Acceleration Methods

Acceleration Methods
Author :
Publisher :
Total Pages : 262
Release :
ISBN-10 : 1680839284
ISBN-13 : 9781680839289
Rating : 4/5 (84 Downloads)

Book Synopsis Acceleration Methods by : Alexandre d'Aspremont

Download or read book Acceleration Methods written by Alexandre d'Aspremont and published by . This book was released on 2021-12-15 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph covers recent advances in a range of acceleration techniques frequently used in convex optimization. Using quadratic optimization problems, the authors introduce two key families of methods, namely momentum and nested optimization schemes. These methods are covered in detail and include Chebyshev Acceleration, Nonlinear Acceleration, Nesterov Acceleration, Proximal Acceleration and Catalysts and Restart Schemes.This book provides the reader with an in-depth description of the developments in Acceleration Methods since the early 2000s, whilst referring the reader back to underpinning earlier work for further understanding. This topic is important in the modern-day application of convex optimization techniques in many applicable areas.This book is an introduction to the topic that enables the reader to quickly understand the important principles and apply the techniques to their own research.


Acceleration Methods Related Books

Acceleration Methods
Language: en
Pages: 262
Authors: Alexandre d'Aspremont
Categories: Technology & Engineering
Type: BOOK - Published: 2021-12-15 - Publisher:

DOWNLOAD EBOOK

This monograph covers recent advances in a range of acceleration techniques frequently used in convex optimization. Using quadratic optimization problems, the a
Handbook of Robust Low-Rank and Sparse Matrix Decomposition
Language: en
Pages: 553
Authors: Thierry Bouwmans
Categories: Computers
Type: BOOK - Published: 2016-05-27 - Publisher: CRC Press

DOWNLOAD EBOOK

Handbook of Robust Low-Rank and Sparse Matrix Decomposition: Applications in Image and Video Processing shows you how robust subspace learning and tracking by d
Design of Distributed and Robust Optimization Algorithms. A Systems Theoretic Approach
Language: en
Pages: 169
Authors: Simon Michalowsky
Categories: Technology & Engineering
Type: BOOK - Published: 2020-04-17 - Publisher: Logos Verlag Berlin GmbH

DOWNLOAD EBOOK

Optimization algorithms are the backbone of many modern technologies. In this thesis, we address the analysis and design of optimization algorithms from a syste
First-order and Stochastic Optimization Methods for Machine Learning
Language: en
Pages: 591
Authors: Guanghui Lan
Categories: Mathematics
Type: BOOK - Published: 2020-05-15 - Publisher: Springer Nature

DOWNLOAD EBOOK

This book covers not only foundational materials but also the most recent progresses made during the past few years on the area of machine learning algorithms.
Optimization for Machine Learning
Language: en
Pages: 509
Authors: Suvrit Sra
Categories: Computers
Type: BOOK - Published: 2012 - Publisher: MIT Press

DOWNLOAD EBOOK

An up-to-date account of the interplay between optimization and machine learning, accessible to students and researchers in both communities. The interplay betw