Inductive learning, including decision-tree and neural-network approaches, Bayesian methods, computational learning theory, instance-based learning, explanation-based learning, reinforcement learning, ...

This article is concerned with supplementary control of discrete-time nonlinear systems with multiple controllers in the framework of goal representation heuristic dynamic programming (GrHDP), where a ...

Course of Study The basic operations research courses offered include: linear, nonlinear, integer and dynamic programming; graph theory and network optimization; convex optimization and convex ...

We present a new class of optimization models, implicit optimization, which includes deep learning, nonlinear control, and mixed-integer programming as special cases. Implicit optimization provides a ...

This project is aimed at implementing nonlinear programming algorithms as the (un-)constrained minimization problems with the focus on their numerical expression using various programming languages.

The book contains a severe course of computation within the scope of its subject-matter, and a considerable proportion of the abundant examples are numerical in character.

During the practical course, experiments on nonlinear effects in electrical, magnetic and optical systems can be carried out, depending on your interests. From the following offer, 2 experiments with ...

IT white papers, webcasts, case studies, and much more - all free to registered TechRepublic members. Recruit the best application support engineer for installing, implementing, and maintaining ...

hpc optimization solver mpi cuda constrained-optimization nonlinear-programming-algorithms nonlinear-optimization nonlinear-programming interior-point-method rocm bfgs parallel-programming ...

We present a high-throughput, end-to-end pipeline for organic crystal structure prediction (CSP)─the problem of identifying the stable crystal structures that will form from a given molecule based ...