default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCID4th L4DC 2022: Stanford University, CA, USA
- Roya Firoozi, Negar Mehr, Esen Yel, Rika Antonova, Jeannette Bohg, Mac Schwager, Mykel J. Kochenderfer:
Learning for Dynamics and Control Conference, L4DC 2022, 23-24 June 2022, Stanford University, Stanford, CA, USA. Proceedings of Machine Learning Research 168, PMLR 2022 - Preface. 1-7
- Daniel Jung:
Automated Design of Grey-Box Recurrent Neural Networks For Fault Diagnosis using Structural Models and Causal Information. 8-20 - Ting-Han Fan, Xian Yeow Lee, Yubo Wang:
PowerGym: A Reinforcement Learning Environment for Volt-Var Control in Power Distribution Systems. 21-33 - Abhishek Cauligi, Ankush Chakrabarty, Stefano Di Cairano, Rien Quirynen:
PRISM: Recurrent Neural Networks and Presolve Methods for Fast Mixed-integer Optimal Control. 34-46 - Anirudh Vemula, Wen Sun, Maxim Likhachev, J. Andrew Bagnell:
On the Effectiveness of Iterative Learning Control. 47-58 - Steven D. Morad
, Stephan Liwicki, Ryan Kortvelesy, Roberto Mecca, Amanda Prorok:
Modeling Partially Observable Systems using Graph-Based Memory and Topological Priors. 59-73 - Andrea Sassella, Valentina Breschi, Simone Formentin:
Noise Handling in Data-driven Predictive Control: A Strategy Based on Dynamic Mode Decomposition. 74-85 - Olle Kjellqvist, Anders Rantzer:
Learning-Enabled Robust Control with Noisy Measurements. 86-96 - Haitong Ma, Changliu Liu, Shengbo Eben Li, Sifa Zheng, Jianyu Chen:
Joint Synthesis of Safety Certificate and Safe Control Policy Using Constrained Reinforcement Learning. 97-109 - Samarth Sinha, Jiaming Song, Animesh Garg, Stefano Ermon:
Experience Replay with Likelihood-free Importance Weights. 110-123 - Baris Kayalibay, Atanas Mirchev, Patrick van der Smagt, Justin Bayer:
Tracking and Planning with Spatial World Models. 124-137 - Nicola Bastianello, Andrea Simonetto, Emiliano Dall'Anese:
OpReg-Boost: Learning to Accelerate Online Algorithms with Operator Regression. 138-152 - Simon Muntwiler, Kim Peter Wabersich, Melanie N. Zeilinger:
Learning-based Moving Horizon Estimation through Differentiable Convex Optimization Layers. 153-165 - Yuda Song, Ye Yuan, Wen Sun, Kris Kitani:
Online No-regret Model-Based Meta RL for Personalized Navigation. 166-179 - Stephen Tu, Alexander Robey, Tingnan Zhang, Nikolai Matni:
On the Sample Complexity of Stability Constrained Imitation Learning. 180-191 - Thinh T. Doan:
Convergence Rates of Two-Time-Scale Gradient Descent-Ascent Dynamics for Solving Nonconvex Min-Max Problems. 192-206 - Brendon G. Anderson, Somayeh Sojoudi:
Certified Robustness via Locally Biased Randomized Smoothing. 207-220 - Henk van Waarde, Rodolphe Sepulchre:
Training Lipschitz Continuous Operators Using Reproducing Kernels. 221-233 - Liliaokeawawa Cothren, Gianluca Bianchin, Emiliano Dall'Anese:
Data-Enabled Gradient Flow as Feedback Controller: Regulation of Linear Dynamical Systems to Minimizers of Unknown Functions. 234-247 - Cameron R. Wolfe, Anastasios Kyrillidis:
i-SpaSP: Structured Neural Pruning via Sparse Signal Recovery. 248-262 - Franck Djeumou, Cyrus Neary, Eric Goubault, Sylvie Putot, Ufuk Topcu:
Neural Networks with Physics-Informed Architectures and Constraints for Dynamical Systems Modeling. 263-277 - Siliang Zeng, Tianyi Chen, Alfredo García, Mingyi Hong:
Learning to Coordinate in Multi-Agent Systems: A Coordinated Actor-Critic Algorithm and Finite-Time Guarantees. 278-290 - Samuel Pfrommer, Tanmay Gautam, Alec Zhou, Somayeh Sojoudi:
