Approximation and Optimization Algorithms, Complexity and Applications
tarafından
Demetriou, Ioannis C. editor.
Başlık
:
Approximation and Optimization Algorithms, Complexity and Applications
Yazar
:
Demetriou, Ioannis C. editor.
ISBN
:
9783030127671
Edisyon
:
1st ed. 2019.
Fiziksel Niteleme
:
X, 237 p. 56 illus., 27 illus. in color. online resource.
Seri
:
Springer Optimization and Its Applications, 145
İçindekiler
:
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.
Özet
:
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 highly relevant applications throughout science, engineering, technology and social sciences. Academics, researchers, data science practitioners, business analysts, social sciences investigators and graduate students will find the number of illustrations, applications, and examples provided useful. This volume is based on the conference Approximation and Optimization: Algorithms, Complexity, and Applications, which was held in the National and Kapodistrian University of Athens, Greece, June 29–30, 2017. The mix of survey and research content includes topics in approximations to discrete noisy data; binary sequences; design of networks and energy systems; fuzzy control; large scale optimization; noisy data; data-dependent approximation; networked control systems; machine learning ; optimal design; no free lunch theorem; non-linearly constrained optimization; spectroscopy.
Konu Başlığı
:
Approximation theory.
Calculus of variations.
Algorithms.
Numerical analysis.
Probabilities.
Approximations and Expansions. https://scigraph.springernature.com/ontologies/product-market-codes/M12023
Calculus of Variations and Optimal Control; Optimization. https://scigraph.springernature.com/ontologies/product-market-codes/M26016
Algorithms. https://scigraph.springernature.com/ontologies/product-market-codes/M14018
Numerical Analysis. https://scigraph.springernature.com/ontologies/product-market-codes/M14050
Probability Theory and Stochastic Processes. https://scigraph.springernature.com/ontologies/product-market-codes/M27004
Yazar Ek Girişi
:
Demetriou, Ioannis C.
Pardalos, Panos M.
Ek Kurum Yazar
:
SpringerLink (Online service)
Elektronik Erişim
:
Materyal Türü | Barkod | Yer Numarası | Durumu/İade Tarihi |
---|
Electronic Book | 429231-1001 | QA401 -425 | Springer E-Book Collection |