In this paper we test different conjugate gradient (CG) methods for solving largescale unconstrained optimization problems. The methods are divided in two groups: the first group includes five basic ...

This course discusses basic convex analysis (convex sets, functions, and optimization problems), optimization theory (linear, quadratic, semidefinite, and geometric programming; optimality conditions ...

This paper provides a review and commentary on the past, present, and future of numerical optimization algorithms in the context of machine learning applications. Through case studies on text ...

The objective of the 3D-SCALO problem is to assign the given components to optimal mounting surfaces and position them at the best locations, while satisfying the requirements for (1) heat dissipation ...

This course introduces high-performance computing (“HPC”) systems, software, and methods used to solve large-scale problems in science and engineering. It will focus on the intersection of two ...

In the fast-evolving field of electronic systems design, engineers are under increasing pressure to deliver innovative, high-performance products within ever ...

This study introduces a reliability assessment methodology for high grade steel large diameter natural gas pipelines, which systematically accounts for the correlations and nonlinear coupling effects ...

In this talk today we will discuss how to improve the resolution of your current CE-SDS methods. We will cover how CE-SDS works and what types of derivatisation for laser induced fluorescence (LIF) ...