“Optimizing Data for Decision-Making” by Asu Ozdaglar (MIT)

“Foundation Models for Autonomous Vehicles” by Marco Pavone (Stanford and NVIDIA)

“Some variants of gradient dominance conditions motivated by LQR direct policy optimization” by Eduardo Sontag (Northeastern University)

“Federated Reinforcement Learning: Statistical and Communication Trade-offs” by Yuejie Chi (Carnegie Mellon University)

Official start of L4DC’25

Time for exciting afternoon tutorials

"Capabilities of Large Language Models (LLMs) in Control Engineering" by Bin Hu, Geir Dullerud, Peter Seiler, and Huan Zhang

"The Scenario Approach: Data Science for Decision and Control" by Marco Claudio Campi and Simone Garatti

L4DC kicked off with the morning tutorials

"Higher-Order Learning Dynamics in Games" by Panayotis Mertikopoulos, Lacra Pavel, Jeff S. Shamma

"Neural Networks in the Loop: a Tutorial on Robust Machine Learning for Control" by Ian Manchester, Peter Seiler, Bin Hu