[Lisa_seminaires] UdeM-McGill-MITACS machine learning seminar Tue May 27th, 10:00am, MC437
Dumitru Erhan
dumitru.erhan at umontreal.ca
Mer 21 Mai 17:54:04 EDT 2008
Next week's UdeM-McGill-MITACS seminar (see http://www.iro.umontreal.ca/article.php3?id_article=107&lang=en)
:
Learning in the Sample Compression Framework
by Mohak Shah,
Probabilistic Vision Group
Centre for Intelligent Machines
McGill University
Location: McConnell Engineering (McGill), room 437
Time: May 27th 2008, 10am
This talk will focus on the algorithms’ learning capabilities under
the Sample Compression framework highlighting some of the advantages
over other learning paradigms. We will show how theoretically
motivated algorithms with practical realizable generalization error
bounds can be obtained and further how these risk bounds can be
utilized to guide the model selection. As a special case, we will
focus on decision based classifiers (e.g. learning conjunctions or
disjunctions of data-dependent features) and show how performances
comparable to and in some cases better than the state-of-the-art
learning algorithms such as SVM can be obtained.
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