default search action
3rd L4DC 2021: Virtual Event, Switzerland
- Ali Jadbabaie, John Lygeros, George J. Pappas, Pablo A. Parrilo, Benjamin Recht, Claire J. Tomlin, Melanie N. Zeilinger:
Proceedings of the 3rd Annual Conference on Learning for Dynamics and Control, L4DC 2021, 7-8 June 2021, Virtual Event, Switzerland. Proceedings of Machine Learning Research 144, PMLR 2021 - Ali Jadbabaie, John Lygeros, George J. Pappas, Pablo A. Parrilo, Benjamin Recht, Claire J. Tomlin, Melanie N. Zeilinger:
Preface. 1-5 - Brandon Amos, Samuel Stanton, Denis Yarats, Andrew Gordon Wilson:
On the model-based stochastic value gradient for continuous reinforcement learning. 6-20 - Anoopkumar Sonar, Vincent Pacelli, Anirudha Majumdar:
Invariant Policy Optimization: Towards Stronger Generalization in Reinforcement Learning. 21-33 - Matthieu Barreau, John Liu, Karl Henrik Johansson:
Learning-based State Reconstruction for a Scalar Hyperbolic PDE under noisy Lagrangian Sensing. 34-46 - Thinh T. Doan:
Nonlinear Two-Time-Scale Stochastic Approximation: Convergence and Finite-Time Performance. 47 - Peng Zhao, Lijun Zhang:
Improved Analysis for Dynamic Regret of Strongly Convex and Smooth Functions. 48-59 - Salar Fattahi:
Learning Partially Observed Linear Dynamical Systems from Logarithmic Number of Samples. 60-72 - Kei Akuzawa, Yusuke Iwasawa, Yutaka Matsuo:
Estimating Disentangled Belief about Hidden State and Hidden Task for Meta-Reinforcement Learning. 73-86 - Laura Ferrarotti, Valentina Breschi, Alberto Bemporad:
The benefits of sharing: a cloud-aided performance-driven framework to learn optimal feedback policies. 87-98 - Andrea Sassella
, Valentina Breschi, Simone Formentin:
Data-driven design of switching reference governors for brake-by-wire applications. 99-110 - Fernando Gama, Somayeh Sojoudi:
Graph Neural Networks for Distributed Linear-Quadratic Control. 111-124 - Meghan Booker, Anirudha Majumdar:
Learning to Actively Reduce Memory Requirements for Robot Control Tasks. 125-137 - Liang Xu, Mustafa Sahin Turan, Baiwei Guo, Giancarlo Ferrari-Trecate:
Non-conservative Design of Robust Tracking Controllers Based on Input-output Data. 138-149 - Alexander Robey, Arman Adibi, Brent Schlotfeldt, Hamed Hassani, George J. Pappas:
Optimal Algorithms for Submodular Maximization with Distributed Constraints. 150-162 - Amr Alanwar, Anne Koch, Frank Allgöwer, Karl Henrik Johansson:
Data-Driven Reachability Analysis Using Matrix Zonotopes. 163-175 - Paul M. J. Van den Hof, Karthik Raghavan Ramaswamy:
Learning local modules in dynamic networks. 176-188 - Anton Xue, Nikolai Matni:
Data-Driven System Level Synthesis. 189-200 - Adam J. Thorpe, Kendric R. Ortiz, Meeko M. K. Oishi:
Learning Approximate Forward Reachable Sets Using Separating Kernels. 201-212 - Ingvar M. Ziemann, Henrik Sandberg:
On Uninformative Optimal Policies in Adaptive LQR with Unknown B-Matrix. 213-226 - Lukas P. Fröhlich, Melanie N. Zeilinger, Edgar D. Klenske:
Cautious Bayesian Optimization for Efficient and Scalable Policy Search. 227-240 - Gerben Beintema, Roland Tóth, Maarten Schoukens:
Nonlinear state-space identification using deep encoder networks. 241-250 - Felix Bünning, Adrian Schalbetter, Ahmed Aboudonia, Mathias Hudoba de Badyn, Philipp Heer, John Lygeros:
Input Convex Neural Networks for Building MPC. 251-262 - Benoît Legat, Raphaël M. Jungers, Jean Bouchat:
Abstraction-based branch and bound approach to Q-learning for hybrid optimal control. 263-274 - Clara Lucía Galimberti, Liang Xu, Giancarlo Ferrari-Trecate:
A unified framework for Hamiltonian deep neural networks. 275-286 - Nils Wieler, Julian Berberich, Anne Koch, Frank Allgöwer:
Data-Driven Controller Design via Finite-Horizon Dissipativity. 287-298 - Lorenz Dörschel, David Stenger, Dirk Abel:
