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