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Volume 120: Learning for Dynamics and Control, 10-11 June 2020, The Cloud
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Editors: Alexandre M. Bayen, Ali Jadbabaie, George Pappas, Pablo A. Parrilo, Benjamin Recht, Claire Tomlin, Melanie Zeilinger
Preface
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:1-4
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Actively Learning Gaussian Process Dynamics
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:5-15
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Finite Sample System Identification: Optimal Rates and the Role of Regularization
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:16-25
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Finite-Time Performance of Distributed Two-Time-Scale Stochastic Approximation
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:26-36
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Virtual Reference Feedback Tuning with data-driven reference model selection
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:37-45
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Direct Data-Driven Control with Embedded Anti-Windup Compensation
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:46-54
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Sparse and Low-bias Estimation of High Dimensional Vector Autoregressive Models
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:55-64
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Robust Online Model Adaptation by Extended Kalman Filter with Exponential Moving Average and Dynamic Multi-Epoch Strategy
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:65-74
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Estimating Reachable Sets with Scenario Optimization
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:75-84
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LSTM Neural Networks: Input to State Stability and Probabilistic Safety Verification
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:85-94
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Bayesian joint state and parameter tracking in autoregressive models
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:95-104
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Learning to Correspond Dynamical Systems
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:105-117
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Learning solutions to hybrid control problems using Benders cuts
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:118-126
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Feed-forward Neural Networks with Trainable Delay
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:127-136
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Exploiting Model Sparsity in Adaptive MPC: A Compressed Sensing Viewpoint
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:137-146
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Structured Variational Inference in Partially Observable Unstable Gaussian Process State Space Models
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:147-157
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Regret Bound for Safe Gaussian Process Bandit Optimization
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:158-159
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Smart Forgetting for Safe Online Learning with Gaussian Processes
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:160-169
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Linear Antisymmetric Recurrent Neural Networks
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:170-178
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Policy Optimization for $\mathcal{H}_2$ Linear Control with $\mathcal{H}_\infty$ Robustness Guarantee: Implicit Regularization and Global Convergence
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:179-190
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A Finite-Sample Deviation Bound for Stable Autoregressive Processes
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:191-200
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Online Data Poisoning Attacks
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:201-210
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Practical Reinforcement Learning For MPC: Learning from sparse objectives in under an hour on a real robot
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:211-224
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Learning Constrained Dynamics with Gauss’ Principle adhering Gaussian Processes
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:225-234
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Counterfactual Programming for Optimal Control
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:235-244
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Learning Navigation Costs from Demonstrations with Semantic Observations
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:245-255
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Scalable Reinforcement Learning of Localized Policies for Multi-Agent Networked Systems
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:256-266
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Black-box continuous-time transfer function estimation with stability guarantees: a kernel-based approach
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:267-276
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Model-Predictive Control via Cross-Entropy and Gradient-Based Optimization
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:277-286
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Learning the Globally Optimal Distributed LQ Regulator
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:287-297
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VarNet: Variational Neural Networks for the Solution of Partial Differential Equations
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:298-307
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Tractable Reinforcement Learning of Signal Temporal Logic Objectives
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:308-317
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A Spatially and Temporally Attentive Joint Trajectory Prediction Framework for Modeling Vessel Intent
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:318-327
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Structured Mechanical Models for Robot Learning and Control
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:328-337
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Data-driven Identification of Approximate Passive Linear Models for Nonlinear Systems
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:338-339
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Constraint Management for Batch Processes Using Iterative Learning Control and Reference Governors
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:340-349
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Robust Guarantees for Perception-Based Control
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:350-360
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Learning Convex Optimization Control Policies
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:361-373
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Fitting a Linear Control Policy to Demonstrations with a Kalman Constraint
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:374-383
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Universal Simulation of Stable Dynamical Systems by Recurrent Neural Nets
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:384-392
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Contracting Implicit Recurrent Neural Networks: Stable Models with Improved Trainability
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:393-403
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On the Robustness of Data-Driven Controllers for Linear Systems
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:404-412
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Faster saddle-point optimization for solving large-scale Markov decision processes
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:413-423
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On Simulation and Trajectory Prediction with Gaussian Process Dynamics
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:424-434
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Sample Complexity of Kalman Filtering for Unknown Systems
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:435-444
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NeurOpt: Neural network based optimization for building energy management and climate control
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:445-454
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Bayesian model predictive control: Efficient model exploration and regret bounds using posterior sampling
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:455-464
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Parameter Optimization for Learning-based Control of Control-Affine Systems
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:465-475
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Riccati updates for online linear quadratic control
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:476-485
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A Theoretical Analysis of Deep Q-Learning
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:486-489
