Programme

jeudi 7 avril 2022

Heures événement (+)
10:00 - 10:30 Accueil (Amphi)  
10:30 - 12:30 Adversarial ML. (Amphi) (+)  
10:30 - 11:30 › Generative Adversarial Networks: understanding optimality properties of Wasserstein GANs (WGANs) - Ugo Tanelian, CRITEO  
11:30 - 12:30 › Security threats in machine learning - Teddy Furon, Inria Rennes – Bretagne Atlantique  
12:30 - 14:00 Déjeuner  
14:00 - 17:30 Stochastic gradient descent (Amphi) (+)  
14:00 - 15:00 › A review of nonconvex stochastic subgradient descent - Pascal Bianchi, Télécom Paris  
15:00 - 16:00 › Stochastic Gradient Descent with communication constraints and compression operators. - Aymeric Dieuleveut, Centre de Mathématiques Appliquées - Ecole Polytechnique  
16:30 - 17:30 › Stochastic gradient descents to online Newton algorithms - Antoine Godichon-Baggioni, UPMC  

vendredi 8 avril 2022

Heures événement (+)
09:30 - 10:00 Café  
10:00 - 12:00 Sampling (Amphi) (+)  
10:00 - 11:00 › Adaptive Importance Sampling meets Mirror Descent: a Bias-variance tradeoff - Anna Korba, ENSAE  
11:00 - 12:00 › Non-Equilibrium Sampling - Alain Durmus - ENS (Paris-Saclay)  
12:00 - 13:30 Déjeuner  
13:30 - 15:30 EM algorithm (+)  
13:30 - 14:30 › Properties of the stochastic approximation EM algorithm with mini-batch sampling - Estelle Kuhn - INRAE  
14:30 - 15:30 › Frugal Gaussian clustering of huge imbalanced datasets through a bin-marginal approach - Christine Keribin - Laboratoire de Mathématiques d'Orsay  
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