3050 search results - page 380 / 610 » On-line Algorithms in Machine Learning |
135
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COLT
2008
Springer
15 years 6 months ago
2008
Springer
We study the problem of clustering discrete probability distributions with respect to the Kullback-Leibler (KL) divergence. This problem arises naturally in many applications. Our...
188
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CVPR
2007
IEEE
16 years 7 months ago
2007
IEEE
Many low-level vision algorithms assume a prior probability over images, and there has been great interest in trying to learn this prior from examples. Since images are very non G...
235
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CVPR
2009
IEEE
17 years 10 days ago
2009
IEEE
Many semi-supervised learning algorithms only
deal with binary classification. Their extension to the
multi-class problem is usually obtained by repeatedly
solving a set of bina...
146
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ICML
2009
IEEE
16 years 5 months ago
2009
IEEE
Sparsity is a desirable property in high dimensional learning. The 1-norm regularization can lead to primal sparsity, while max-margin methods achieve dual sparsity. Combining the...
156
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ICML
2007
IEEE
16 years 5 months ago
2007
IEEE
Non-linear dimensionality reduction of noisy data is a challenging problem encountered in a variety of data analysis applications. Recent results in the literature show that spect...