This important study, which tackles the challenge of analyzing genome integrity and instability in unicellular pathogens by introducing a novel single-cell genomics approach, presents compelling ...

Learn what is Linear Regression Cost Function in Machine Learning and how it is used. Linear Regression Cost function in Machine Learning is "error" representation between actual value and model ...

This repository contains a complete collection of implementations for various Numerical Methods used in computational mathematics. The project covers a wide range of topics including linear and ...

Multi-step temporal-difference (TD) learning, where the update targets contain information from multiple time steps ahead, is one of the most popular forms of TD learning for linear function ...

This paper introduces the Julia programming language as a dynamic, cost-effective, and efficient framework for implementing structural analysis packages. To achieve this, the finite element method was ...

Abstract: The variants of constructing the circulant matrices of any p-ary linear recurrent sequence (LRS) of maximal period on the basis of automorphic multiplicative groups of the extended Galois ...

In this study, we propose an exact method for optimizing a linear function over the efficient set of a multi-objective transportation problem (MOTP). This type of problem arises when a decision maker ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. In this work, we describe the development of a new algorithm for the computation of ...