Papers
546 papers found
Reward Biased Maximum Likelihood Estimation for Reinforcement Learning
Akshay Mete, Rahul Singh, Xi Liu et al.
Robust error bounds for quantised and pruned neural networks
Jiaqi Li, Ross Drummond, Stephen R. Duncan
Robust Reinforcement Learning: A Constrained Game-theoretic Approach
Jing Yu, Clement Gehring, Florian Schäfer et al.
Safe Bayesian Optimisation for Controller Design by Utilising the Parameter Space Approach
Lorenz Dörschel, David Stenger, Dirk Abel
Safely Learning Dynamical Systems from Short Trajectories
Amir Ali Ahmadi, Abraar Chaudhry, Vikas Sindhwani et al.
Safe Reinforcement Learning of Control-Affine Systems with Vertex Networks
Liyuan Zheng, Yuanyuan Shi, Lillian J. Ratliff et al.
Safe Reinforcement Learning Using Robust Action Governor
Yutong Li, Nan Li, H. Eric Tseng et al.
Sample Complexity of Linear Quadratic Gaussian (LQG) Control for Output Feedback Systems
Yang Zheng, Luca Furieri, Maryam Kamgarpour et al.
SEAGuL: Sample Efficient Adversarially Guided Learning of Value Functions
Benoit Landry, Hongkai Dai, Marco Pavone
Self-Supervised Learning of Long-Horizon Manipulation Tasks with Finite-State Task Machines
Junchi Liang, Abdeslam Boularias
Sequential Topological Representations for Predictive Models of Deformable Objects
Rika Antonova, Anastasia Varava, Peiyang Shi et al.
Stability and Identification of Random Asynchronous Linear Time-Invariant Systems
Sahin Lale, Oguzhan Teke, Babak Hassibi et al.
Stable Online Control of Linear Time-Varying Systems
Guannan Qu, Yuanyuan Shi, Sahin Lale et al.
Suboptimal coverings for continuous spaces of control tasks
James A. Preiss, Gaurav S. Sukhatme
The benefits of sharing: a cloud-aided performance-driven framework to learn optimal feedback policies
Laura Ferrarotti, Valentina Breschi, Alberto Bemporad
The Dynamics of Gradient Descent for Overparametrized Neural Networks
Siddhartha Satpathi, R Srikant
The Impact of Data on the Stability of Learning-Based Control
Armin Lederer, Alexandre Capone, Thomas Beckers et al.
Tight sampling and discarding bounds for scenario programs with an arbitrary number of removed samples
Licio Romao, Kostas Margellos, Antonis Papachristodoulou
Traffic Forecasting using Vehicle-to-Vehicle Communication
Steven Wong, Lejun Jiang, Robin Walters et al.
Training deep residual networks for uniform approximation guarantees
Matteo Marchi, Bahman Gharesifard, Paulo Tabuada
Uncertain-aware Safe Exploratory Planning using Gaussian Process and Neural Control Contraction Metric
Dawei Sun, Mohammad Javad Khojasteh, Shubhanshu Shekhar et al.
When to stop value iteration: stability and near-optimality versus computation
Mathieu Granzotto, Romain Postoyan, Dragan Nešić et al.
Actively Learning Gaussian Process Dynamics
Mona Buisson-Fenet, Friedrich Solowjow, Sebastian Trimpe
A Finite-Sample Deviation Bound for Stable Autoregressive Processes
Rodrigo A. González, Cristian R. Rojas