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
›8:45 (1h)
The Marauders Map of adversarial examples: State of knowledge on evasion attacks in machine learning (2/3)
Rafael Pinot
Rafael Pinot
› Conference room
8:45 - 9:45 (1h)
The Marauders Map of adversarial examples: State of knowledge on evasion attacks in machine learning (2/3)
Conference room
Rafael Pinot
›9:45 (1h)
9:45 - 10:45 (1h)
Convex Optimization and First-Order Algorithms for Data Science (2/3)
Adrien Taylor
›10:45 (30min)
10:45 - 11:15 (30min)
Coffee break
›11:15 (1h)
› Conference room
11:15 - 12:15 (1h)
Transport based generative modeling and applications to sampling (1/3)
Conference room
Marylou Gabrié
›12:30 (1h)
12:30 - 13:30 (1h)
Lunch
›13:30 (2h)
13:30 - 15:30 (2h)
Free time
15:30 - 16:45 (1h15)
CT - Session 2
Conference room
› When to Forget? Complexity Trade-offs in Machine Unlearning
- Martin Van Waerebeke, Centre Inria de Paris
15:30-15:55 (25min)
› Consensus Monte Carlo for mixtures of categorical distributions
- Julie Fendler, MRC Biostatistics Unit, University of Cambridge
15:55-16:20 (25min)
› Finite-Sample Convergence Bounds for Trust Region Policy Optimization in Mean-Field Games
- Antonio Ocello, ENSAE
16:20-16:45 (25min)
›16:45 (30min)
16:45 - 17:15 (30min)
Coffee break
17:15 - 18:05 (50min)
Optimization bilevel et unrolling
Conference room
Thomas Moreau
›18:10 (50min)
Machine learning and numerical simulations. Interplay between data and physical models.
Mathilde Mougeot
Mathilde Mougeot
› Conference room
18:10 - 19:00 (50min)
Machine learning and numerical simulations. Interplay between data and physical models.
Conference room
Mathilde Mougeot
›19:30 (1h)
19:30 - 20:30 (1h)
Dinner
