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Volume 144: Learning for Dynamics and Control, 7-8 June 2021, The Cloud
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Editors: Ali Jadbabaie, John Lygeros, George J. Pappas, Pablo A. Parrilo, Benjamin Recht, Claire J. Tomlin, Melanie N. Zeilinger
Preface
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:1-5
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On the Model-Based Stochastic Value Gradient for Continuous Reinforcement Learning
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:6-20
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Invariant Policy Optimization: Towards Stronger Generalization in Reinforcement Learning
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:21-33
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Learning-based State Reconstruction for a Scalar Hyperbolic PDE under noisy Lagrangian Sensing
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:34-46
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Nonlinear Two-Time-Scale Stochastic Approximation: Convergence and Finite-Time Performance
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:47-47
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Improved Analysis for Dynamic Regret of Strongly Convex and Smooth Functions
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:48-59
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Learning Partially Observed Linear Dynamical Systems from Logarithmic Number of Samples
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:60-72
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Estimating Disentangled Belief about Hidden State and Hidden Task for Meta-Reinforcement Learning
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:73-86
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The benefits of sharing: a cloud-aided performance-driven framework to learn optimal feedback policies
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:87-98
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Data-driven design of switching reference governors for brake-by-wire applications
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:99-110
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Graph Neural Networks for Distributed Linear-Quadratic Control
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:111-124
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Learning to Actively Reduce Memory Requirements for Robot Control Tasks
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:125-137
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Non-conservative Design of Robust Tracking Controllers Based on Input-output Data
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:138-149
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Optimal Algorithms for Submodular Maximization with Distributed Constraints
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:150-162
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Data-Driven Reachability Analysis Using Matrix Zonotopes
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:163-175
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Learning local modules in dynamic networks
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:176-188
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Data-Driven System Level Synthesis
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:189-200
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Learning Approximate Forward Reachable Sets Using Separating Kernels
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:201-212
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On Uninformative Optimal Policies in Adaptive LQR with Unknown B-Matrix
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:213-226
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Cautious Bayesian Optimization for Efficient and Scalable Policy Search
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:227-240
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Nonlinear state-space identification using deep encoder networks
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:241-250
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Input Convex Neural Networks for Building MPC
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:251-262
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Abstraction-based branch and bound approach to Q-learning for hybrid optimal control
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:263-274
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A unified framework for Hamiltonian deep neural networks
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:275-286
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Data-Driven Controller Design via Finite-Horizon Dissipativity
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:287-298
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Safe Bayesian Optimisation for Controller Design by Utilising the Parameter Space Approach
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:299-311
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Tight sampling and discarding bounds for scenario programs with an arbitrary number of removed samples
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:312-323
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Probabilistic robust linear quadratic regulators with Gaussian processes
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:324-335
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Safe Reinforcement Learning of Control-Affine Systems with Vertex Networks
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:336-347
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Sequential Topological Representations for Predictive Models of Deformable Objects
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:348-360
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Robust error bounds for quantised and pruned neural networks
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:361-372
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The Dynamics of Gradient Descent for Overparametrized Neural Networks
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:373-384
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Bridging Physics-based and Data-driven modeling for Learning Dynamical Systems
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:385-398
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Certainty Equivalent Perception-Based Control
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:399-411
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When to stop value iteration: stability and near-optimality versus computation
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:412-424
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Learning Recurrent Neural Net Models of Nonlinear Systems
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:425-435
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A Data Driven, Convex Optimization Approach to Learning Koopman Operators
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:436-446
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Accelerating Distributed SGD for Linear Regression using Iterative Pre-Conditioning
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:447-458
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Neural Lyapunov Redesign
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:459-470
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Regret Bounds for Adaptive Nonlinear Control
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:471-483
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Self-Supervised Learning of Long-Horizon Manipulation Tasks with Finite-State Task Machines
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:484-497
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Safely Learning Dynamical Systems from Short Trajectories
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:498-509
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Adaptive Risk Sensitive Model Predictive Control with Stochastic Search
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:510-522
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Nonlinear Data-Enabled Prediction and Control
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:523-534
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Learning-based feedforward augmentation for steady state rejection of residual dynamics on a nanometer-accurate planar actuator system
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:535-546
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Suboptimal coverings for continuous spaces of control tasks
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:547-558
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Sample Complexity of Linear Quadratic Gaussian (LQG) Control for Output Feedback Systems
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:559-570
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Chance-constrained quasi-convex optimization with application to data-driven switched systems control
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:571-583
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Control of Unknown (Linear) Systems with Receding Horizon Learning
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:584-596
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Provably Sample Efficient Reinforcement Learning in Competitive Linear Quadratic Systems
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:597-598
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Analysis of the Optimization Landscape of Linear Quadratic Gaussian (LQG) Control
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:599-610
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Physics-penalised Regularisation for Learning Dynamics Models with Contact
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:611-622
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The Impact of Data on the Stability of Learning-Based Control
