Visual Studio Magazine

Support Vector Regression with SGD Training Using C#

Support vector regression can predict numeric values effectively, and this article shows how to implement and train a kernel SVR model in C# using stochastic sub-gradient descent.
IEEE

Fuzzy Nonlinear Regression Modeling With Radial Basis Function Networks

Abstract: In this article, we extend the popular supervised learning technique radial basis function network (RBFN) for regression modeling based on fuzzy responses ...
GitHub

SinoBF-1: Satellite Mapping of Every Building’s Function in Urban China Reveals Deep Built Environment Disparities

In this study, we present a building-level functional map of China, covering 110 million individual buildings across 109 cities using 69 terabytes of multi-modal satellite imagery. The national-scale ...
IEEE

Gaussian-Cauchy Mixture Kernel Function Based Maximum Correntropy Criterion Kalman Filter for Linear Non-Gaussian Systems

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, ...