Autumn School on Recent Advances in Machine Learning

7:30 - 8:30 (1h)

Breakfast

9:15 - 9:45 (30min)

Welcome speech

9:45 - 10:45 (1h)

The Marauders Map of adversarial examples: State of knowledge on evasion attacks in machine learning (1/3)

Conference room

Rafael Pinot

10:45 - 11:15 (30min)

Coffee break

11:15 - 12:15 (1h)

Convex Optimization and First-Order Algorithms for Data Science (1/3)

Conference room

Adrien Taylor

12:30 - 13:30 (1h)

Lunch

13:30 - 15:55 (2h25)

Free time

15:55 - 16:45 (50min)

Approximating Optimal Transport plans with Sliced-Wasserstein

Conference room

Laetitia Chapel

16:45 - 17:15 (30min)

Coffee break

17:15 - 17:45 (30min)

Speed presentation from participants

Conference room

17:45 - 19:00 (1h15)

CT - Session 1

Conference room

› Continuous sparse estimation of a Gaussian Mixture Model with unknown covariances - Romane Giard, Institut Camille Jordan 17:45-18:10 (25min)

› UNHaP : Unmixing Noise from Hawkes Processes - Virginie Loison, Modèles et inférence pour les données de Neuroimagerie, Marqueurs cardiovasculaires en situation de stress 18:10-18:35 (25min)

› Optimal transport with Heterogenously Missing Data - Linus Bleistein, Inria de Paris, Artificial Intelligence Laboratory [EPFL], Université Paris Dauphine-PSL 18:35-19:00 (25min)

19:30 - 20:30 (1h)

Dinner

Program