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

arXiv: https://arxiv.org/abs/1601.01345 · HTML: https://mlsanity.com/paper/1601.01345/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 Jan 2016.

## Built on by (most cited first, 1 of 1)

- [PAC-Bayes-Chernoff bounds for unbounded losses](https://mlsanity.com/paper/2401.01148/) (2024)

## Abstract (arXiv)

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.