Safe Bayesian Optimisation for Controller Design by Utilising the Parameter Space Approach. 299-311 - Licio Romao, Kostas Margellos, Antonis Papachristodoulou:
Tight sampling and discarding bounds for scenario programs with an arbitrary number of removed samples. 312-323 - Alexander von Rohr, Matthias Neumann-Brosig
Probabilistic robust linear quadratic regulators with Gaussian processes. 324-335 - Liyuan Zheng, Yuanyuan Shi, Lillian J. Ratliff, Baosen Zhang:
Safe Reinforcement Learning of Control-Affine Systems with Vertex Networks. 336-347 - Rika Antonova, Anastasiia Varava, Peiyang Shi, J. Frederico Carvalho, Danica Kragic:
Sequential Topological Representations for Predictive Models of Deformable Objects. 348-360 - Jiaqi Li, Ross Drummond, Stephen R. Duncan:
Robust error bounds for quantised and pruned neural networks. 361-372 - Siddhartha Satpathi, Rayadurgam Srikant:
The Dynamics of Gradient Descent for Overparametrized Neural Networks. 373-384 - Rui Wang, Danielle C. Maddix, Christos Faloutsos, Yuyang Wang, Rose Yu:
Bridging Physics-based and Data-driven modeling for Learning Dynamical Systems. 385-398 - Sarah Dean, Benjamin Recht:
Certainty Equivalent Perception-Based Control. 399-411 - Mathieu Granzotto, Romain Postoyan, Dragan Nesic, Lucian Busoniu, Jamal Daafouz:
When to stop value iteration: stability and near-optimality versus computation. 412-424 - Joshua Hanson, Maxim Raginsky, Eduardo D. Sontag:
Learning Recurrent Neural Net Models of Nonlinear Systems. 425-435 - Mario Sznaier:
A Data Driven, Convex Optimization Approach to Learning Koopman Operators. 436-446 - Kushal Chakrabarti, Nirupam Gupta, Nikhil Chopra:
Accelerating Distributed SGD for Linear Regression using Iterative Pre-Conditioning. 447-458 - Arash Mehrjou, Mohammad Ghavamzadeh, Bernhard Schölkopf:
Neural Lyapunov Redesign. 459-470 - Nicholas M. Boffi, Stephen Tu, Jean-Jacques E. Slotine:
Regret Bounds for Adaptive Nonlinear Control. 471-483 - Junchi Liang, Abdeslam Boularias:
Self-Supervised Learning of Long-Horizon Manipulation Tasks with Finite-State Task Machines. 484-497 - Amir Ali Ahmadi, Abraar Chaudhry, Vikas Sindhwani, Stephen Tu:
Safely Learning Dynamical Systems from Short Trajectories. 498-509 - Ziyi Wang, Oswin So, Keuntaek Lee, Evangelos A. Theodorou:
Adaptive Risk Sensitive Model Predictive Control with Stochastic Search. 510-522 - Ying Zhao Lian, Colin N. Jones:
Nonlinear Data-Enabled Prediction and Control. 523-534 - Ioannis Proimadis, Yorick Broens, Roland Tóth, Hans Butler:
Learning-based feedforward augmentation for steady state rejection of residual dynamics on a nanometer-accurate planar actuator system. 535-546 - James A. Preiss, Gaurav S. Sukhatme:
Suboptimal coverings for continuous spaces of control tasks. 547-558 - Yang Zheng, Luca Furieri, Maryam Kamgarpour, Na Li:
Sample Complexity of Linear Quadratic Gaussian (LQG) Control for Output Feedback Systems. 559-570 - Guillaume O. Berger, Raphaël M. Jungers, Zheming Wang:
Chance-constrained quasi-convex optimization with application to data-driven switched systems control. 571-583 - Christian Ebenbauer, Fabian Pfitz, Shuyou Yu:
Control of Unknown (Linear) Systems with Receding Horizon Learning. 584-596 - Jingwei Zhang, Zhuoran Yang, Zhengyuan Zhou, Zhaoran Wang:
Provably Sample Efficient Reinforcement Learning in Competitive Linear Quadratic Systems. 597-598 - Yujie Tang, Yang Zheng, Na Li:
Analysis of the Optimization Landscape of Linear Quadratic Gaussian (LQG) Control. 599-610 - Gabriella Pizzuto, Michael N. Mistry:
Physics-penalised Regularisation for Learning Dynamics Models with Contact. 611-622 - Armin Lederer, Alexandre Capone, Thomas Beckers, Jonas Umlauft, Sandra Hirche:
