A01=Guillaume Carlier
Acyclic Matrix
Augmented Lagrangian
Author_Guillaume Carlier
Basis Pursuit
Bellman Equation
Bistochastic Matrix
Calculus of Variations
Category=PBU
Constrained Optimization
Convex Analysis
Convex Duality
Differential Calculus
Douglas Rachford
Dynamic Programming
Ekeland's Variational Principle
Envelope Theorems
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
Euler-Lagrange Equations
Existence Theory
Extreme Points
Farkas Minkowski
Hamilton-Jacobi Equations
Infimal Convolution
ISTA
Iterative Methods
Kantorovich Duality
KKT Rules
Lagrange Multipliers
Lagrangian Duality
Legendre Transforms
Local Inversion In Banach Spaces
LP Duality
Mangasarian-Fromowitz Condition
Nesterov Acceleration
Optimal Transport
Optimization
Optimization For Data Processing
Penrose Inverse
Principal Component Analysis
Proximal Algorithm
SDP Duality
Singular Value Decomposition
Slater Condition
Subdifferentials
Support Vector Machines
Tikhonov Regularization
Product details
- ISBN 9781800610866
- Publication Date: 07 Apr 2022
- Publisher: World Scientific Europe Ltd
- Publication City/Country: GB
- Product Form: Paperback
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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.
