PROGRAMME

Centre de recherches mathématiques
Université de Montréal

École printanière PNSDC/MITACS sur les algorithmes d’apprentissage:
perspectives statisticienne et informaticienne/

NPCDS/MITACS Spring School on Statistical
and Machine Learning: Topics at the Interface

23-27 mai / May 23-27, 2006

INTRODUCTION
Mardi 23 mai / Tuesday, May 23
08:30 - 09:00
Inscription (Salle 5345) • Café / (salle 6245) /
Registration (Room 5345) • Coffee (Room 6245)
09:00 - 09:30
Bienvenue et introduction /
Welcome and introduction
09:30 - 10:30
Russell Steele (McGill)
Basic statistical inference vs. machine learning
terminology
10:30 - 10:45
Pause café • Coffee Break (Salle / Room 6245)
10:45 - 11:45
Russell Steele (McGill)
Bootstrapping/CV/Bayesian methods for penalizing complexity
11:45 - 13:00
Lunch
13:00 - 14:00
Software introduction
14:00 - 15:30
Laboratoire informatique / Computing Lab
(Salle / Room 1340)
15:30 - 16:00
Pause café • Coffee Break (Salle / Room 6245)
16:00 - 17:00
Laboratoire informatique / Computing Lab
(Salle / Room 1340)
NEURAL NETWORKS
Mercredi 24 mai / Wednesday, May 24
09:00 - 09:45
Helmut Kroger (Laval)
Background and history
09:45 - 10:45
Doina Precup (McGill)
Machine learning perspective
10:45 - 11:00
Pause café • Coffee Break (Salle / Room 6245)
11:00 - 11:45
Antonio Ciampi (McGill)
Bayesian approaches
11:45 - 13:00
Lunch
13:00 - 14:00
Hugh Chipman (Acadia) & Antonio Ciampi (McGill)
Model selection issues
14:00 - 15:30
Laboratoire informatique / Computing Lab (Salle / Room 1340)
15:30 - 16:00
Pause café • Coffee Break (Salle / Room 6245)
16:00 - 17:00
Laboratoire informatique / Computing Lab (Salle / Room 1340)
MODEL-BASED CLUSTERING
Jeudi 25 mai / Thursday, May 25
09:00 - 09:45
Russell Steele (McGill)
Background
09:45 - 10:30
Russell Steele (McGill)
Machine learning perspective
10:30 - 10:45
Pause café • Coffee Break (Salle / Room 6245)
10:45 - 11:45
Russell Steele (McGill)
Bayesian approaches
11:45 - 13:00
Lunch
13:00 - 14:00
Russell Steele (McGill)
Model selection issues
14:00 - 15:30
Laboratoire informatique / Computing Lab (Salle / Room 1340)
15:30 - 16:00
Pause café • Coffee Break (Salle / Room 6245)
16:00 - 17:00
Laboratoire informatique / Computing Lab (Salle / Room 1340)
SUPPORT VECTOR MACHINE
Vendredi 26 mai / Friday, May 26
09:00 - 09:45
Ji Zhu (Michigan)
Background
09:45 - 10:30
Ji Zhu (Michigan)
Statistical learning interpretation
10:30 - 10:45
Pause café • Coffee Break (Salle / Room 6245)
10:45 - 11:45
Doina Precup (McGill)
Dangers of Using SVM's
11:45 - 13:00
Lunch
13:00 - 14:00
Doina Precup (McGill)
Applications
14:00 - 15:30
Laboratoire informatique / Computing Lab (Salle / Room 1340)
15:30 - 16:00
Pause café • Coffee Break (Salle / Room 6245)
16:00 - 17:00
Laboratoire informatique / Computing Lab (Salle / Room 1340)
MANIFOLD LEARNING
Samedi 27 mai / Saturday, May 27
09:00 - 09:45
Yoshua Bengio (Montreal)
Background
09:45 - 10:30
Yoshua Bengio (Montreal)
Statistical learning interpretation
10:30 - 10:45
Pause café • Coffee Break (Salle / Room 6245)
10:45 - 11:45
Helmut Kroger (Laval)
Kohonen map connections
11:45 - 13:00
Lunch
13:00 - 14:00
Yoshua Bengio (Montreal)
Connections with semi-supervised learning
14:00 - 15:30
Laboratoire informatique / Computing Lab (Salle / Room 1340)
15:30 - 16:00
Pause café • Coffee Break (Salle / Room 6245)
16:00 - 17:00
Laboratoire informatique / Computing Lab (Salle / Room 1340)