The Impact of Data on the Stability of Learning-Based Control. 623-635 - Joseph E. Gaudio, Anuradha M. Annaswamy, José M. Moreu, Michael A. Bolender, Travis E. Gibson:
Accelerated Learning with Robustness to Adversarial Regressors. 636-650 - Sahin Lale, Oguzhan Teke, Babak Hassibi, Anima Anandkumar:
Stability and Identification of Random Asynchronous Linear Time-Invariant Systems. 651-663 - Lenart Treven, Sebastian Curi, Mojmír Mutný, Andreas Krause:
Learning Stabilizing Controllers for Unstable Linear Quadratic Regulators from a Single Trajectory. 664-676 - Matteo Marchi, Bahman Gharesifard, Paulo Tabuada:
Training deep residual networks for uniform approximation guarantees. 677-688 - Naifu Zhang, Nicholas Capel:
LEOC: A Principled Method in Integrating Reinforcement Learning and Classical Control Theory. 689-701 - Feiran Zhao, Keyou You:
Primal-dual Learning for the Model-free Risk-constrained Linear Quadratic Regulator. 702-714 - Matthew Newton, Antonis Papachristodoulou:
Exploiting Sparsity for Neural Network Verification. 715-727 - Dawei Sun, Mohammad Javad Khojasteh, Shubhanshu Shekhar, Chuchu Fan:
Uncertain-aware Safe Exploratory Planning using Gaussian Process and Neural Control Contraction Metric. 728-741 - Guannan Qu, Yuanyuan Shi, Sahin Lale, Anima Anandkumar, Adam Wierman:
Stable Online Control of Linear Time-Varying Systems. 742-753 - Joshua Smith, Michael N. Mistry:
ARDL - A Library for Adaptive Robotic Dynamics Learning. 754-766 - Konstantinos Gatsis:
Linear Regression over Networks with Communication Guarantees. 767-778 - Junhyeok Ahn, Luis Sentis:
Nested Mixture of Experts: Cooperative and Competitive Learning of Hybrid Dynamical System. 779-790 - Chenyu Liu, Yan Zhang, Yi Shen, Michael M. Zavlanos:
Learning without Knowing: Unobserved Context in Continuous Transfer Reinforcement Learning. 791-802 - Anas Makdesi, Antoine Girard, Laurent Fribourg:
Data-Driven Abstraction of Monotone Systems. 803-814 - Akshay Mete, Rahul Singh, Xi Liu, P. R. Kumar:
Reward Biased Maximum Likelihood Estimation for Reinforcement Learning. 815-827 - Murad Abu-Khalaf, Sertac Karaman, Daniela Rus:
Feedback from Pixels: Output Regulation via Learning-based Scene View Synthesis. 828-841 - Navid Hashemi, Justin Ruths, Mahyar Fazlyab:
Certifying Incremental Quadratic Constraints for Neural Networks via Convex Optimization. 842-853 - Lintao Ye, Aritra Mitra, Shreyas Sundaram:
Near-Optimal Data Source Selection for Bayesian Learning. 854-865 - Daniel Esteban Ochoa, Jorge I. Poveda, Anantharam Subbaraman, Gerd S. Schmidt, Farshad R. Pour Safaei:
Accelerated Concurrent Learning Algorithms via Data-Driven Hybrid Dynamics and Nonsmooth ODEs. 866-878 - Anshuka Rangi, Mohammad Javad Khojasteh, Massimo Franceschetti:
Learning based attacks in Cyber Physical Systems: Exploration, Detection, and Control Cost trade-offs. 879-892 - Anders Rantzer:
Minimax Adaptive Control for a Finite Set of Linear Systems. 893-904 - Pierre-François Massiani, Steve Heim, Sebastian Trimpe:
On exploration requirements for learning safety constraints. 905-916 - Steven Wong, Lejun Jiang, Robin Walters, Tamás G. Molnár, Gábor Orosz, Rose Yu:
Traffic Forecasting using Vehicle-to-Vehicle Communication. 917-929 - Xunbi A. Ji, Tamás G. Molnár, Sergei S. Avedisov, Gábor Orosz:
Learning the Dynamics of Time Delay Systems with Trainable Delays. 930-942 - Signe Moe, Camilla Sterud:
Decoupling dynamics and sampling: RNNs for unevenly sampled data and flexible online predictions. 943-953 - Jingxi Xu, Bruce D. Lee, Nikolai Matni, Dinesh Jayaraman:
How Are Learned Perception-Based Controllers Impacted by the Limits of Robust Control? 954-966 - Sahin Lale, Kamyar Azizzadenesheli, Babak Hassibi, Anima Anandkumar:
