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185
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JMLR
2010
15 years 1 months ago
2010
Principal component analysis (PCA) is a classical data analysis technique that finds linear transformations of data that retain the maximal amount of variance. We study a case whe...
206
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JMLR
2010
15 years 1 months ago
2010
We present an extension of sparse PCA, or sparse dictionary learning, where the sparsity patterns of all dictionary elements are structured and constrained to belong to a prespeci...
192
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JMLR
2010
15 years 1 months ago
2010
The goal of sufficient dimension reduction in supervised learning is to find the lowdimensional subspace of input features that is `sufficient' for predicting output values. ...
198
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JMLR
2010
15 years 1 months ago
2010
Bandit algorithms are concerned with trading exploration with exploitation where a number of options are available but we can only learn their quality by experimenting with them. ...
196
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NAR
2010
15 years 1 months ago
2010
Nucleic acid-binding proteins are involved in a great number of cellular processes. Understanding the mechanisms underlying these proteins first requires the identification of spe...