doi]
(last updated on 2018/10/20)
Abstract: A new messagepassing (MP) method is considered for the matrix completion problem associated with recommender systems. We attack the problem using a (generative) factor graph model that is related to a probabilistic lowrank matrix factorization. Based on the model, we propose a new algorithm, termed IMP, for the recovery of a data matrix from incomplete observations. The algorithm is based on a clustering followed by inference via MP (IMP). The algorithm is compared with a number of other matrix completion algorithms on real collaborative filtering (e.g., Netflix) data matrices. Our results show that, while many methods perform similarly with a large number of revealed entries, the IMP algorithm outperforms all others when the fraction of observed entries is small. This is helpful because it reduces the wellknown coldstart problem associated with collaborative filtering (CF) systems in practice. © 2010 IEEE.


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