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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Vydané v:	arXiv.org
Hlavní autori:	Qin, Xiangju, Blomstedt, Paul, Leppäaho, Eemeli, Parviainen, Pekka, Kaski, Samuel
Médium:	Paper
Jazyk:	English
Vydavateľské údaje:	Ithaca Cornell University Library, arXiv.org 27.02.2019
Predmet:	Bayesian analysis Communication Computer simulation Confidence intervals Factorization Inference State of the art
ISSN:	2331-8422
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