May 30, 2019Introductory remarks: Ali Jadbabaie (MIT) and Benjamin Recht (UC Berkeley) Manfred Morari (University of Pennsylvania): “A Practitioner’s Perspective” Francesco Borrelli (UC Berkeley): “Learning to Predict and Control” Angela Schoellig (University of Toronto): “Machine Learning for Robotics: Safety and Performance Guarantees for Learning-Based Control” Maryam Fazel (University of Washington): “Gradient based methods for linear system control and identification” Stefano Soatto (UC Berkeley): “Dynamics and Control of Differential Learning” Anca Dragan (UC Berkeley): “An Optimization-Centric Theory of Mind for Human-Robot Interaction” Cathy Wu (Microsoft Research/MIT): “Integrating Autonomy into Urban Systems” Planning and Discussion Session Emma Brunskill (Stanford University): “Efficient Reinforcement Learning When Data is Costly” Andreas Krause (ETH Zuerich): “Safe Exploration in Reinforcement Learning” May 31, 2019Claire Tomlin (UC Berkeley): “Safe Learning in Robotics” Dorsa Sadigh (Stanford University): “Influencing Interactive Mixed-Autonomy Systems” Rene Vidal (Johns Hopkins University): “From Optimization Algorithms to Continuous Dynamical Systems and Back” Emo Todorov (University of Washington): “Acceleration-based methods for trajectory optimization through contacts” Russ Tedrake (MIT): “Learning manipulation — and why I (still) like F=ma” John Tsitsiklis (MIT): “The Shades of Reinforcement Learning” Sergey Levine (UC Berkeley): “Robots That Learn By Doing” Sham Kakade (University of Washington): “A No Regret Algorithm for Robust Online Adaptive Control” Anima Anandkumar (CalTech): “Infusing Physics and Structure into Machine Learning” Zico Kolter (Carnegie Mellon University): “Cheating with neural networks: How to make the networks you hate obey the constraints you love”
