[Lisa_seminaires] UdeM-McGill-MITACS machine learning seminar Mon, Sept 14th @15h00

Guillaume Desjardins guillaume.desjardins at gmail.com
Mar 8 Sep 17:36:57 EDT 2009


We start off the new academic year with a talk from Dr. Massih-Reza
Amini entitled "Learning from Multiple Partially Observed Views".

Speaker: Dr. Massih-Reza Amini
              Associate Professor of  Pierre & Marie Curie University /
              Research Officer, NRC Institute for Information Technology

Location: Pavillon André-Aisenstadt (UdeM), room 3195
Time: September 14th 2009 at 15h00

Title: Learning from Multiple Partially Observed Views

Résumé: We address the problem of learning classifiers when
observations have multiple views, some of which may not be observed
for all examples. We assume the existence of view generating functions
which may complete the missing views in an approximate way. This
situation corresponds for example to learning text classifiers from
multilingual collections where documents are not available in all
languages. In that case, Machine Translation (MT) systems may be used
to translate each document in the missing languages. We derive a
generalization error bound for classifiers learned on examples with
multiple artificially created views. Our result uncovers a trade-off
between the size of the training set, the number of views, and the
quality of the view generating functions. As a consequence, we
identify situations where it is more interesting to use multiple views
for learning instead of classical single view learning. An extension
of this framework is a natural way to leverage unlabeled multi-view
data in semi-supervised learning. Experimental results on a subset of
the Reuters RCV1/RCV2 collections support our findings by showing that
additional views obtained from MT may significantly improve the
classification performance in the cases identified by our trade-off.


Plus d'informations sur la liste de diffusion Lisa_seminaires