A Non-Negative Matrix Factorization Game

04/11/2021
by   Satpreet H. Singh, et al.
0

We present a novel game-theoretic formulation of Non-Negative Matrix Factorization (NNMF), a popular data-analysis method with many scientific and engineering applications. The game-theoretic formulation is shown to have favorable scaling and parallelization properties, while retaining reconstruction and convergence performance comparable to the traditional Multiplicative Updates algorithm.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
10/19/2022

Binary Orthogonal Non-negative Matrix Factorization

We propose a method for computing binary orthogonal non-negative matrix ...
research
08/06/2018

A Survey on Surrogate Approaches to Non-negative Matrix Factorization

Motivated by applications in hyperspectral imaging we investigate method...
research
05/16/2019

Non-negative matrix factorization based on generalized dual divergence

A theoretical framework for non-negative matrix factorization based on g...
research
01/06/2016

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

The aim of this paper is to provide some theoretical understanding of Ba...
research
09/19/2016

Stochastic Matrix Factorization

This paper considers a restriction to non-negative matrix factorization ...
research
11/11/2016

Recovery Guarantee of Non-negative Matrix Factorization via Alternating Updates

Non-negative matrix factorization is a popular tool for decomposing data...
research
06/13/2017

Provable Alternating Gradient Descent for Non-negative Matrix Factorization with Strong Correlations

Non-negative matrix factorization is a basic tool for decomposing data i...

Please sign up or login with your details

Forgot password? Click here to reset