Finite-time System Identification and Adaptive Control in Autoregressive Exogenous Systems. 967-979 - Elliott Skomski, Ján Drgona, Aaron Tuor:
Automating Discovery of Physics-Informed Neural State Space Models via Learning and Evolution. 980-991 - Patricia Pauli, Johannes Köhler, Julian Berberich, Anne Koch, Frank Allgöwer:
Offset-free setpoint tracking using neural network controllers. 992-1003 - Mingzhou Yin, Andrea Iannelli, Roy S. Smith:
Maximum Likelihood Signal Matrix Model for Data-Driven Predictive Control. 1004-1014 - Emilio Tanowe Maddalena, Paul Scharnhorst, Yuning Jiang, Colin N. Jones:
KPC: Learning-Based Model Predictive Control with Deterministic Guarantees. 1015-1026 - Aditya Gahlawat, Arun Lakshmanan, Lin Song, Andrew Patterson, Zhuohuan Wu, Naira Hovakimyan, Evangelos A. Theodorou:
Contraction ℒ1-Adaptive Control using Gaussian Processes. 1027-1040 - Noel Csomay-Shanklin, Ryan K. Cosner, Min Dai, Andrew J. Taylor, Aaron D. Ames:
Episodic Learning for Safe Bipedal Locomotion with Control Barrier Functions and Projection-to-State Safety. 1041-1053 - Samuel K. Ainsworth, Kendall Lowrey, John Thickstun, Zaïd Harchaoui, Siddhartha S. Srinivasa:
Faster Policy Learning with Continuous-Time Gradients. 1054-1067 - Hotae Lee, Monimoy Bujarbaruah, Francesco Borrelli:
Learning How to Solve "Bubble Ball". 1068-1079 - Benjamin Gravell, Iman Shames, Tyler H. Summers:
Approximate Midpoint Policy Iteration for Linear Quadratic Control. 1080-1092 - Yutong Li, Nan Li, H. Eric Tseng, Anouck Girard, Dimitar P. Filev, Ilya V. Kolmanovsky:
Safe Reinforcement Learning Using Robust Action Governor. 1093-1104 - Benoit Landry, Hongkai Dai, Marco Pavone:
SEAGuL: Sample Efficient Adversarially Guided Learning of Value Functions. 1105-1117 - Simone Totaro, Anders Jonsson:
Fast Stochastic Kalman Gradient Descent for Reinforcement Learning. 1118-1129 - Sean J. Wang, Aaron M. Johnson:
Domain Adaptation Using System Invariant Dynamics Models. 1130-1141 - Aaron J. Havens, Girish Chowdhary:
Forced Variational Integrator Networks for Prediction and Control of Mechanical Systems. 1142-1153 - Rafael Rafailov, Tianhe Yu, Aravind Rajeswaran, Chelsea Finn:
Offline Reinforcement Learning from Images with Latent Space Models. 1154-1168 - Dhruva Kartik, Neeraj Sood, Urbashi Mitra, Tara Javidi
Adaptive Sampling for Estimating Distributions: A Bayesian Upper Confidence Bound Approach. 1169-1179 - Nicholas Galioto, Alex Arkady Gorodetsky:
A New Objective for Identification of Partially Observed Linear Time-Invariant Dynamical Systems from Input-Output Data. 1180-1191 - Udaya Ghai, David Snyder, Anirudha Majumdar, Elad Hazan:
Generating Adversarial Disturbances for Controller Verification. 1192-1204 - Avik Jain, Lawrence Chan, Daniel S. Brown, Anca D. Dragan:
Optimal Cost Design for Model Predictive Control. 1205-1217 - Yaofeng Desmond Zhong, Biswadip Dey, Amit Chakraborty:
Benchmarking Energy-Conserving Neural Networks for Learning Dynamics from Data. 1218-1229 - Siddharth Karamcheti, Albert J. Zhai, Dylan P. Losey, Dorsa Sadigh:
Learning Visually Guided Latent Actions for Assistive Teleoperation. 1230-1241 - Jing Yu, Clement Gehring, Florian Schäfer
Robust Reinforcement Learning: A Constrained Game-theoretic Approach. 1242-1254 - Yassine Nemmour, Bernhard Schölkopf, Jia-Jie Zhu:
Approximate Distributionally Robust Nonlinear Optimization with Application to Model Predictive Control: A Functional Approach. 1255-1269 - Gautam Goel, Babak Hassibi:
Regret-optimal measurement-feedback control. 1270-1280 - Mohammad Khosravi:
Learning Finite-Dimensional Representations For Koopman Operators. 1281
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
last updated on 2024-11-15 19:19 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by: