881 search results - page 11 / 177 » Spectral Algorithms for Supervised Learning |
157
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JMLR
2010
14 years 11 months ago
2010
We use convex relaxation techniques to provide a sequence of regularized low-rank solutions for large-scale matrix completion problems. Using the nuclear norm as a regularizer, we...
158
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ICML
2009
IEEE
16 years 5 months ago
2009
IEEE
Training principles for unsupervised learning are often derived from motivations that appear to be independent of supervised learning. In this paper we present a simple unificatio...
126
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NIPS
2007
15 years 5 months ago
2007
We present a simple, agnostic active learning algorithm that works for any hypothesis class of bounded VC dimension, and any data distribution. Our algorithm extends a scheme of C...
141
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ICML
2009
IEEE
16 years 5 months ago
2009
IEEE
We introduce a new algorithm for binary classification in the selective sampling protocol. Our algorithm uses Regularized Least Squares (RLS) as base classifier, and for this reas...
150
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AUSDM
2006
Springer
15 years 8 months ago
2006
Springer
The support vector machine (SVM) is a wellestablished and accurate supervised learning method for the classification of data in various application fields. The statistical learnin...