Safe Reinforcement Learning with Chance-constrained Model Predictive Control. 291-303 - Yansong Li, Shuo Han:
Accelerating Model-Free Policy Optimization Using Model-Based Gradient: A Composite Optimization Perspective. 304-315 - Miguel Jaques, Martin Asenov, Michael Burke, Timothy M. Hospedales:
Vision-based System Identification and 3D Keypoint Discovery using Dynamics Constraints. 316-329 - Yujie Yang, Jianyu Chen, Shengbo Li:
Learning POMDP Models with Similarity Space Regularization: a Linear Gaussian Case Study. 330-341 - Yuanhanqing Huang, Jianghai Hu:
Distributed Stochastic Nash Equilibrium Learning in Locally Coupled Network Games with Unknown Parameters. 342-354 - Samuel Low, Mykel J. Kochenderfer:
Optimal Pointing Sequences in Spacecraft Formation Flying Using Online Planning with Resource Constraints. 355-365 - Krista Longi, Jakob Lindinger, Olaf Duennbier, Melih Kandemir, Arto Klami, Barbara Rakitsch:
Traversing Time with Multi-Resolution Gaussian Process State-Space Models. 366-377 - Yifeng Jiang, Jiazheng Sun, C. Karen Liu:
Data-Augmented Contact Model for Rigid Body Simulation. 378-390 - Jingrong Wang, Ben Liang:
Gradient and Projection Free Distributed Online Min-Max Resource Optimization. 391-403 - Gautam Goel, Babak Hassibi:
Online Estimation and Control with Optimal Pathlength Regret. 404-414 - Ce Xu Zheng, Adrià Colomé, Luis Sentis, Carme Torras:
Mixtures of Controlled Gaussian Processes for Dynamical Modeling of Deformable Objects. 415-426 - Han Wang, James Anderson:
Learning Linear Models Using Distributed Iterative Hessian Sketching. 427-440 - Ali Salamati, Majid Zamani:
Data-Driven Safety Verification of Stochastic Systems via Barrier Certificates: A Wait-and-Judge Approach. 441-452 - Franck Djeumou, Ufuk Topcu:
Learning to Reach, Swim, Walk and Fly in One Trial: Data-Driven Control with Scarce Data and Side Information. 453-466 - Feiran Zhao, Xingchen Li, Keyou You:
Data-driven Control of Unknown Linear Systems via Quantized Feedback. 467-479 - Rel Guzman Apaza, Rafael Oliveira, Fabio Ramos:
Adaptive Model Predictive Control by Learning Classifiers. 480-491 - Vittorio Caggiano, Huawei Wang, Guillaume Durandau, Massimo Sartori, Vikash Kumar:
MyoSuite: A Contact-rich Simulation Suite for Musculoskeletal Motor Control. 492-507 - Weiming Zhi, Tin Lai, Lionel Ott, Fabio Ramos:
Diffeomorphic Transforms for Generalised Imitation Learning. 508-519 - Santiago Sanchez-Escalonilla Plaza, Rodolfo Reyes-Báez, Bayu Jayawardhana:
Total Energy Shaping with Neural Interconnection and Damping Assignment - Passivity Based Control. 520-531 - Thomas T. C. K. Zhang, Stephen Tu, Nicholas M. Boffi, Jean-Jacques E. Slotine, Nikolai Matni:
Adversarially Robust Stability Certificates can be Sample-Efficient. 532-545 - Harish S. Bhat, Kevin Collins, Prachi Gupta, Christine M. Isborn:
Dynamic Learning of Correlation Potentials for a Time-Dependent Kohn-Sham System. 546-558 - Agustin Castellano, Hancheng Min, Enrique Mallada, Juan Andrés Bazerque:
Reinforcement Learning with Almost Sure Constraints. 559-570 - Luca Furieri, Clara Lucía Galimberti, Muhammad Zakwan, Giancarlo Ferrari-Trecate:
Distributed Neural Network Control with Dependability Guarantees: a Compositional Port-Hamiltonian Approach. 571-583 - Saul Santos, Monica Ekal, Rodrigo M. M. Ventura:
Symplectic Momentum Neural Networks - Using Discrete Variational Mechanics as a prior in Deep Learning. 584-595 - Charis J. Stamouli, Anastasios Tsiamis, Manfred Morari, George J. Pappas:
Adaptive Stochastic MPC under Unknown Noise Distribution. 596-607 - Shagun Sodhani, Franziska Meier, Joelle Pineau, Amy Zhang:
Block Contextual MDPs for Continual Learning. 608-623 - Rameez Wajid, Asad Ullah Awan, Majid Zamani:
Formal Synthesis of Safety Controllers for Unknown Stochastic Control Systems using Gaussian Process Learning. 624-636 - Nima Eshraghi, Ben Liang:
Improving Dynamic Regret in Distributed Online Mirror Descent Using Primal and Dual Information. 637-649 - Benjamin Gravell, Iman Shames, Tyler H. Summers:
Robust Data-Driven Output Feedback Control via Bootstrapped Multiplicative Noise. 650-662 - Alan Yang, Jie Xiong, Maxim Raginsky, Elyse Rosenbaum:
Input-to-State Stable Neural Ordinary Differential Equations with Applications to Transient Modeling of Circuits. 663-675 - Rahul Singh, Keuntaek Lee, Yongxin Chen:
Sample-based Distributional Policy Gradient. 676-688 - Zhe Du, Necmiye Ozay, Laura Balzano:
Clustering-based Mode Reduction for Markov Jump Systems. 689-701 - Marcos M. Vasconcelos:
Learning Distributed Channel Access Policies for Networked Estimation: Data-driven Optimization in the Mean-field Regime. 702-712 - Amir Khazraei, Henry D. Pfister, Miroslav Pajic:
Resiliency of Perception-Based Controllers Against Attacks. 713-725 - Andrea Martin, Luca Furieri, Florian Dörfler, John Lygeros, Giancarlo Ferrari-Trecate:
Safe Control with Minimal Regret. 726-738 - Tianhao Wei, Changliu Liu:
Safe Control with Neural Network Dynamic Models. 739-750 - Ningyuan Zhang, Wenliang Liu, Calin Belta:
Distributed Control using Reinforcement Learning with Temporal-Logic-Based Reward Shaping. 751-762 - Ameneh Nejati, Bingzhuo Zhong, Marco Caccamo, Majid Zamani:
Data-Driven Controller Synthesis of Unknown Nonlinear Polynomial Systems via Control Barrier Certificates. 763-776 - Zihao Zhou, Xingyi Yang, Ryan A. Rossi, Handong Zhao, Rose Yu:
Neural Point Process for Learning Spatiotemporal Event Dynamics. 777-789 - Adam J. Thorpe, Thomas Lew, Meeko Oishi, Marco Pavone:
Data-Driven Chance Constrained Control using Kernel Distribution Embeddings. 790-802 - Samuel Chevalier, Jochen Stiasny, Spyros Chatzivasileiadis:
Accelerating Dynamical System Simulations with Contracting and Physics-Projected Neural-Newton Solvers. 803-816 - Ross Drummond, Stephen Duncan, Mathew Turner, Patricia Pauli, Frank Allgöwer:
Bounding the Difference Between Model Predictive Control and Neural Networks. 817-829 - Milad Farsi, Yinan Li, Ye Yuan, Jun Liu:
A Piecewise Learning Framework for Control of Unknown Nonlinear Systems with Stability Guarantees. 830-843 - Zhigen Zhao, Simiao Zuo, Tuo Zhao, Ye Zhao:
Adversarially Regularized Policy Learning Guided by Trajectory Optimization. 844-857 - Horia Mania, Ali Jadbabaie, Devavrat Shah, Suvrit Sra:
Time Varying Regression with Hidden Linear Dynamics. 858-869 - Daniel Gurevich, Debdipta Goswami, Charles L. Fefferman, Clarence W. Rowley:
Optimal Control with Learning on the Fly: System with Unknown Drift. 870-880 - Lukas Brunke, Siqi Zhou, Angela P. Schoellig:
Barrier Bayesian Linear Regression: Online Learning of Control Barrier Conditions for Safety-Critical Control of Uncertain Systems. 881-892 - Yuchen Cui, Scott Niekum, Abhinav Gupta, Vikash Kumar, Aravind Rajeswaran:
