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.

Tired of Google AI? Green search engines to try instead, how they work

Here’s a quick introduction to the two most popular "green" search engines, how they help the environment and how to use them ...
GitHub

ut-beg-texnet/NonLinLoc

The NonLinLoc (Non-Linear Location) package is a set of programs for velocity model construction, travel-time calculation and probabilistic, non-linear, global-search earthquake location in 3D ...
Scientific Research Publishing

Reproducing Kernel Hilbert Space Technique for Fourth-Order Singular Boundary Value Problems ()

Reproducing kernel Hilbert space method is utilized in this paper as an efficient approach to solve singular fourth order ...
GitHub

functions-bindings-timer.md

This article explains how to work with timer triggers in Azure Functions. A timer trigger lets you run a function on a schedule. [!INCLUDE [intro](../../includes ...
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, ...
IEEE

Minimal Binary Linear Codes From Vectorial Boolean Functions

Abstract: Recently, much progress has been made to construct minimal linear codes due to their preference in secret sharing schemes and secure two-party computation. In this paper, we put forward a ...