An Introduction to Matrix Concentration Inequalities
J. Tropp. (2015)cite arxiv:1501.01571Comment: 163 pages. To appear in Foundations and Trends in Machine Learning.
Zusammenfassung
In recent years, random matrices have come to play a major role in
computational mathematics, but most of the classical areas of random matrix
theory remain the province of experts. Over the last decade, with the advent of
matrix concentration inequalities, research has advanced to the point where we
can conquer many (formerly) challenging problems with a page or two of
arithmetic. The aim of this monograph is to describe the most successful
methods from this area along with some interesting examples that these
techniques can illuminate.
Beschreibung
[1501.01571] An Introduction to Matrix Concentration Inequalities
%0 Generic
%1 tropp2015introduction
%A Tropp, Joel A.
%D 2015
%K 2015 arxiv book matrix
%T An Introduction to Matrix Concentration Inequalities
%U http://arxiv.org/abs/1501.01571
%X In recent years, random matrices have come to play a major role in
computational mathematics, but most of the classical areas of random matrix
theory remain the province of experts. Over the last decade, with the advent of
matrix concentration inequalities, research has advanced to the point where we
can conquer many (formerly) challenging problems with a page or two of
arithmetic. The aim of this monograph is to describe the most successful
methods from this area along with some interesting examples that these
techniques can illuminate.
@misc{tropp2015introduction,
abstract = {In recent years, random matrices have come to play a major role in
computational mathematics, but most of the classical areas of random matrix
theory remain the province of experts. Over the last decade, with the advent of
matrix concentration inequalities, research has advanced to the point where we
can conquer many (formerly) challenging problems with a page or two of
arithmetic. The aim of this monograph is to describe the most successful
methods from this area along with some interesting examples that these
techniques can illuminate.},
added-at = {2018-07-18T13:30:14.000+0200},
author = {Tropp, Joel A.},
biburl = {https://www.bibsonomy.org/bibtex/21bc02e577cf748758ced803e0e38102e/analyst},
description = {[1501.01571] An Introduction to Matrix Concentration Inequalities},
interhash = {2f18b953eabc9986770ba2974d518039},
intrahash = {1bc02e577cf748758ced803e0e38102e},
keywords = {2015 arxiv book matrix},
note = {cite arxiv:1501.01571Comment: 163 pages. To appear in Foundations and Trends in Machine Learning},
timestamp = {2018-07-18T13:30:14.000+0200},
title = {An Introduction to Matrix Concentration Inequalities},
url = {http://arxiv.org/abs/1501.01571},
year = 2015
}