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02795aam a2200361 i 4500 001 8A62EBAA72D911EDA0B05B7C49ECA4DB 003 SILO 005 20221203010154 008 210731s2022 nju b 001 0 eng c 010 $a 2021028029 020 $a 1800610866 020 $a 9781800610866 020 $a 1800610653 020 $a 9781800610651 035 $a (OCoLC)1264723339 040 $a LBSOR/DLC $b eng $e rda $c DLC $d YDX $d UKMGB $d OCLCF $d DLC $d OCLCO $d UIU $d SILO 042 $a pcc 050 00 $a QA402.5 C367 2022 100 1 $a Carlier, Guillaume, $e author. 245 10 $a Classical and modern optimization / $c Guillaume Carlier, UniversiteÌ Paris Dauphine, France. 264 1 $a Hackensack, New Jersey : $b World Scientific, $c [2022] 300 $a xiii, 371 pages ; $c 24 cm. 490 1 $a Advanced textbooks in mathematics 504 $a Includes bibliographical references and index. 505 0 $a Topological and functional analytic preliminaries -- Differential calculus -- Convexity -- Optimality conditions for differentiable optimization -- Problems depending on a parameter -- Convex duality and applications -- Iterative methods for convex minimization -- When optimization and data meet -- An invitation to the calculus of variations. 520 $a "The quest for the optimal is ubiquitous in nature and human behavior. The field of mathematical optimization has a long history and remains active today, particularly in the development of machine learning. Classical and Modern Optimization presents a self-contained overview of classical and modern ideas and methods in approaching optimization problems. The approach is rich and flexible enough to address smooth and non-smooth, convex and non-convex, finite or infinite-dimensional, static or dynamic situations. The first chapters of the book are devoted to the classical toolbox: topology and functional analysis, differential calculus, convex analysis and necessary conditions for differentiable constrained optimization. The remaining chapters are dedicated to more specialized topics and applications. Valuable to a wide audience, including students in mathematics, engineers, data scientists or economists, Classical and Modern Optimization contains more than 200 exercises to assist with self-study or for anyone teaching a third- or fourth-year optimization class"-- $c Provided by publisher. 650 0 $a Mathematical optimization. 776 08 $i Online version: $a Carlier, Guillaume. $t Classical and modern optimization $d Hackensack, New Jersey : World Scientific, [2022] $z 9781800610668 $w (DLC) 2021028030 830 0 $a Advanced textbooks in mathematics 941 $a 1 952 $l USUX851 $d 20240502014227.0 956 $a http://locator.silo.lib.ia.us/search.cgi?index_0=id&term_0=8A62EBAA72D911EDA0B05B7C49ECA4DB 994 $a C0 $b IWAInitiate Another SILO Locator Search