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» Relative Margin Machines
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ICML
2006
IEEE
14 years 8 months ago
How boosting the margin can also boost classifier complexity
Boosting methods are known not to usually overfit training data even as the size of the generated classifiers becomes large. Schapire et al. attempted to explain this phenomenon i...
Lev Reyzin, Robert E. Schapire
ICML
2004
IEEE
14 years 8 months ago
Large margin hierarchical classification
We present an algorithmic framework for supervised classification learning where the set of labels is organized in a predefined hierarchical structure. This structure is encoded b...
Ofer Dekel, Joseph Keshet, Yoram Singer
ICML
2004
IEEE
14 years 8 months ago
Margin based feature selection - theory and algorithms
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 ...
Ran Gilad-Bachrach, Amir Navot, Naftali Tishby
COLT
2008
Springer
13 years 9 months ago
Dimension and Margin Bounds for Reflection-invariant Kernels
A kernel over the Boolean domain is said to be reflection-invariant, if its value does not change when we flip the same bit in both arguments. (Many popular kernels have this prop...
Thorsten Doliwa, Michael Kallweit, Hans-Ulrich Sim...
ICML
2007
IEEE
14 years 8 months ago
Maximum margin clustering made practical
Maximum margin clustering (MMC) is a recent large margin unsupervised learning approach that has often outperformed conventional clustering methods. Computationally, it involves n...
Kai Zhang, Ivor W. Tsang, James T. Kwok