Conjugate gradient methods form a class of iterative algorithms that are highly effective for solving large‐scale unconstrained optimisation problems. They achieve efficiency by constructing search ...

In this paper the generalized Newton's method for LC¹ unconstrained optimization is investigated. This method is an extension of Newton's method for the smooth optimization. Some basic concepts are ...

To fulfill the 2 Core Courses, take two Core Courses from two different Core Areas. CSE Core Courses are classified into six areas: Introduction to CSE, Computational Mathematics, High Performance ...

This course offers an introduction to mathematical nonlinear optimization with applications in data science. The theoretical foundation and the fundamental algorithms for nonlinear optimization are ...

A thorough understanding of Linear Algebra and Vector Calculus, and strong familiarity with the Python programming language (e.g., basic data manipulation libraries, how to construct functions and ...