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154
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ICML
2004
IEEE
16 years 6 months ago
2004
IEEE
Feature selection is the task of choosing a small set out of a given set of features that capture the relevant properties of the data. In the context of supervised classification ...
158
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ICML
2004
IEEE
16 years 6 months ago
2004
IEEE
Boosting is a popular approach for building accurate classifiers. Despite the initial popular belief, boosting algorithms do exhibit overfitting and are sensitive to label noise. ...
148
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ICML
2004
IEEE
16 years 6 months ago
2004
IEEE
Many clustering algorithms fail when dealing with high dimensional data. Principal component analysis (PCA) is a popular dimensionality reduction algorithm. However, it assumes a ...
155
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ICML
2004
IEEE
16 years 6 months ago
2004
IEEE
A standard method for approximating averages in probabilistic models is to construct a Markov chain in the product space of the random variables with the desired equilibrium distr...
143
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ICML
2004
IEEE
16 years 6 months ago
2004
IEEE
Surrogate maximization (or minimization) (SM) algorithms are a family of algorithms that can be regarded as a generalization of expectation-maximization (EM) algorithms. There are...