東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Approximation and optimization = alg...

Demetriou, Ioannis C.

FindBook

Google Book

Amazon

博客來

Approximation and optimization = algorithms, complexity and applications /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Approximation and optimization/ edited by Ioannis C. Demetriou, Panos M. Pardalos.
其他題名:	algorithms, complexity and applications /
其他作者:	Demetriou, Ioannis C.
出版者:	Cham :Springer International Publishing : : 2019.,
面頁冊數:	x, 237 p. :ill., digital ;24 cm.
內容註:	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.
Contained By:	Springer eBooks
標題:	Approximation theory - Congresses. -
電子資源:	https://doi.org/10.1007/978-3-030-12767-1
ISBN:	9783030127671

Approximation and optimization = algorithms, complexity and applications /
Approximation and optimizationalgorithms, complexity and applications /[electronic resource] :edited by Ioannis C. Demetriou, Panos M. Pardalos. - Cham :Springer International Publishing :2019. - x, 237 p. :ill., digital ;24 cm. - Springer optimization and its applications,v.1451931-6828 ;. - Springer optimization and its applications ;v.145..

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.

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.

ISBN: 9783030127671

Standard No.: 10.1007/978-3-030-12767-1doiSubjects--Topical Terms:

659277
Approximation theory
--Congresses.

LC Class. No.: QA221 / .A677 2019

Dewey Class. No.: 511.4

Approximation and optimization = algorithms, complexity and applications /
LDR:03032nmm a2200337 a 4500 001 2191537
003 DE-He213
005 20191031172656.0
006 m d
007 cr nn 008maaau
008 200504s2019 gw s 0 eng d
020 $a 9783030127671 $q (electronic bk.)
020 $a 9783030127664 $q (paper)
024 7 $a 10.1007/978-3-030-12767-1 $2 doi
035 $a 978-3-030-12767-1
040 $a GP $c GP
041 0 $a eng
050 4 $a QA221 $b .A677 2019
072 7 $a PBKJ $2 bicssc
072 7 $a MAT034000 $2 bisacsh
072 7 $a PBKJ $2 thema
082 0 4 $a 511.4 $2 23
090 $a QA221 $b .A652 2019
245 0 0 $a Approximation and optimization $h [electronic resource] : $b algorithms, complexity and applications / $c edited by Ioannis C. Demetriou, Panos M. Pardalos.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2019.
300 $a x, 237 p. : $b ill., digital ; $c 24 cm.
490 1 $a Springer optimization and its applications, $x 1931-6828 ; $v v.145
505 0 $a 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.
520 $a 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.
650 0 $a Approximation theory $x Congresses. $3 659277
650 0 $a Mathematical optimization $x Congresses. $3 647613
650 1 4 $a Approximations and Expansions. $3 897324
650 2 4 $a Calculus of Variations and Optimal Control; Optimization. $3 898674
650 2 4 $a Algorithms. $3 536374
650 2 4 $a Numerical Analysis. $3 892626
650 2 4 $a Probability Theory and Stochastic Processes. $3 891080
700 1 $a Demetriou, Ioannis C. $3 3411027
700 1 $a Pardalos, Panos M. $3 670825
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
830 0 $a Springer optimization and its applications ; $v v.145. $3 3411028
856 4 0 $u https://doi.org/10.1007/978-3-030-12767-1
950 $a Mathematics and Statistics (Springer-11649)