Oral presentations

Session 1: Statistical Learning & Neural Networks

Tuesday, July 16, 10:00 - 11:00

Paper	Paper Title	Authors
50	Parameter-Adaptive Approximate MPC: Tuning Neural-Network Controllers without Re-Training	Henrik Hose, Alexander Gräfe and Sebastian Trimpe
93	Rademacher Complexity of Neural ODEs via Chen-Fliess Series	Joshua Hanson and Maxim Raginsky
85	Data-Driven Robust Covariance Control for Uncertain Linear Systems	Joshua Pilipovsky and Panagiotis Tsiotras
185	Data Driven Verification of Positive Invariant Sets for Discrete, Nonlinear Systems	Amy K. Strong and Leila J. Bridgeman

Session 2: Optimization and Uncertainty Quantification

Tuesday, July 16, 15:15 - 16:15

Paper	Paper Title	Authors
52	Inverse Optimal Control as an Errors-in-Variables Problem	Rahel Rickenbach, Anna Scampicchio and Melanie Zeilinger
111	Meta-Learning Linear Quadratic Regulators: A Policy Gradient MAML Approach for the Model-free LQR	Leonardo Felipe Toso, Donglin Zhan, James Anderson and Han Wang
124	Nonasymptotic Regret Analysis of Adaptive Linear Quadratic Control with Model Misspecification	Bruce Lee, Anders Rantzer and Nikolai Matni
162	Towards Model-Free LQR Control over Rate-Limited Channels	Aritra Mitra, Lintao Ye and Vijay Gupta

Session 3: Learning for Control

Wednesday, July 17, 09:45 - 10:45

Paper	Paper Title	Authors
42	Uncertainty Quantification of Set-Membership Estimation in Control and Perception: Revisiting the Minimum Enclosing Ellipsoid	Yukai Tang, Jean-Bernard Lasserre and Heng Yang
108	Learning Robust Policies for Uncertain Parametric Markov Decision Processes	Luke Rickard, Alessandro Abate and Kostas Margellos
123	System-level Safety Guard: Safe Tracking Control through Uncertain Neural Network Dynamics Models	Xiao Li, Yutong Li, Anouck Girard and Ilya Kolmanovsky
120	In vivo learning-based control of microbial populations density in bioreactors	Sara Maria Brancato, Davide Salzano, Francesco De Lellis, Davide Fiore, Giovanni Russo and Mario di Bernardo

Session 4: Reinforcement Learning for Control and Game Theory

Wednesday, July 17, 14:45 - 15:45

Paper	Paper Title	Authors
51	Õ(T^-1) Convergence to (Coarse) Correlated Equilibria in Full-Information General-Sum Markov Games	Weichao Mao, Haoran Qiu, Chen Wang, Hubertus Franke, Zbigniew Kalbarczyk and Tamer Başar
96	Learning ϵ-Nash Equilibrium Policies in Stochastic Games with Unknown Independent Chains Using Online Mirror Descent	Tiancheng Qin and S. Rasoul Etesami
121	Bounded Robustness in Reinforcement Learning via Lexicographic Objectives	Daniel Jarne Ornia, Licio Romao, Lewis Hammond, Manuel Mazo Jr and Alessandro Abate
227	Conservative Model-based Imitation Learning	Victor Kolev, Rafael Rafailov, Kyle Hatch, Jiajun Wu and Chelsea Finn