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.

Students have the opportunity to develop their knowledge, understanding and skills in mathematics and working mathematically. They develop ways of thinking and use mathematics as a powerful way of ...

Pull request by Ben Goodrich for fixing the issue with clang4. New version on it's way to CRAN.

This repository contains an efficient implementation of Kolmogorov-Arnold Network (KAN). The original implementation of KAN is available here. The problem is in the sparsification which is claimed to ...

Abstract: In this paper, an importance sampling maximum likelihood (ISML) estimator for direction-of-arrival (DOA) of incoherently distributed (ID) sources is proposed. Starting from the maximum ...

8.3 Examples of Finite-State DTMCs 8.3.1 Repair Facility Problem 8.3.2 Umbrella Problem 8.3.3 Program Analysis Problem 8.4 Powers of P: n-Step Transition Probabilities 8.5 Stationary Equations 8.6 The ...

We propose a strategy for building prior distributions that stabilize the estimation of complex “working models” when sample sizes are too small for standard statistical analysis. The stabilization is ...

A new algorithm is suggested based on the central limit theorem for generating pseudo-random numbers with a specified normal or Gaussian probability density function. The suggested algorithm is very ...

This paper explores the mathematics behind optimal portfolio construction when relative utility and risk are considered together in a general sense. I derive the portfolio optimization problems when ...

Despite thousands of articles addressing heart rate variability (HRV) in healthy subjects and patients with various clinical conditions published during the last decades, our understanding of the ...