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| 003 | OSt | ||
| 005 | 20240502115724.0 | ||
| 006 | m |o d | | ||
| 007 | cr_||||||||||| | ||
| 008 | 210731s2022 nju ob 001 0 eng | ||
| 010 | _a 2021028030 | ||
| 020 | _a9781944660529 (Pbk) | ||
| 020 |
_z9781800610651 _q(hardcover) |
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| 020 |
_z9781800610866 _q(paperback) |
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| 040 |
_aDLC _beng _erda _cIISERB _dDLC |
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| 042 | _apcc | ||
| 050 | 0 | 0 | _aQA402.5 |
| 082 | 0 | 0 |
_a519.6 C194C _223 |
| 100 | 1 |
_aCarlier, Guillaume. _930181 |
|
| 245 | 1 | 0 |
_aClassical and modern optimization _cGuillaume Carlier, Université Paris Dauphine, France. |
| 260 |
_aSingapore: _bWorld Scientific, _c2024. |
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| 263 | _a2110 | ||
| 300 | _axiii, 371p. | ||
| 490 | 0 |
_aAdvanced textbooks in mathematics, _x2059-769X |
|
| 504 | _aIncludes bibliographical references and index. | ||
| 505 | 0 | _aTopological 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"-- | ||
| 650 | 0 |
_aMathematical optimization. _930182 |
|
| 776 | 0 | 8 |
_iPrint version: _aCarlier, Guillaume. _tClassical and modern optimization _dHackensack, New Jersey : World Scientific, [2022] _z9781800610651 _w(DLC) 2021028029 |
| 906 |
_a7 _brip _corignew _d1 _eecip _f20 _gy-gencatlg |
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