Stretchy Polynomial Regression

TL;DR

This paper introduces a new stretchy polynomial regression method that modifies covariance computation with a power term, enhancing learning flexibility and effectiveness in compressive learning scenarios.

Contribution

It presents a novel closed-form solution for polynomial regression that incorporates a stretch factor, extending ridge regression techniques.

Findings

Effective on synthetic data

Improves compressive learning performance

Provides primal and dual closed-form solutions

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.