Approximation and Optimization Algorithms, Complexity and Applications /

• Corporate Author: SpringerLink (Online service)
• Other Authors: Demetriou, Ioannis C. (Editor, http://id.loc.gov/vocabulary/relators/edt), Pardalos, Panos M. (Editor, http://id.loc.gov/vocabulary/relators/edt)
• Format: Electronic eBook
• Language: English
• Published: Cham : Springer International Publishing : Imprint: Springer, 2019.
• Edition: 1st ed. 2019.
• Series: Springer Optimization and Its Applications, 145
• Subjects: Approximation theory.; Calculus of variations.; Algorithms.; Numerical analysis.; Probabilities.; Approximations and Expansions.; Calculus of Variations and Optimal Control; Optimization.; Numerical Analysis.; Probability Theory and Stochastic Processes.

This book focuses on the development of approximation-related algorithms and their relevant applications. Individual contributions are written by leading experts and reflect emerging directions and connections in data approximation and optimization. Chapters discuss state of the art topics with high...

Table of Contents:

• Introduction
• Evaluation Complexity Bounds for Smooth Constrained Nonlinear Optimization using Scaled KKT Conditions and High-order Models
• Data-Dependent Approximation in Social Computing
• Multi-Objective Evolutionary Optimization Algorithms for Machine Learning: a Recent Survey
• No Free Lunch Theorem, a Review
• Piecewise Convex-Concave Approximation in the Minimax Norm
• A Decomposition Theorem for the Least Squares Piecewise Monotonic Data Approximation Problem
• Recent Progress in Optimization of Multiband Electrical Filters
• Impact of Error in Parameter Estimations on Large Scale Portfolio Optimization
• Optimal Design of Smart Composites
• Tax Evasion as an Optimal Solution to a Partially Observable Markov Decision Process.