With the advent of massively parallel computing coprocessors, numerical optimization for deep-learning disciplines is now possible. Complex real-time pattern recognition, for example, that can be used ...

We propose a new trust region algorithm for nonlinear constrained optimization problems. In each iteration of our algorithm, the trial step is computed by minimizing a quadratic approximation to the ...

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 ...

The course is designed to provide engineering students a view of optimization as a tool for engineering decision making. Students will be given a fundamental introduction to the optimization ...

Today the Numerical Algorithms Group announces the latest version of its flagship software, the NAG Library, Mark 26. In this release, NAG has introduced an Optimization Modeling Suite for linear and ...

We will be concerned with the mathematical modeling, numerical simulation, and shape optimization of microfluidic biochips that are used for various biomedical applications. A particular feature is ...

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 ...

Students will learn about the most common numerical optimization algorithms for solving smooth unconstrained and constrained optimization problems. They will understand the theoretical foundation and ...