Hi All,
We will have a talk tomorrow (Friday) by Nicolas Le Roux (work with
Andrew Fitzgibbon). Apologies for the short notice.
Place: Pavillon André-Aisenstadt, room 3195
Time 3pm, Friday July 16th
Title: A fast natural Newton method
Abstract:
Nowadays, for many tasks such as object recognition or language
modeling, data is plentiful. As such, an important challenge has
become to find learning algorithms which can make use of all the
available data. In this setting, called ``large-scale learning'' by
Bottou and Bousquet (2008), learning and optimization become different
and powerful optimization algorithms are suboptimal learning
algorithms. While most efforts are focused on adapting optimization
algorithms for learning by efficiently using the information contained
in the Hessian, Le Roux et al. (2008) exploited the special structure
of the learning problem to achieve faster convergence. In this paper,
we investigate a natural way of combining these two directions to
yield fast and robust learning algorithms.
Cheers,
Aaron
--
Aaron C. Courville
Département d’Informatique et
de recherche opérationnelle
Université de Montréal
email:Aaron.Courville@gmail.com
