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Massoud Babaie-Zadeh

4 accepted papers

2020

A Novel Pruning Approach for Bagging Ensemble Regression Based on Sparse Representation

ICASSP 2020accepted

This work aims to propose an approach for pruning a bagging ensemble regression (BER) model based on sparse representation, which we call sparse representation pruning (SRP). Firstly, a BER model with a specific number of subensembles should be trained. Then, the BER model is pruned by our sparse re…

Cited by 0SourceScholar
2020

Low Mutual and Average Coherence Dictionary Learning Using Convex Approximation

ICASSP 2020accepted

In dictionary learning, a desirable property for the dictionary is to be of low mutual and average coherences. Mutual coherence is defined as the maximum absolute correlation between distinct atoms of the dictionary, whereas the average coherence is a measure of the average correlations. In this pap…

Cited by 3SourceScholar
2017

Blind compensation of polynomial mixtures of Gaussian signals with application in nonlinear blind source separation

ICASSP 2017accepted

In this paper, a proof is provided to show that Gaussian signals will lose their Gaussianity if they are passed through a polynomial of an order greater than 1. This can help in blind compensation of polynomial nonlinearities on Gaussian sources by forcing the output to follow a Gaussian distributio…

Cited by 0SourceScholar
2015

Image interpolation using Gaussian Mixture Models with spatially constrained patch clustering

ICASSP 2015accepted

In this paper we address the problem of image interpolation using Gaussian Mixture Models (GMM) as a prior. Previous methods of image restoration with GMM have not considered spatial (geometric) distance between patches in clustering, failing to fully exploit the coherency of nearby patches. The GMM…

Cited by 0SourceScholar