Morning Session: | |
---|---|
Linear and order statistics combiners for classification | Kagan Tumer |
Is boosting a universal learning algorithm? | Yoav Freund |
Error-correcting output coding: current results | Thomas Dietterich |
Using adaptive bagging to debias predictors | Leo Breiman |
Afternoon Session: | |
The ubiquitous role of reproducing kernel Hilbert spaces in machine learning: Regularization, Bayes estimates, Support Vector Machines, Graphical Models, Mean Field Theory | Grace Wahba |
High-rise generalisation: what will we find in the penthouse? | Chris Thornton |
Some extensions of bagging | Tom Heskes |
An application of monte-carlo cross-validation (or bagging without replacement") for predicting website visitor preferences. | Mark Plutowski |
We still don't know why model ensembles work. | Pedro Domingos |
If you have any questions or comments, please email Kagan Tumer.
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