Microsoft issued security updates to fix over 60 CVEs in the November Patch Tuesday yesterday, including one being actively exploited in the wild. No public proof-of-concept has been released for ...

This repository provides a brief introduction and Python implementations of various regression techniques applied to noisy and nonlinear time series data. The main objective is to evaluate the ...

ABSTRACT: We introduce the Kernel-based Partial Conditional Mean Dependence, a scalar-valued measure of conditional mean dependence of Y given X , while adjusting for the nonlinear dependence on Z .

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of Nadaraya-Watson kernel regression using the C# language. NW kernel regression is simple to implement and is ...

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 income based on their age, height, high school GPA, and so on.

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 ...

I am bullish on Nvidia Corporation due to its data center and AI technology, which are major long-term growth catalysts. Despite recent stock volatility, I believe, Nvidia's innovation, especially ...

Modeling periodic phenomena with accuracy is a key aspect to detect abnormal behavior in time series for the context of Structural Health Monitoring. Modeling complex non-harmonic periodic pattern ...