{We consider projected Newton-type methods for solving large-scale optimization problems arising in machine learning and related fields. We first introduce an algorithmic framework for projected Newton-type methods by reviewing a canonical projected (quasi-)Newton method. This method, while conceptually pleasing, has a high computation cost per iteration. Thus, we discuss two variants that are more scalable, namely, two-metric projection and inexact projection methods. Finally, we show how to apply the Newton-type framework to handle non-smooth objectives. Examples are provided throughout the chapter to illustrate machine learning applications of our framework.}
| Author(s): | Schmidt, M. and Kim, D. and Sra, S. |
| Book Title: | Optimization for Machine Learning |
| Pages: | 305--330 |
| Year: | 2011 |
| Publisher: | MIT Press |
| BibTeX Type: | Book Chapter (incollection) |
| Address: | Cambridge, MA, USA |
| URL: | http://www.kyb.tuebingen.mpg.de//fileadmin/user\textunderscoreupload/files/publications/2011\textunderscoreOPT\textunderscoreChapter\textunderscore6824[0].pdf |
| Electronic Archiving: | grant_archive |
BibTeX
@incollection{escidoc:0279,
title = {{Projected Newton-type methods in machine learning}},
booktitle = {{Optimization for Machine Learning}},
abstract = {{We consider projected Newton-type methods for solving large-scale optimization problems arising in machine learning and related fields. We first introduce an algorithmic framework for projected Newton-type methods by reviewing a canonical projected (quasi-)Newton method. This method, while conceptually pleasing, has a high computation cost per iteration. Thus, we discuss two variants that are more scalable, namely, two-metric projection and inexact projection methods. Finally, we show how to apply the Newton-type framework to handle non-smooth objectives. Examples are provided throughout the chapter to illustrate machine learning applications of our framework.}},
pages = {305--330},
publisher = {MIT Press},
address = {Cambridge, MA, USA},
year = {2011},
author = {Schmidt, M. and Kim, D. and Sra, S.},
url = {http://www.kyb.tuebingen.mpg.de//fileadmin/user\textunderscoreupload/files/publications/2011\textunderscoreOPT\textunderscoreChapter\textunderscore6824[0].pdf}
}