Stretchy Polynomial Regression
Machine Learning
2014-08-26 v1 Machine Learning
Abstract
This article proposes a novel solution for stretchy polynomial regression learning. The solution comes in primal and dual closed-forms similar to that of ridge regression. Essentially, the proposed solution stretches the covariance computation via a power term thereby compresses or amplifies the estimation. Our experiments on both synthetic data and real-world data show effectiveness of the proposed method for compressive learning.
Keywords
Cite
@article{arxiv.1408.5449,
title = {Stretchy Polynomial Regression},
author = {Kar-Ann Toh},
journal= {arXiv preprint arXiv:1408.5449},
year = {2014}
}
Comments
Article created in April and revised in August 2014. Submitted to ICARCV 2014