Workshop on Modern Challenges of Learning TheoryApril 23-26, 2018Program |
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Monday, April 23, 2018 |
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09:00 - 09:30
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Registration (Room 5345) and Coffee & Croissants (Room 6245)
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Meeting room(s) : 6254 |
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09:30 - 10:30
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Peter L. Bartlett
(University of California, Berkeley) Representation, optimization and generalization properties of deep neural networks | Abstract
Video |
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10:30 - 11:00
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Coffee break
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11:00 - 12:00
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Gérard Ben Arous
(New York University) Complexity of Tensor PCA and of its optimization dynamics | Abstract
Video |
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12:00 - 13:30
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Lunch break
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13:30 - 14:30
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Marc G. Bellemare
(Google Brain Montréal) A distributional perspective on reinforcement learning | Abstract
Video |
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14:30 - 15:00
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Coffee break
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15:00 - 16:00
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Sham M. Kakade
(University of Washington) Sub-linear reinforcement learning | Abstract
Video |
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16:30 - 17:30
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Yoshua Bengio
(Université de Montréal) Figuring out the magic behind backprop and SGD | Abstract
Video |
Tuesday, April 24, 2018 |
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09:00 - 09:30
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Coffee & Croissants
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Meeting room(s) : 6254 |
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09:30 - 10:30
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Alexander Rakhlin
(MIT) Sufficient statistics for online prediction via the Burkholder method | Abstract
Video |
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10:30 - 11:00
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Coffee break
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11:00 - 12:00
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Grigoris Paouris
(Texas A&M University) The "Small ball" property in high dimensional measures | Abstract
Video |
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12:00 - 13:30
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Lunch break
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13:30 - 14:30
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Csaba Szepesvári
(University of Alberta) Completing the classification of adversarial partial monitoring games | Abstract
Video |
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14:30 - 15:00
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Coffee break
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15:00 - 16:00
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Alexandra Carpentier
(Universität Potsdam) Adaptivity to smoothness in X-armed bandits | Abstract
Video |
Wednesday, April 25, 2018 |
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09:00 - 09:30
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Coffee & Croissants
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Meeting room(s) : 6254 |
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09:30 - 10:30
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Nicolò Cesa-Bianchi
(Università degli Studi di Milano) Nonstochastic bandits with anonymous feedback | Abstract
Video |
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10:30 - 11:00
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Coffee break
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11:00 - 12:00
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Emilie Kaufmann
(Inria Lille - Nord Europ) Bandit (for) games | Abstract
Video |
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12:00 - 13:30
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Lunch break
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13:30 - 14:30
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Daniel Hsu
(Columbia University) Learning without correspondence | Abstract
Video |
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14:30 - 15:00
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Coffee break
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15:00 - 16:00
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Nicolas Le Roux
(Google Brain - Montréal) An exploration of variance reduction techniques in stochastic optimization | Abstract
Video |
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16:30 - 17:30
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Audrey Durand
(McGill University) Streaming kernel regression with provably adaptive mean, variance, and regularization | Abstract
Video |
Thursday, April 26, 2018 |
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09:00 - 09:30
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Coffee & Croissants
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Meeting room(s) : 6254 |
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09:30 - 10:30
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Gergely Neu
(Universitat Pompeu Fabra) A unified view of entropy-regularized Markov decision processes | Abstract
Video |
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10:30 - 11:00
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Coffee break
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11:00 - 12:00
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Nicolas Broutin
(Sorbonne Université) Combinatorics of colliding bullets | Abstract
Video |
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12:00 - 13:30
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Lunch break
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13:30 - 14:30
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András György
(Imperial College London) A modular analysis of adaptive online (non-)convex optimization | Abstract
Video |
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14:30 - 15:00
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Coffee break
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15:00 - 16:00
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Gautam Kamath
(MIT) Robustness in unsupervised and supervised machine learning | Abstract
Video |
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16:30 - 17:30
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Andreas Maurer
Concentration properties and examples of functions with weak interactions | Abstract
Video |
Last modified : Monday, May 13, 2019 13:50