Lectures on Convex Optimization: 137 (Springer Optimization and Its Applications, 137) - Image 1

Price loading...

Springer Lectures on Convex Optimization: 137 (Springer Optimization and Its Applications, 137)

Name: Lectures on Convex Optimization: 137 (Springer Optimization and Its Applications, 137)
Brand: Springer

Algorithms

Price History & Forecast

No Price Data Available

Price history will appear here once data is collected from Amazon.

Price Distribution

No price data available for histogram

Description

This book provides a comprehensive, modern introduction to convex optimization, a field that is becoming increasingly important in applied mathematics, economics and finance, engineering, and computer science, notably in data science and machine learning. Written by a leading expert in the field, this book includes recent advances in the algorithmic theory of convex optimization, naturally complementing the existing literature. It contains a unified and rigorous presentation of the acceleration techniques for minimization schemes of first- and second-order. It provides readers with a full treatment of the smoothing technique, which has tremendously extended the abilities of gradient-type methods. Several powerful approaches in structural optimization, including optimization in relative scale and polynomial-time interior-point methods, are also discussed in detail. Researchers in theoretical optimization as well as professionals working on optimization problems will findthis book very useful. It presents many successful examples of how to develop very fast specialized minimization algorithms. Based on the author’s lectures, it can naturally serve as the basis for introductory and advanced courses in convex optimization for students in engineering, economics, computer science and mathematics.

Product Specifications

Brand: Springer
Format: hardcover
ASIN: 3319915770
Category: Books > Subjects > Computing & Internet > Programming > Algorithms
Domain: Amazon UK
Release Date: 01 December 2018
Listed Since: 11 April 2018

Barcode

No barcode data available

Springer Lectures on Convex Optimization: 137 (Springer Optimization and Its Applications, 137)

Price History & Forecast

No Price Data Available

Price Distribution

Description

Product Specifications

Barcode

Similar Products You Might Like

Convex Analysis and Nonlinear Optimization: Theory and Examples (CMS Books in Mathematics)

Springer Introductory Lectures on Convex Optimization - 87

Convex Analysis and Global Optimization: 110 (Springer Optimization and Its Applications, 110)

Essential Mathematics for Convex Optimization

Convex Analysis and Beyond: Volume I: Basic Theory (Springer Series in Operations Research and Financial Engineering)

Convex Optimization in Normed Spaces: Theory, Methods and Examples (SpringerBriefs in Optimization)

Convex Optimization with Computational Errors: 155 (Springer Optimization and Its Applications, 155)

Convex Optimization for Machine Learning (NowOpen)

Convex Optimization

Convex Analysis and Global Optimization: 22 (Nonconvex Optimization and Its Applications, 22)

Deterministic Global Optimization: Theory, Methods and Applications: 37 (Nonconvex Optimization and Its Applications, 37)

Non-convex Optimization for Machine Learning (Foundations and Trends in Machine Learning)

Introduction to Online Convex Optimization (Foundations and Trends (R) in Optimization)

Large-Scale Convex Optimization: Algorithms & Analyses via Monotone Operators

Convex Optimization: Introductory Course

Lectures on Convex Sets

Deterministic Global Optimization: Theory, Methods and Applications: 37 (Nonconvex Optimization and Its Applications, 37)

Springer Convex and Stochastic Optimization (Universitext) Book

Introduction to Global Optimization: 3 (Nonconvex Optimization and Its Applications, 3)

Generalized Convexity, Generalized Monotonicity: Recent Results: Recent Results: 27 (Nonconvex Optimization and Its Applications, 27)

Introduction to Online Convex Optimization, Second Edition (Adaptive Computation and Machine Learning) (Adaptive Computation and Machine Learning series)

Optimization for Machine Learning (Neural Information Processing series)

Practical Mathematical Optimization: Basic Optimization Theory and Gradient-Based Algorithms: 133 (Springer Optimization and Its Applications, 133)

Optimization on Solution Sets of Common Fixed Point Problems: 178 (Springer Optimization and Its Applications, 178)