An Oracle Inequality for Quasi-Bayesian Non-Negative Matrix Factorization

Published 6 Jan 2016 in stat.ML, math.ST, and stat.TH | (1601.01345v4)

Abstract: The aim of this paper is to provide some theoretical understanding of quasi-Bayesian aggregation methods non-negative matrix factorization. We derive an oracle inequality for an aggregated estimator. This result holds for a very general class of prior distributions and shows how the prior affects the rate of convergence.

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