Reminder: we have a tea talk this morning at 11h30 in the LISA Lab. Details below.
Cheers, Aaron
On Tue, Nov 1, 2011 at 6:12 PM, Aaron Courville aaron.courville@gmail.comwrote:
Due to a conflicting Ubisoft meeting we have rescheduled Ian's Tea Talk for Friday at 11h30. Original message, including the abstract, below.
i.e. New Date/Time: Friday Nov. 4th / 11h30
Cheers, Aaron
On Tue, Nov 1, 2011 at 6:20 AM, Aaron Courville <aaron.courville@gmail.com
wrote:
Due to travel by some of us to a DARPA-related meeting. The tea talk this week has been moved to Friday. Hope you all can make it -- this talk should be of interest to everyone and particularly for the newer students that may not have had much previous exposure to statistical learning theory. The talk will be given by Ian Goodfellow.
Date/Time: Friday Nov. 4th / 14h00 Location: LISA Lab (AA3256)
Title: Statistical Learning Theory
Abstract: I will give a tutorial on statistical learning theory. First I will show how to prove some simple probabilistic guarantees on the generalization error of a classifier in the PAC learning framework using Chebyshev's inequality. Next I will discuss how to extend these bounds to more realistic settings using the concept of Vapnik-Chervonenkis dimension. Finally I will compare structural risk minimization, a model selection principle based on statistical learning theory, to other methods of obtaining low generalization error.
Cheers, Aaron
-- Aaron C. Courville Département d’Informatique et de recherche opérationnelle Université de Montréal email:Aaron.Courville@gmail.com
-- Aaron C. Courville Département d’Informatique et de recherche opérationnelle Université de Montréal email:Aaron.Courville@gmail.com