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Nonlinear Regression with Logistic Product Basis Networks | IEEE Journals & Magazine | IEEE Xplore

Nonlinear Regression with Logistic Product Basis Networks


Abstract:

We introduce a novel general regression model that is based on a linear combination of a new set of non-local basis functions that forms an effective feature space. We pr...Show More

Abstract:

We introduce a novel general regression model that is based on a linear combination of a new set of non-local basis functions that forms an effective feature space. We propose a training algorithm that learns all the model parameters simultaneously and offer an initialization scheme for parameters of the basis functions. We show through several experiments that the proposed method offers better coverage for high-dimensional space compared to local Gaussian basis functions and provides competitive performance in comparison to other state-of-the-art regression methods.
Published in: IEEE Signal Processing Letters ( Volume: 22, Issue: 8, August 2015)
Page(s): 1011 - 1015
Date of Publication: 18 December 2014

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