Distributed Bayesian Matrix Factorization with Limited Communication

Bayesian matrix factorization (BMF) is a powerful tool for producing low-rank representations of matrices and for predicting missing values and providing confidence intervals. Scaling up the posterior inference for massive-scale matrices is challenging and requires distributing both data and computa...

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Bibliographic Details

Published in:	arXiv.org
Main Authors:	Qin, Xiangju, Blomstedt, Paul, Leppäaho, Eemeli, Parviainen, Pekka, Kaski, Samuel
Format:	Paper
Language:	English
Published:	Ithaca Cornell University Library, arXiv.org 27.02.2019
Subjects:	Bayesian analysis Communication Computer simulation Confidence intervals Factorization Inference State of the art
ISSN:	2331-8422
Online Access:	Get full text
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