Jae-Ho Choi, Kwang-Yong Kim, Duck-Soo Chung, Numerical Optimization for Design of an Automotive Cooling Fan, SAE Transactions, Vol. 106, Section 6: JOURNAL OF PASSENGER CARS: Part 1 (1997), pp.

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 ...

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 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 ...

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 ...

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 ...

Particle swarm optimization isn't usually seen as the first-choice technique for training a neural network but, as James McCaffrey demonstrates, it's a useful alternative.