Non-negative matrix factorization based on generalized dual divergence

05/16/2019
by   Karthik Devarajan, et al.
0

A theoretical framework for non-negative matrix factorization based on generalized dual Kullback-Leibler divergence, which includes members of the exponential family of models, is proposed. A family of algorithms is developed using this framework and its convergence proven using the Expectation-Maximization algorithm. The proposed approach generalizes some existing methods for different noise structures and contrasts with the recently proposed quasi-likelihood approach, thus providing a useful alternative for non-negative matrix factorizations. A measure to evaluate the goodness-of-fit of the resulting factorization is described. This framework can be adapted to include penalty, kernel and discriminant functions as well as tensors.

READ FULL TEXT

page 1

page 2

page 3

page 4

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
04/11/2021

A Non-Negative Matrix Factorization Game

We present a novel game-theoretic formulation of Non-Negative Matrix Fac...
research
08/06/2018

A Survey on Surrogate Approaches to Non-negative Matrix Factorization

Motivated by applications in hyperspectral imaging we investigate method...
research
01/23/2019

High order concentrated non-negative matrix-exponential functions

Highly concentrated functions play an important role in many research fi...
research
04/03/2023

Effective Feature Extraction for Intrusion Detection System using Non-negative Matrix Factorization and Univariate analysis

An Intrusion detection system (IDS) is essential for avoiding malicious ...
research
07/06/2022

A flexible model-based framework for robust estimation of mutational signatures

Somatic mutations in cancer can be viewed as a mixture distribution of s...
research
07/22/2019

Hyperlink Regression via Bregman Divergence

A collection of U (∈N) data vectors is called a U-tuple, and the assoc...

Please sign up or login with your details

Forgot password? Click here to reset