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Localized active learning of Gaussian process state space models
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:490-499
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Generating Robust Supervision for Learning-Based Visual Navigation Using Hamilton-Jacobi Reachability
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:500-510
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Learning supported Model Predictive Control for Tracking of Periodic References
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:511-520
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Data-driven distributionally robust LQR with multiplicative noise
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:521-530
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Learning the model-free linear quadratic regulator via random search
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:531-539
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Lambda-Policy Iteration with Randomization for Contractive Models with Infinite Policies: Well-Posedness and Convergence
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:540-549
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Optimistic robust linear quadratic dual control
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:550-560
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Bayesian Learning with Adaptive Load Allocation Strategies
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:561-570
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Learning-based Stochastic Model Predictive Control with State-Dependent Uncertainty
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:571-580
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Stable Reinforcement Learning with Unbounded State Space
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:581-581
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Periodic Q-Learning
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:582-598
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Robust Learning-Based Control via Bootstrapped Multiplicative Noise
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:599-607
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Robust Regression for Safe Exploration in Control
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:608-619
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Constrained Upper Confidence Reinforcement Learning
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:620-629
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Euclideanizing Flows: Diffeomorphic Reduction for Learning Stable Dynamical Systems
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:630-639
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Planning from Images with Deep Latent Gaussian Process Dynamics
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:640-650
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A First Principles Approach for Data-Efficient System Identification of Spring-Rod Systems via Differentiable Physics Engines
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:651-665
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Model-Based Reinforcement Learning with Value-Targeted Regression
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:666-686
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Localized Learning of Robust Controllers for Networked Systems with Dynamic Topology
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:687-696
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NeuralExplorer: State Space Exploration of Closed Loop Control Systems Using Neural Networks
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:697-697
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Toward fusion plasma scenario planning for NSTX-U using machine-learning-accelerated models
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:698-707
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Learning for Safety-Critical Control with Control Barrier Functions
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:708-717
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Learning Dynamical Systems with Side Information
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:718-727
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Feynman-Kac Neural Network Architectures for Stochastic Control Using Second-Order FBSDE Theory
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:728-738
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Hamilton-Jacobi-Bellman Equations for Q-Learning in Continuous Time
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:739-748
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Identifying Mechanical Models of Unknown Objects with Differentiable Physics Simulations
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:749-760
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Objective Mismatch in Model-based Reinforcement Learning
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:761-770
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Tools for Data-driven Modeling of Within-Hand Manipulation with Underactuated Adaptive Hands
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:771-780
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Probabilistic Safety Constraints for Learned High Relative Degree System Dynamics
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:781-792
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Lyceum: An efficient and scalable ecosystem for robot learning
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:793-803
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Encoding Physical Constraints in Differentiable Newton-Euler Algorithm
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:804-813
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Distributed Reinforcement Learning for Decentralized Linear Quadratic Control: A Derivative-Free Policy Optimization Approach
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:814-814
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Learning to Plan via Deep Optimistic Value Exploration
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:815-825
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L1-GP: L1 Adaptive Control with Bayesian Learning
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:826-837
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Data-Driven Distributed Predictive Control via Network Optimization
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:838-839
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Information Theoretic Model Predictive Q-Learning
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:840-850
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Learning nonlinear dynamical systems from a single trajectory
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:851-861
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A Duality Approach for Regret Minimization in Average-Award Ergodic Markov Decision Processes
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:862-883
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Robust Deep Learning as Optimal Control: Insights and Convergence Guarantees
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:884-893
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Dual Stochastic MPC for Systems with Parametric and Structural Uncertainty
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:894-903
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Hierarchical Decomposition of Nonlinear Dynamics and Control for System Identification and Policy Distillation
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:904-914
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A Kernel Mean Embedding Approach to Reducing Conservativeness in Stochastic Programming and Control
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:915-923
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Efficient Large-Scale Gaussian Process Bandits by Believing only Informative Actions
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:924-934
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Plan2Vec: Unsupervised Representation Learning by Latent Plans
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:935-946
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Policy Learning of MDPs with Mixed Continuous/Discrete Variables: A Case Study on Model-Free Control of Markovian Jump Systems
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:947-957
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Improving Robustness via Risk Averse Distributional Reinforcement Learning
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:958-968
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Keyframing the Future: Keyframe Discovery for Visual Prediction and Planning
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:969-979
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Safe non-smooth black-box optimization with application to policy search
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:980-989
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Improving Input-Output Linearizing Controllers for Bipedal Robots via Reinforcement Learning
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:990-999
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Uncertain multi-agent MILPs: A data-driven decentralized solution with probabilistic feasibility guarantees
; Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:1000-1009
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