159 search results - page 6 / 32 » Regularization in matrix relevance learning |
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UAI
2008
14 years 11 months ago
2008
Gaussian Markov random fields (GMRFs) are useful in a broad range of applications. In this paper we tackle the problem of learning a sparse GMRF in a high-dimensional space. Our a...
ICASSP
2011
IEEE
14 years 1 months ago
2011
IEEE
There has been a significant interest in the recovery of low-rank matrices from an incomplete of measurements, due to both theoretical and practical developments demonstrating th...
ICML
2008
IEEE
15 years 10 months ago
2008
IEEE
Low-rank matrix approximation methods provide one of the simplest and most effective approaches to collaborative filtering. Such models are usually fitted to data by finding a MAP...
NIPS
2007
14 years 11 months ago
2007
Semi-supervised inductive learning concerns how to learn a decision rule from a data set containing both labeled and unlabeled data. Several boosting algorithms have been extended...
JALC
2007
14 years 9 months ago
2007
Inspired by the results obtained in the string case, we present in this paper the extension of the correction queries to regular tree languages. Relying on Angluin’s and Sakakib...