Quadratic regression is a classical machine learning technique to predict a single numeric value. Quadratic regression is an extension of basic linear regression. Quadratic regression can deal with ...

Here’s a quick library to write your GPU-based operators and execute them in your Nvidia, AMD, Intel or whatever, along with my new VisualDML tool to design your operators visually. This is a follow ...

Abstract: We study the convergence of minimum error entropy (MEE) algorithms when they are implemented by gradient descent. This method has been used in practical ...

The goal of a machine learning regression problem is to predict a single numeric value. For example, you might want to predict a person's bank savings account balance based on their age, years of ...

Struggling to understand how logistic regression works with gradient descent? This video breaks down the full mathematical derivation step-by-step, so you can truly grasp this core machine learning ...

Attention-based architectures are a powerful force in modern AI. In particular, the emergence of in-context learning abilities enables task generalization far beyond the original next-token prediction ...

ABSTRACT: This paper proposes a universal framework for constructing bivariate stochastic processes, going beyond the limitations of copulas and offering a potentially simpler alternative. The ...

This project explores linear regression using both the least squares method and gradient descent. It implements the matrix form of linear regression and applies it to a real-world dataset. The ...