Exploring Parallel Implementations of the Bayesian Probabilistic Matrix Factorization

Using the matrix factorization technique in machine learning is very common mainly in areas like recommender systems. Despite its high prediction accuracy and its ability to avoid over-fitting of the data, the Bayesian Probabilistic Matrix Factorization algorithm (BPMF) has not been widely used beca...

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Vydáno v:	2016 24th Euromicro International Conference on Parallel, Distributed, and Network-Based Processing (PDP) s. 119 - 126
Hlavní autoři:	Chakroun, Imen, Haber, Tom, Aa, Tom Vander, Kovac, Thomas
Médium:	Konferenční příspěvek Journal Article
Jazyk:	angličtina
Vydáno:	IEEE 01.02.2016
Témata:	Algorithms Bayes methods Bayesian analysis Collaborative filtering Conferences Electronics packaging Factorization Instruction sets Machine learning Motion pictures multicore Multicore processing PGAS Probabilistic logic Probabilistic matrix factorization algorithm Probabilistic methods Probability theory Recommender systems Sampling
ISSN:	2377-5750
On-line přístup:	Získat plný text
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