Papers
546 papers found
Feynman-Kac Neural Network Architectures for Stochastic Control Using Second-Order FBSDE Theory
Marcus Pereira, Ziyi Wang, Tianrong Chen et al.
Finite Sample System Identification: Optimal Rates and the Role of Regularization
Yue Sun, Samet Oymak, Maryam Fazel
Finite-Time Performance of Distributed Two-Time-Scale Stochastic Approximation
Thinh Doan, Justin Romberg
Fitting a Linear Control Policy to Demonstrations with a Kalman Constraint
Malayandi Palan, Shane Barratt, Alex McCauley et al.
Generating Robust Supervision for Learning-Based Visual Navigation Using Hamilton-Jacobi Reachability
Anjian Li, Somil Bansal, Georgios Giovanis et al.
Hamilton-Jacobi-Bellman Equations for Q-Learning in Continuous Time
Jeongho Kim, Insoon Yang
Hierarchical Decomposition of Nonlinear Dynamics and Control for System Identification and Policy Distillation
Hany Abdulsamad, Jan Peters
Identifying Mechanical Models of Unknown Objects with Differentiable Physics Simulations
Changkyu Song, Abdeslam Boularias
Improving Input-Output Linearizing Controllers for Bipedal Robots via Reinforcement Learning
Fernando Castañeda, Mathias Wulfman, Ayush Agrawal et al.
Improving Robustness via Risk Averse Distributional Reinforcement Learning
Rahul Singh, Qinsheng Zhang, Yongxin Chen
Information Theoretic Model Predictive Q-Learning
Mohak Bhardwaj, Ankur Handa, Dieter Fox et al.
Keyframing the Future: Keyframe Discovery for Visual Prediction and Planning
Karl Pertsch, Oleh Rybkin, Jingyun Yang et al.
L1-GP: L1 Adaptive Control with Bayesian Learning
Aditya Gahlawat, Pan Zhao, Andrew Patterson et al.
Lambda-Policy Iteration with Randomization for Contractive Models with Infinite Policies: Well-Posedness and Convergence
Yuchao Li, Karl Henrik Johansson, Jonas Mårtensson
Learning-based Stochastic Model Predictive Control with State-Dependent Uncertainty
Angelo Domenico Bonzanini, Ali Mesbah
Learning Constrained Dynamics with Gauss’ Principle adhering Gaussian Processes
Andreas Geist, Sebastian Trimpe
Learning Convex Optimization Control Policies
Akshay Agrawal, Shane Barratt, Stephen Boyd et al.
Learning Dynamical Systems with Side Information
Amir Ali Ahmadi, Bachir El Khadir
Learning for Safety-Critical Control with Control Barrier Functions
Andrew Taylor, Andrew Singletary, Yisong Yue et al.
Learning Navigation Costs from Demonstrations with Semantic Observations
Tianyu Wang, Vikas Dhiman, Nikolay Atanasov
Learning nonlinear dynamical systems from a single trajectory
Dylan Foster, Tuhin Sarkar, Alexander Rakhlin
Learning solutions to hybrid control problems using Benders cuts
Sandeep Menta, Joseph Warrington, John Lygeros et al.
Learning supported Model Predictive Control for Tracking of Periodic References
Janine Matschek, Rolf Findeisen
Learning the Globally Optimal Distributed LQ Regulator
Luca Furieri, Yang Zheng, Maryam Kamgarpour
Learning the model-free linear quadratic regulator via random search
Hesameddin Mohammadi, Mihailo R. Jovanovic’, Mahdi Soltanolkotabi