07:00
08:00
09:00
10:00
11:00
12:00
13:00
14:00
15:00
16:00
17:00
18:00
19:00
20:00
›7:30 (1h)
7:30 - 8:30 (1h)
Breakfast
›9:15 (30min)
9:15 - 9:45 (30min)
Welcome speech
›9:45 (1h)
The Marauders Map of adversarial examples: State of knowledge on evasion attacks in machine learning (1/3)
Rafael Pinot
Rafael Pinot
› Conference room
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 (30min)
10:45 - 11:15 (30min)
Coffee break
›11:15 (1h)
› Conference room
11:15 - 12:15 (1h)
Convex Optimization and First-Order Algorithms for Data Science (1/3)
Conference room
Adrien Taylor
›12:30 (1h)
12:30 - 13:30 (1h)
Lunch
›13:30 (2h25)
13:30 - 15:55 (2h25)
Free time
›15:55 (50min)
› Conference room
15:55 - 16:45 (50min)
Approximating Optimal Transport plans with Sliced-Wasserstein
Conference room
Laetitia Chapel
›16:45 (30min)
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 (1h)
19:30 - 20:30 (1h)
Dinner
