Skip navigation
Skip navigation

Convex learning with invariances

Teo, Choon-Hui; Globerson, Amir; Roweis, Sam; Smola, Alexander

Description

Incorporating invariances into a learning algorithm is a common problem in machine learning. We provide a convex formulation which can deal with arbitrary loss functions and arbitrary losses. In addition, it is a drop-in replacement for most optimization

CollectionsANU Research Publications
Date published: 2008
Type: Conference paper
URI: http://hdl.handle.net/1885/53583
Source: Advances in Neural Information Processing Systems 20: Proceedings of the 2007 Conference

Download

File Description SizeFormat Image
01_Teo_Convex_learning_with_2008.pdf374.38 kBAdobe PDF    Request a copy


Items in Open Research are protected by copyright, with all rights reserved, unless otherwise indicated.

Updated:  23 August 2018/ Responsible Officer:  University Librarian/ Page Contact:  Library Systems & Web Coordinator