2015 LargeScaleDistributedBayesianMa

• (Ahn et al., 2015) ⇒ Sungjin Ahn, Anoop Korattikara, Nathan Liu, Suju Rajan, and Max Welling. (2015). “Large-Scale Distributed Bayesian Matrix Factorization Using Stochastic Gradient MCMC.” In: Proceedings of the 21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2015). ISBN:978-1-4503-3664-2 doi:10.1145/2783258.2783373

Subject Headings:

Cited By

• http://scholar.google.com/scholar?q=%222015%22+Large-Scale+Distributed+Bayesian+Matrix+Factorization+Using+Stochastic+Gradient+MCMC
• http://dl.acm.org/citation.cfm?id=2783258.2783373&preflayout=flat#citedby

Quotes

Author Keywords

• Algorithm design and analysis; bayesian inference; distributed; large-scale; matrix factorization; mcmc; parallel and vector implementations; stochastic gradient

Abstract

Despite having various attractive qualities such as high prediction accuracy and the ability to quantify uncertainty and avoid over-fitting, Bayesian Matrix Factorization has not been widely adopted because of the prohibitive cost of inference. In this paper, we propose a scalable distributed Bayesian matrix factorization algorithm using stochastic gradient MCMC. Our algorithm, based on Distributed Stochastic Gradient Langevin Dynamics, can not only match the prediction accuracy of standard MCMC methods like Gibbs sampling, but at the same time is as fast and simple as stochastic gradient descent. In our experiments, we show that our algorithm can achieve the same level of prediction accuracy as Gibbs sampling an order of magnitude faster. We also show that our method reduces the prediction error as fast as distributed stochastic gradient descent, achieving a 4.1% improvement in RMSE for the Netflix dataset and an 1.8% for the Yahoo music dataset.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2015 LargeScaleDistributedBayesianMa	Max Welling Sungjin Ahn Anoop Korattikara Nathan Liu Suju Rajan			Large-Scale Distributed Bayesian Matrix Factorization Using Stochastic Gradient MCMC				10.1145/2783258.2783373		2015