Approximation and Optimization: Algorithms, Complexity and Applications - Softcover

Buch 135 von 176: Springer Optimization and Its Applications
 
9783030127688: Approximation and Optimization: Algorithms, Complexity and Applications

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Inhaltsangabe

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.

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9783030127664: Approximation and Optimization: Algorithms, Complexity and Applications (Springer Optimization and Its Applications, 145, Band 145)

Vorgestellte Ausgabe

ISBN 10:  3030127664 ISBN 13:  9783030127664
Verlag: Springer, 2019
Hardcover