Dimensionality reduction techniques like PCA work wonderfully when datasets are linearly separable—but they break down the moment nonlinear patterns appear. That’s exactly what happens with datasets ...

Abstract: This paper proposes a Gaussian-Cauchy mixture maximum correntropy criterion Kalman filter algorithm (GCM_MCCKF) for robust state estimation in linear systems under non-Gaussian noise, ...

Abstract: Topology optimizations involving evolutionary algorithms are promising approaches to solve practical engineering design problems, since their use of derivation-free algorithms makes them ...

We have 7 agents, and each agent has approximately 30+ functions. These functions are being passed as arguments when making the invoke method call. This setup was working fine until last week. However ...

If you’re stuck on today’s Wordle answer, we’re here to help—but beware of spoilers for Wordle #1527 ahead. Let's start with a few hints. 🎬 SIGN UP for Parade's Daily newsletter to get the latest pop ...

Today, you’re the calm in the chaos and the one making elegance look like a power move. Libra, August 9 puts you in alignment with yourself, your goals, and your glow-up. Venus is smoothing your edges ...

Dr. James McCaffrey presents a complete end-to-end demonstration of the kernel ridge regression technique to predict a single numeric value. The demo uses stochastic gradient descent, one of two ...

Purpose: This study introduces two-dimensional (2D) Kernel Density Estimation (KDE) plots as a novel tool for visualising Training Intensity Distribution (TID) in biathlon. The goal was to assess how ...

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 ...

At the heart of Microsoft’s AI application development strategy is Semantic Kernel, an open source set of tools for managing and orchestrating AI prompts. Since its launch as a way to simplify ...