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:623-635
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Accelerated Learning with Robustness to Adversarial Regressors
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:636-650
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Stability and Identification of Random Asynchronous Linear Time-Invariant Systems
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:651-663
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Learning Stabilizing Controllers for Unstable Linear Quadratic Regulators from a Single Trajectory
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:664-676
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Training deep residual networks for uniform approximation guarantees
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:677-688
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LEOC: A Principled Method in Integrating Reinforcement Learning and Classical Control Theory
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:689-701
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Primal-dual Learning for the Model-free Risk-constrained Linear Quadratic Regulator
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:702-714
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Exploiting Sparsity for Neural Network Verification
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:715-727
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Uncertain-aware Safe Exploratory Planning using Gaussian Process and Neural Control Contraction Metric
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:728-741
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Stable Online Control of Linear Time-Varying Systems
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:742-753
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ARDL - A Library for Adaptive Robotic Dynamics Learning
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:754-766
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Linear Regression over Networks with Communication Guarantees
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:767-778
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Nested Mixture of Experts: Cooperative and Competitive Learning of Hybrid Dynamical System
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:779-790
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Learning without Knowing: Unobserved Context in Continuous Transfer Reinforcement Learning
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:791-802
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Data-Driven Abstraction of Monotone Systems
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:803-814
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Reward Biased Maximum Likelihood Estimation for Reinforcement Learning
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:815-827
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Feedback from Pixels: Output Regulation via Learning-based Scene View Synthesis
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:828-841
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Certifying Incremental Quadratic Constraints for Neural Networks via Convex Optimization
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:842-853
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Near-Optimal Data Source Selection for Bayesian Learning
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:854-865
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Accelerated Concurrent Learning Algorithms via Data-Driven Hybrid Dynamics and Nonsmooth ODEs
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:866-878
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Learning based attacks in Cyber Physical Systems: Exploration, Detection, and Control Cost trade-offs
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:879-892
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Minimax Adaptive Control for a Finite Set of Linear Systems
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:893-904
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On exploration requirements for learning safety constraints
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:905-916
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Traffic Forecasting using Vehicle-to-Vehicle Communication
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:917-929
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Learning the Dynamics of Time Delay Systems with Trainable Delays
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:930-942
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Decoupling dynamics and sampling: RNNs for unevenly sampled data and flexible online predictions
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:943-953
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How Are Learned Perception-Based Controllers Impacted by the Limits of Robust Control?
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:954-966
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Finite-time System Identification and Adaptive Control in Autoregressive Exogenous Systems
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:967-979
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Automating Discovery of Physics-Informed Neural State Space Models via Learning and Evolution
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:980-991
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Offset-free setpoint tracking using neural network controllers
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:992-1003
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Maximum Likelihood Signal Matrix Model for Data-Driven Predictive Control
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:1004-1014
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KPC: Learning-Based Model Predictive Control with Deterministic Guarantees
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:1015-1026
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Contraction $\\mathcal{L}_1$-Adaptive Control using Gaussian Processes
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:1027-1040
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Episodic Learning for Safe Bipedal Locomotion with Control Barrier Functions and Projection-to-State Safety
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:1041-1053
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Faster Policy Learning with Continuous-Time Gradients
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:1054-1067
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Learning How to Solve “Bubble Ball”
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:1068-1079
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Approximate Midpoint Policy Iteration for Linear Quadratic Control
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:1080-1092
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Safe Reinforcement Learning Using Robust Action Governor
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:1093-1104
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SEAGuL: Sample Efficient Adversarially Guided Learning of Value Functions
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:1105-1117
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Fast Stochastic Kalman Gradient Descent for Reinforcement Learning
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:1118-1129
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Domain Adaptation Using System Invariant Dynamics Models
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:1130-1141
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Forced Variational Integrator Networks for Prediction and Control of Mechanical Systems
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:1142-1153
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Offline Reinforcement Learning from Images with Latent Space Models
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:1154-1168
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Adaptive Sampling for Estimating Distributions: A Bayesian Upper Confidence Bound Approach
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:1169-1179
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A New Objective for Identification of Partially Observed Linear Time-Invariant Dynamical Systems from Input-Output Data
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:1180-1191
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Generating Adversarial Disturbances for Controller Verification
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:1192-1204
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Optimal Cost Design for Model Predictive Control
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:1205-1217
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Benchmarking Energy-Conserving Neural Networks for Learning Dynamics from Data
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:1218-1229
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Learning Visually Guided Latent Actions for Assistive Teleoperation
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:1230-1241
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Robust Reinforcement Learning: A Constrained Game-theoretic Approach
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:1242-1254
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Approximate Distributionally Robust Nonlinear Optimization with Application to Model Predictive Control: A Functional Approach
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:1255-1269
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Regret-optimal measurement-feedback control
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:1270-1280
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Learning Finite-Dimensional Representations For Koopman Operators
Proceedings of the 3rd Conference on Learning for Dynamics and Control, PMLR 144:1281-1281
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