Can Foundation Models Perform Zero-Shot Task Specification For Robot Manipulation? 893-905 - Riccardo Valperga, Kevin Webster, Dmitry Turaev, Victoria Klein, Jeroen S. W. Lamb:
Learning Reversible Symplectic Dynamics. 906-916 - Saber Jafarpour, Matthew Abate, Alexander Davydov, Francesco Bullo, Samuel Coogan:
Robustness Certificates for Implicit Neural Networks: A Mixed Monotone Contractive Approach. 917-930 - Julian Viereck, Avadesh Meduri, Ludovic Righetti:
ValueNetQP: Learned One-step Optimal Control for Legged Locomotion. 931-942 - Yifei Zhang, Sourav Kumar Ukil, Ephraim Neimand, Serban Sabau, Myron E. Hohil:
Sample Complexity of the Robust LQG Regulator with Coprime Factors Uncertainty. 943-953 - Ryan Sander, Wilko Schwarting, Tim Seyde, Igor Gilitschenski, Sertac Karaman, Daniela Rus:
Neighborhood Mixup Experience Replay: Local Convex Interpolation for Improved Sample Efficiency in Continuous Control Tasks. 954-967 - Suhail Alsalehi, Erfan Aasi, Ron Weiss, Calin Belta:
Learning Spatio-Temporal Specifications for Dynamical Systems. 968-980 - Zhichao Li, Thai Duong, Nikolay Atanasov:
Safe Autonomous Navigation for Systems with Learned SE(3) Hamiltonian Dynamics. 981-993 - Muhammed O. Sayin, K. Alperen Cetiner:
On the Heterogeneity of Independent Learning Dynamics in Zero-sum Stochastic Games. 994-1005 - Jose Luis Vazquez Espinoza, Alexander Liniger, Wilko Schwarting, Daniela Rus, Luc Van Gool:
Deep Interactive Motion Prediction and Planning: Playing Games with Motion Prediction Models. 1006-1019 - Ryan K. Cosner, Maegan Tucker, Andrew J. Taylor, Kejun Li, Tamás G. Molnár, Wyatt Ubellacker, Anil Alan, Gábor Orosz, Yisong Yue, Aaron D. Ames:
Safety-Aware Preference-Based Learning for Safety-Critical Control. 1020-1033 - Junhyung Lyle Kim, Panos Toulis, Anastasios Kyrillidis:
Convergence and Stability of the Stochastic Proximal Point Algorithm with Momentum. 1034-1047 - Francesco De Lellis, Marco Coraggio, Giovanni Russo, Mirco Musolesi, Mario di Bernardo:
Control-Tutored Reinforcement Learning: Towards the Integration of Data-Driven and Model-Based Control. 1048-1059 - Ivan Dario Jimenez Rodriguez, Noel Csomay-Shanklin, Yisong Yue, Aaron D. Ames:
Neural Gaits: Learning Bipedal Locomotion via Control Barrier Functions and Zero Dynamics Policies. 1060-1072 - Raghu Arghal, Eric Lei, Shirin Saeedi Bidokhti:
Robust Graph Neural Networks via Probabilistic Lipschitz Constraints. 1073-1085 - Thomas Lew, Lucas Janson, Riccardo Bonalli, Marco Pavone:
A Simple and Efficient Sampling-based Algorithm for General Reachability Analysis. 1086-1099 - Felipe Galarza-Jimenez, Jorge Poveda, Emiliano Dall'Anese:
Sliding-Seeking Control: Model-Free Optimization with Safety Constraints. 1100-1111 - Bibit Bianchini, Mathew Halm, Nikolai Matni, Michael Posa:
Generalization Bounded Implicit Learning of Nearly Discontinuous Functions. 1112-1124 - Brett Thomas Lopez, Jean-Jacques E. Slotine:
Adaptive Variants of Optimal Feedback Policies. 1125-1136 - Wanxin Jin, Alp Aydinoglu, Mathew Halm, Michael Posa:
Learning Linear Complementarity Systems. 1137-1149 - Jan Brüdigam, Martin Schuck, Alexandre Capone, Stefan Sosnowski, Sandra Hirche:
Structure-Preserving Learning Using Gaussian Processes and Variational Integrators. 1150-1162 - Udaya Ghai, Xinyi Chen, Elad Hazan, Alexandre Megretski:
Robust Online Control with Model Misspecification. 1163-1175
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 2025-03-24 00:13 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:
