Convex learning with invariances

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

Convex learning with invariances

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

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

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 algorithms for kernels, including solvers of the SVMStruct family. The advantage of our setting is that it relies on column generation instead of modifying the underlying optimization problem directly.

Original language	English
Title of host publication	Advances in Neural Information Processing Systems 20: Proceedings of the 2007 Conference
Editors	Platt, John C., Koller, Daphne, Singer, Yoram and Roweis, Sam
Place of Publication	Vancouver Canada
Publisher	MIT Press
Pages	1489-1496
Edition	Peer Reviewed
ISBN (Print)	9781605603520
Publication status	Published - 2009
Event	Conference on Advances in Neural Information Processing Systems (NIPS 2007) - Vancouver Canada Duration: 1 Jan 2009 → … http://books.nips.cc/nips20.html

Conference

Conference	Conference on Advances in Neural Information Processing Systems (NIPS 2007)
Period	1/01/09 → …
Other	December 3-6 2007
Internet address	http://books.nips.cc/nips20.html

Cite this

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title = "Convex learning with invariances",

abstract = "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 algorithms for kernels, including solvers of the SVMStruct family. The advantage of our setting is that it relies on column generation instead of modifying the underlying optimization problem directly.",

author = "Choon-Hui Teo and Amir Globerson and Sam Roweis and Alexander Smola",

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booktitle = "Advances in Neural Information Processing Systems 20: Proceedings of the 2007 Conference",

publisher = "MIT Press",

edition = "Peer Reviewed",

note = "Conference on Advances in Neural Information Processing Systems (NIPS 2007) ; Conference date: 01-01-2009",

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Convex learning with invariances. / Teo, Choon-Hui; Globerson, Amir; Roweis, Sam et al.
Advances in Neural Information Processing Systems 20: Proceedings of the 2007 Conference. ed. / Platt, John C., Koller, Daphne, Singer, Yoram and Roweis, Sam. Peer Reviewed. ed. Vancouver Canada: MIT Press, 2009. p. 1489-1496.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Convex learning with invariances

AU - Teo, Choon-Hui

AU - Globerson, Amir

AU - Roweis, Sam

AU - Smola, Alexander

PY - 2009

Y1 - 2009

N2 - 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 algorithms for kernels, including solvers of the SVMStruct family. The advantage of our setting is that it relies on column generation instead of modifying the underlying optimization problem directly.

AB - 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 algorithms for kernels, including solvers of the SVMStruct family. The advantage of our setting is that it relies on column generation instead of modifying the underlying optimization problem directly.

M3 - Conference contribution

SN - 9781605603520

SP - 1489

EP - 1496

BT - Advances in Neural Information Processing Systems 20: Proceedings of the 2007 Conference

A2 - null, Platt, John C., Koller, Daphne, Singer, Yoram and Roweis, Sam

PB - MIT Press

CY - Vancouver Canada

T2 - Conference on Advances in Neural Information Processing Systems (NIPS 2007)

Y2 - 1 January 2009

ER -

Convex learning with invariances

Abstract

Conference

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