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.

New Jersey Supreme Court Requires Transparency for Facial Recognition Evidence

A state Supreme Court ruling requires prosecutors to disclose details about how facial recognition was used to identify ...
CoinDesk

Bitcoin developers want to fix the 'replace this transaction with a higher fee' button. Here's why

A helpful feature of speeding up transactions has become redundant and a "fingerprint" for tracking. Developers now want to ...

Jeff Bezos Is Funding a Wild Hunt for the Brain’s ‘Core Algorithm’

With $500 million in funding and a reported $2.5 billion valuation, Flourish wants to reinvent AI by putting real neurons ...
IEEE

A Surrogate-Assisted Differential Evolution Algorithm for High-Dimensional Expensive Optimization Problems

Abstract: The radial basis function (RBF) model and the Kriging model have been widely used in the surrogate-assisted evolutionary algorithms (SAEAs). Based on their characteristics, a global and ...
IEEE

Robot Motion Planning Based on Improved RRT Algorithm and RBF Neural Network Sliding

Abstract: Aiming to address the limitations of the traditional rapidly-exploring random tree (RRT) algorithm in robotic arm path planning, such as high randomness, slow planning speed, non-smooth ...
Visual Studio Magazine

Kernel Ridge Regression Using C#

KRR is especially useful when there is limited training data, says Dr. James McCaffrey of Microsoft Research in this full-code, step-by-step tutorial. The goal of a machine learning regression problem ...