This Article Is Based On The Research 'POLYLOSS: A POLYNOMIAL EXPANSION PERSPECTIVE OF CLASSIFICATION LOSS FUNCTIONS'. All Credit For This Research Goes To The Researchers Of This Paper 👏👏👏 Please ...

Bernstein polynomial estimation provides a robust nonparametric technique for approximating both density and distribution functions. Based on the properties of Bernstein polynomials, which uniformly ...

Algorithmic complexity, a cornerstone of theoretical computer science, examines the intrinsic resource requirements of computational problems and the limits of what can be efficiently computed. Within ...

Polynomials and power functions are the foundation for modelling non-linear relationships. Polynomial functions such as quadratic, cubic and quartic model variables raised to exponents of different ...

This repository contains Python code for performing polynomial regression using gradient descent, implemented with PyTorch, as required for Assignment 1. The code provides functions for polynomial ...

In this paper, an algebraic method which is based on the groebner bases theory is proposed to solve the polynomial functions conditional extreme. Firstly, we describe how to solve conditional extreme ...

The original code is as old as from 1995 and was written by Gerhard Krucker (see http://www.krucker.ch/skripten-uebungen/IAMSkript/IAMKap3.pdf#page=14). So all ...

Abstract: We examine linear programming (LP) based relaxations for synthesizing polynomial Lyapunov functions to prove the stability of polynomial ordinary differential equations (ODEs). Our approach ...