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Abstract: We present a framework for sparse Gaussian process (GP) methods which uses forward selection with criteria based on information-theoretical principles, previously suggested for active learning. In contrast to most previous work on sparse GPs, our goal is not only to learn sparse predictors (which can be evaluated in O(d) rather than O(n), d<<n, n the number of training points), but also to perform training under strong restrictions on time and memory requirements. The scaling of our method is... (Update)
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BibTeX entry: (Update)
Matthias Seeger, Neil D. Lawrence, and Ralf Herbrich. Fast sparse gaussian process methods: The informative vector machine. In in Advances in Neural Information Processing Systems, Workshop on Kernel Methods, 2003. http://citeseer.ist.psu.edu/lawrence03fast.html More
@misc{ seeger03fast,
author = "M. Seeger and N. Lawrence and R. Herbrich",
title = "Fast sparse gaussian process methods: The informative vector machine",
text = "Matthias Seeger, Neil D. Lawrence, and Ralf Herbrich. Fast sparse gaussian
process methods: The informative vector machine. In in Advances in Neural
Information Processing Systems, Workshop on Kernel Methods, 2003.",
year = "2003",
url = "citeseer.ist.psu.edu/lawrence03fast.html" }
Citations (may not include all citations):191 Fast training of support vector machines using sequential mi.. (context) - Platt - 1998
63 California Institute of Technology (context) - MacKay, for et al. - 1991
50 Sparse Bayesian learning and the relevance vector machine - Tipping - 2001
41 A Family of Algorithms for Approximate Bayesian Inference - Minka - 2001
20 Sparse greedy Gaussian process regression - Smola, Bartlett - 2000
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10 Sparse online Gaussian processes (context) - Csat, Manfred - 2002
5 A sparse Bayesian compression scheme - the Informative Vecto.. - Lawrence, Herbrich - 2001
3 Gaussian processes for classi cation: Mean eld algorithms (context) - Opper, Winther - 2000
1 Sparse Bayesian learning: The informative vector machine (context) - Lawrence, Seeger et al. - 2002
1 om method to speed up kernel machines (context) - Williams, Seeger et al. - 2000
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