- We will send in 10–14 business days.
/images/books/12315513/9781800610866.jpg)
- Author: Guillaume Carlier
- Publisher: World Scientific Publishing Europe Ltd
- ISBN-10: 1800610866
- ISBN-13: 9781800610866
- Format: 15.2 x 22.9 x 2 cm, minkšti viršeliai
- Language: English
- SAVE -10% with code: EXTRA
Reviews
Description
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.
EXTRA 10 % discount with code: EXTRA
The promotion ends in 21d.23:21:35
The discount code is valid when purchasing from 10 €. Discounts do not stack.
- Author: Guillaume Carlier
- Publisher: World Scientific Publishing Europe Ltd
- ISBN-10: 1800610866
- ISBN-13: 9781800610866
- Format: 15.2 x 22.9 x 2 cm, minkšti viršeliai
- Language: English English
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.
Reviews