09:30 - 10:00 Some Hints on the Teaching of Machine Learning to Industrial Practitioners - Christopher Kermorvant, Paris, France
(paper, talk)
10:00 - 10:30 Master's Level Machine Learning: Public Perceptions - David Barber, London, United Kingdom
(paper, talk)
Coffee break
Session 2: Some Master's with strong machine learning components (11:00 - 12:00)
11:00 - 11:30 Interactions between the Industrial and Academic Skill for Teaching Machine Learning in
Master's Programs - Younès Benanni and Céline Rouveirol, Paris, France
(paper, talk)
11:30 - 12:00 Macadamia: Master's Programme in Machine Learning and Data Mining - Tapani Raiko, Kai Puolamäki, Samuel Kaski, Jaakko Hollmén, Antti Honkela, Juha Karhunen, Heikki Mannila, Erkki Oja and Olli Simula, Helsinki, Finland
(paper, talk)
Lunch
Session 3: Erasmus Mundus issues (14:00 - 15:00)
14:00 - 14:30 About the Erasmus Mundus programme - Thomas Guillobez, Saint-Étienne, France
(paper, talk)
14:30 - 15:00 The Master Erasmus Mundus CIMET "Color in Informatics and Media Technology" - Alain Trémeau, Saint-Etienne, France
(paper, talk)
Bus break
Session 4: What should be taught
Theoritical Computer Science for Machine Learning - Colin de la Higuera, Saint-Étienne, France
(paper, talk)
Teaching Experiments and Programming for Machine Learning - François Jacquenet, Saint-Étienne, France
(paper, talk)
What is the place of Machine Learning between Pattern Recognition and Optimization? - Laurent Miclet, Lannion and Antoine Cornuéjols, Paris, France
(paper, talk)
Debate
Banquet
Wednesday 7th
Session 5: How machine learning might be taught (9:00 - 10:00)
09:00 - 09:30 Learning mixture models - courseware for finite
mixtures of Bernoulli distributions - Jaakko Hollmén and Tapani Raiko, Helsinki, Finland
(paper, talk)
09:30 - 10:00 Triad "Lectures-Labs-Contest" as a form
of Research Based Approach in Teaching Machine Learning - Igor Chikalov
Victor Eruhimov, Intel, Alexey Polovinkin and Nikolai Yu. Zolotykh, Nizhni Novgorod, Russia
(paper)
Coffee break
Session 6: Teaching a larger audience (10:30 - 12:00)
10:30 - 11:00 A point of view on teaching Pattern Recognition - Maria Luisa Micó, Alicante, Spain
(paper, talk)
11:00 - 11:30 Spring School in
Machine Learning Teaching experiences - Cécile Capponi, François Denis, Rémi
Eyraud, Amaury Habrard and Liva Ralaivola, Marseille, France
(paper, talk)
11:30 - 12:00 Discussion
Lunch
End of workshop
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