(Tentative - Best viewed with laptops)
Day 1
Day 2
Breakfast: 8:00 a.m.– 8:45 a.m.
Breakfast 8:00 a.m.– 9:00 a.m.
Introduction: 8:45 a.m.– 9:00 a.m.
9:15 a.m.– 10:05 a.m.
Characterizing Trust and Resilience in Distributed Optimization for Cyberphysical
Systems
9:00 a.m.– 9:50 a.m.
Towards Federated Foundation Models
10:10 a.m.– 10:30 a.m.
Prescribed-Time Nash Equilibrium-Seeking in Switching Games: Synergies between Non-smooth, Time-Varying, and Momentum-based Techniques
9:50 a.m.– 10:10 a.m.
Zen: Near-Optimal Communications for Sparse and Distributed DNN Training
Coffee break until 11:00 a.m.
11:00 a.m.– 11:50 a.m.
Distributed network utility maximization in large scale hierarchical systems
11:00 a.m.– 11:50 a.m.
Benchmarking Neural Network Training Algorithms
11:50 a.m.– 12:10 p.m.
Distributed and private matrix inverses, correlations and flow embeddings
11:50 a.m.– 12:10 p.m.
FeDXL:Provable Federated Learning for Deep X-Risk Optimization
Lunch break until 2:00 p.m.
2:00 p.m.– 2:50 p.m.
Redefining small language models performance
2:00 p.m.– 2:50 p.m.
Heterogeneity-aware Algorithms for Federated Optimization
2:50 p.m.– 3:40 p.m.
Decentralised Bilevel Optimization
2:50 p.m.– 3:40 p.m.
Provably Private and Robust Federated Learning
3:50 p.m.– 5:30 p.m.
3:40 p.m.– 4:30 p.m.
6:00 p.m.–