Sample selection for MCMC-based recommender systems

conference on recommender systems, 2013, Pages 403-406.

Cited by: 0|Bibtex|Views95|DOI:https://doi.org/10.1145/2507157.2507224
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Other Links: dblp.uni-trier.de|dl.acm.org|academic.microsoft.com

Abstract:

Bayesian Inference with Markov Chain Monte Carlo (MCMC) has been shown to provide high prediction quality in recommender systems. The advantage over learning methods such as coordinate descent/alternating least-squares (ALS) or (stochastic) gradient descent (SGD) is that MCMC takes uncertainty into account and moreover MCMC can easily int...More

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