(Tentative - Best viewed with laptops)
Day 1
Day 2
Breakfast: 9:00 a.m.– 9:45 a.m.
Breakfast 9:00 a.m.– 10:00 a.m.
Introduction: 9:45 a.m.– 10:00 a.m.
10:00 a.m.– 11:00 a.m.
Learning under requirements
10:00 a.m.– 11:00 a.m.
Perspective on the analysis and design of optimization algorithms
Short coffee break - 15mins
11:15 a.m.– 12:15 p.m.
On Graphs with Finite-Time Consensus
11:15 a.m.– 12:15 p.m.
Towards understanding sequential/parallelized learning (agents, MoEs, etc)
Lunch break until 2:00 p.m.
2:00 p.m.– 3:00p.m.
Machine Learning for Signal Processing: Learning to Reconstruct, Learning to Discover
2:00 p.m.– 3:00 p.m.
Compositional Design of Society-Critical Systems: From Autonomy to Future Mobility
3:00 p.m.– 4:00 p.m.
Efficient AI – a full stack perspective
3:00 p.m.– 4:00 p.m.
Quentin Berthet
Implicit Diffusion: Efficient Optimization through Stochastic Sampling
4:00 p.m.– 4:45 p.m.
Title
4:00 p.m.– 4:15 p.m.