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GeezerVison is showing proceedings.mlr.press — Proceedings of Machine Learning Research [edit] Volume 211: Learning for Dynamics and Control Conference, 15-16 June 2023, Philadelphia, PA[edit] Editors: Nikolai Matni, Manfred Morari, George J. Pappas Filter Authors: Filter Titles: Learning on Manifolds: Universal Approximations Properties using Geometric Controllability Conditions for Neural ODEs Karthik Elamvazhuthi, Xuechen Zhang, Samet Oymak, Fabio Pasqualetti; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1-11 Interval Reachability of Nonlinear Dynamical Systems with Neural Network Controllers Saber Jafarpour, Akash Harapanahalli, Samuel Coogan; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:12-25 Physics-Informed Model-Based Reinforcement Learning Adithya Ramesh, Balaraman Ravindran; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:26-37 Learning-to-Learn to Guide Random Search: Derivative-Free Meta Blackbox Optimization on Manifold Bilgehan Sel, Ahmad Tawaha, Yuhao Ding, Ruoxi Jia, Bo Ji, Javad Lavaei, Ming Jin; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:38-50 Can Direct Latent Model Learning Solve Linear Quadratic Gaussian Control? Yi Tian, Kaiqing Zhang, Russ Tedrake, Suvrit Sra; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:51-63 Policy Learning for Active Target Tracking over Continuous $SE(3)$ Trajectories Pengzhi Yang, Shumon Koga, Arash Asgharivaskasi, Nikolay Atanasov; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:64-75 Guaranteed Conformance of Neurosymbolic Models to Natural Constraints Kaustubh Sridhar, Souradeep Dutta, James Weimer, Insup Lee; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:76-89 ISAACS: Iterative Soft Adversarial Actor-Critic for Safety Kai-Chieh Hsu, Duy Phuong Nguyen, Jaime Fernàndez Fisac; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:90-103 Safe and Efficient Reinforcement Learning using Disturbance-Observer-Based Control Barrier Functions Yikun Cheng, Pan Zhao, Naira Hovakimyan; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:104-115 Learning the dynamics of autonomous nonlinear delay systems Xunbi Ji, Gabor Orosz; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:116-127 Improving Gradient Computation for Differentiable Physics Simulation with Contacts Yaofeng Desmond Zhong, Jiequn Han, Biswadip Dey, Georgia Olympia Brikis; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:128-141 Learning Trust Over Directed Graphs in Multiagent Systems Orhan Eren Akgun, Arif Kerem Dayi, Stephanie Gil, Angelia Nedich; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:142-154 Contrastive Example-Based Control Kyle Beltran Hatch, Benjamin Eysenbach, Rafael Rafailov, Tianhe Yu, Ruslan Salakhutdinov, Sergey Levine, Chelsea Finn; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:155-169 DiffTune$^+$: Hyperparameter-Free Auto-Tuning using Auto-Differentiation Sheng Cheng, Lin Song, Minkyung Kim, Shenlong Wang, Naira Hovakimyan; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:170-183 Policy Gradient Play with Networked Agents in Markov Potential Games Sarper Aydin, Ceyhun Eksin; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:184-195 Sample Complexity Bound for Evaluating the Robust Observer’s Performance under Coprime Factors Uncertainty Serban Sabau, Yifei Zhang, Sourav Kumar Ukil; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:196-207 Learning Robust State Observers using Neural ODEs Keyan Miao, Konstantinos Gatsis; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:208-219 End-to-End Learning to Warm-Start for Real-Time Quadratic Optimization Rajiv Sambharya, Georgina Hall, Brandon Amos, Bartolomeo Stellato; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:220-234 Full Gradient Deep Reinforcement Learning for Average-Reward Criterion Tejas Pagare, Vivek Borkar, Konstantin Avrachenkov; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:235-247 Regret Analysis of Online LQR Control via Trajectory Prediction and Tracking Yitian Chen, Timothy L Molloy, Tyler Summers, Iman Shames; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:248-258 Learning Policy-Aware Models for Model-Based Reinforcement Learning via Transition Occupancy Matching Yecheng Jason Ma, Kausik Sivakumar, Jason Yan, Osbert Bastani, Dinesh Jayaraman; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:259-271 Compositional Neural Certificates for Networked Dynamical Systems Songyuan Zhang, Yumeng Xiu, Guannan Qu, Chuchu Fan; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:272-285 In-Distribution Barrier Functions: Self-Supervised Policy Filters that Avoid Out-of-Distribution States Fernando Castañeda, Haruki Nishimura, Rowan Thomas McAllister, Koushil Sreenath, Adrien Gaidon; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:286-299 Adaptive Conformal Prediction for Motion Planning among Dynamic Agents Anushri Dixit, Lars Lindemann, Skylar X Wei, Matthew Cleaveland, George J. Pappas, Joel W. Burdick; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:300-314 Provably Efficient Generalized Lagrangian Policy Optimization for Safe Multi-Agent Reinforcement Learning Dongsheng Ding, Xiaohan Wei, Zhuoran Yang, Zhaoran Wang, Mihailo Jovanovic; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:315-332 Equilibria of Fully Decentralized Learning in Networked Systems Yan Jiang, Wenqi Cui, Baosen Zhang, Jorge Cortes; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:333-345 Operator Learning for Nonlinear Adaptive Control Luke Bhan, Yuanyuan Shi, Miroslav Krstic; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:346-357 A Generalizable Physics-informed Learning Framework for Risk Probability Estimation Zhuoyuan Wang, Yorie Nakahira; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:358-370 Efficient Reinforcement Learning Through Trajectory Generation Wenqi Cui, Linbin Huang, Weiwei Yang, Baosen Zhang; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:371-382 Concentration Phenomenon for Random Dynamical Systems: An Operator Theoretic Approach Muhammad Abdullah Naeem; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:383-394 Modified Policy Iteration for Exponential Cost Risk Sensitive MDPs Yashaswini Murthy, Mehrdad Moharrami, R. Srikant; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:395-406 Automated Reachability Analysis of Neural Network-Controlled Systems via Adaptive Polytopes Taha Entesari, Mahyar Fazlyab; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:407-419 Designing System Level Synthesis Controllers for Nonlinear Systems with Stability Guarantees Lauren E Conger, Sydney Vernon, Eric Mazumdar; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:420-430 Targeted Adversarial Attacks against Neural Network Trajectory Predictors Kaiyuan Tan, Jun Wang, Yiannis Kantaros; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:431-444 Can Learning Deteriorate Control? Analyzing Computational Delays in Gaussian Process-Based Event-Triggered Online Learning Xiaobing Dai, Armin Lederer, Zewen Yang, Sandra Hirche; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:445-457 Probabilistic Invariance for Gaussian Process State Space Models Paul Griffioen, Alex Devonport, Murat Arcak; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:458-468 Compositional Learning-based Planning for Vision POMDPs Sampada Deglurkar, Michael H Lim, Johnathan Tucker, Zachary N Sunberg, Aleksandra Faust, Claire Tomlin; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:469-482 Certified Invertibility in Neural Networks via Mixed-Integer Programming Tianqi Cui, Thomas Bertalan, George J. Pappas, Manfred Morari, Yannis Kevrekidis, Mahyar Fazlyab; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:483-496 The Impact of the Geometric Properties of the Constraint Set in Safe Optimization with Bandit Feedback Spencer Hutchinson, Berkay Turan, Mahnoosh Alizadeh; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:497-508 Template-Based Piecewise Affine Regression Guillaume O Berger, Sriram Sankaranarayanan; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:509-520 Physics-enhanced Gaussian Process Variational Autoencoder Thomas Beckers, Qirui Wu, George J. Pappas; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:521-533 A Reinforcement Learning Look at Risk-Sensitive Linear Quadratic Gaussian Control Leilei Cui, Tamer Basar, Zhong-Ping Jiang; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:534-546 Time-Incremental Learning of Temporal Logic Classifiers Using Decision Trees Erfan Aasi, Mingyu Cai, Cristian Ioan Vasile, Calin Belta; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:547-559 Adaptive Regret for Control of Time-Varying Dynamics Paula Gradu, Elad Hazan, Edgar Minasyan; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:560-572 Automatic Integration for Fast and Interpretable Neural Point Processes Zihao Zhou, Rose Yu; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:573-585 Multi-Task Imitation Learning for Linear Dynamical Systems Thomas T. Zhang, Katie Kang, Bruce D Lee, Claire Tomlin, Sergey Levine, Stephen Tu, Nikolai Matni; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:586-599 Accelerating Trajectory Generation for Quadrotors Using Transformers Srinath Tankasala, Mitch Pryor; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:600-611 A finite-sample analysis of multi-step temporal difference estimates Yaqi Duan, Martin J. Wainwright; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:612-624 Practical Critic Gradient based Actor Critic for On-Policy Reinforcement Learning Swaminathan Gurumurthy, Zachary Manchester, J Zico Kolter; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:625-638 Deep Off-Policy Iterative Learning Control Swaminathan Gurumurthy, J Zico Kolter, Zachary Manchester; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:639-652 Transportation-Inequalities, Lyapunov Stability and Sampling for Dynamical Systems on Continuous State Space Muhammad Abdullah Naeem, Miroslav Pajic; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:653-664 Learning Disturbances Online for Risk-Aware Control: Risk-Aware Flight with Less Than One Minute of Data Prithvi Akella, Skylar X Wei, Joel W. Burdick, Aaron Ames; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:665-678 Compositional Learning of Dynamical System Models Using Port-Hamiltonian Neural Networks Cyrus Neary, Ufuk Topcu; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:679-691 Multi-Agent Reinforcement Learning with Reward Delays Yuyang Zhang, Runyu Zhang, Yuantao Gu, Na Li; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:692-704 CatlNet: Learning Communication and Coordination Policies from CaTL+ Specifications Wenliang Liu, Kevin Leahy, Zachary Serlin, Calin Belta; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:705-717 Roll-Drop: accounting for observation noise with a single parameter Luigi Campanaro, Daniele De Martini, Siddhant Gangapurwala, Wolfgang Merkt, Ioannis Havoutis; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:718-730 Lie Group Forced Variational Integrator Networks for Learning and Control of Robot Systems Valentin Duruisseaux, Thai P. Duong, Melvin Leok, Nikolay Atanasov; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:731-744 Learning Object-Centric Dynamic Modes from Video and Emerging Properties Armand Comas, Christian Fernandez Lopez, Sandesh Ghimire, Haolin Li, Mario Sznaier, Octavia Camps; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:745-769 Continuous Versatile Jumping Using Learned Action Residuals Yuxiang Yang, Xiangyun Meng, Wenhao Yu, Tingnan Zhang, Jie Tan, Byron Boots; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:770-782 Probabilistic Safeguard for Reinforcement Learning Using Safety Index Guided Gaussian Process Models Weiye Zhao, Tairan He, Changliu Liu; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:783-796 Hierarchical Policy Blending As Optimal Transport An Thai Le, Kay Hansel, Jan Peters, Georgia Chalvatzaki; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:797-812 Top-k data selection via distributed sample quantile inference Xu Zhang, Marcos M. Vasconcelos; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:813-824 Model-based Validation as Probabilistic Inference Harrison Delecki, Anthony Corso, Mykel Kochenderfer; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:825-837 Nonlinear Controllability and Function Representation by Neural Stochastic Differential Equations Tanya Veeravalli, Maxim Raginsky; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:838-850 Agile Catching with Whole-Body MPC and Blackbox Policy Learning Saminda Abeyruwan, Alex Bewley, Nicholas Matthew Boffi, Krzysztof Marcin Choromanski, David B D’Ambrosio, Deepali Jain, Pannag R Sanketi, Anish Shankar, Vikas Sindhwani, Sumeet Singh, Jean-Jacques Slotine, Stephen Tu; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:851-863 Distributionally Robust Lyapunov Function Search Under Uncertainty Kehan Long, Yinzhuang Yi, Jorge Cortes, Nikolay Atanasov; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:864-877 Black-Box vs. Gray-Box: A Case Study on Learning Table Tennis Ball Trajectory Prediction with Spin and Impacts Jan Achterhold, Philip Tobuschat, Hao Ma, Dieter Büchler, Michael Muehlebach, Joerg Stueckler; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:878-890 Data-driven memory-dependent abstractions of dynamical systems Adrien Banse, Licio Romao, Alessandro Abate, Raphael Jungers; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:891-902 Congestion Control of Vehicle Traffic Networks by Learning Structural and Temporal Patterns SooJean Han, Soon-Jo Chung, Johanna Gustafson; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:903-914 A Learning and Control Perspective for Microfinance Xiyu Deng, Christian Kurniawan, Adhiraj Chakraborty, Assane Gueye, Niangjun Chen, Yorie Nakahira; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:915-927 Physics-Guided Active Learning of Environmental Flow Fields Reza Khodayi-mehr, Pingcheng Jian, Michael M. Zavlanos; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:928-940 CT-DQN: Control-Tutored Deep Reinforcement Learning Francesco De Lellis, Marco Coraggio, Giovanni Russo, Mirco Musolesi, Mario di Bernardo; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:941-953 Failing with Grace: Learning Neural Network Controllers that are Boundedly Unsafe Panagiotis Vlantis, Leila Bridgeman, Michael Zavlanos; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:954-965 Probabilistic Verification of ReLU Neural Networks via Characteristic Functions Joshua Pilipovsky, Vignesh Sivaramakrishnan, Meeko Oishi, Panagiotis Tsiotras; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:966-979 Data-driven Stochastic Output-Feedback Predictive Control: Recursive Feasibility through Interpolated Initial Conditions Guanru Pan, Ruchuan Ou, Timm Faulwasser; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:980-992 Detection of Man-in-the-Middle Attacks in Model-Free Reinforcement Learning Rishi Rani, Massimo Franceschetti; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:993-1007 On Controller Reduction in Linear Quadratic Gaussian Control with Performance Bounds Zhaolin Ren, Yang Zheng, Maryam Fazel, Na Li; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1008-1019 Competing Bandits in Time Varying Matching Markets Deepan Muthirayan, Chinmay Maheshwari, Pramod Khargonekar, Shankar Sastry; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1020-1031 Regret Guarantees for Online Deep Control Xinyi Chen, Edgar Minasyan, Jason D. Lee, Elad Hazan; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1032-1045 Frequency Domain Gaussian Process Models for $H^∞$ Uncertainties Alex Devonport, Peter Seiler, Murat Arcak; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1046-1057 Satellite Navigation and Coordination with Limited Information Sharing Sydney Dolan, Siddharth Nayak, Hamsa Balakrishnan; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1058-1071 Toward Multi-Agent Reinforcement Learning for Distributed Event-Triggered Control Lukas Kesper, Sebastian Trimpe, Dominik Baumann; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1072-1085 Analysis and Detectability of Offline Data Poisoning Attacks on Linear Dynamical Systems Alessio Russo; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1086-1098 Learning Stability Attention in Vision-based End-to-end Driving Policies Tsun-Hsuan Wang, Wei Xiao, Makram Chahine, Alexander Amini, Ramin Hasani, Daniela Rus; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1099-1111 Provably Efficient Model-free RL in Leader-Follower MDP with Linear Function Approximation Arnob Ghosh; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1112-1124 Learning-enhanced Nonlinear Model Predictive Control using Knowledge-based Neural Ordinary Differential Equations and Deep Ensembles Kong Yao Chee, M. Ani Hsieh, Nikolai Matni; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1125-1137 Online switching control with stability and regret guarantees Yingying Li, James A Preiss, Na Li, Yiheng Lin, Adam Wierman, Jeff S Shamma; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1138-1151 CLAS: Coordinating Multi-Robot Manipulation with Central Latent Action Spaces Elie Aljalbout, Maximilian Karl, Patrick van der Smagt; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1152-1166 Learning Coherent Clusters in Weakly-Connected Network Systems Hancheng Min, Enrique Mallada; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1167-1179 Predictive safety filter using system level synthesis Antoine Leeman, Johannes Köhler, Samir Bennani, Melanie Zeilinger; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1180-1192 Time Dependent Inverse Optimal Control using Trigonometric Basis Functions Rahel Rickenbach, Elena Arcari, Melanie Zeilinger; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1193-1204 Interpreting Primal-Dual Algorithms for Constrained Multiagent Reinforcement Learning Daniel Tabas, Ahmed S Zamzam, Baosen Zhang; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1205-1217 Learning Locomotion Skills from MPC in Sensor Space Majid Khadiv, Avadesh Meduri, Huaijiang Zhu, Ludovic Righetti, Bernhard Schölkopf; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1218-1230 Probabilistic Symmetry for Multi-Agent Dynamics Sophia Huiwen Sun, Robin Walters, Jinxi Li, Rose Yu; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1231-1244 Policy Evaluation in Distributional LQR Zifan Wang, Yulong Gao, Siyi Wang, Michael M. Zavlanos, Alessandro Abate, Karl Henrik Johansson; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1245-1256 Reachability Analysis-based Safety-Critical Control using Online Fixed-Time Reinforcement Learning Nick-Marios Kokolakis, Kyriakos G Vamvoudakis, Wassim Haddad; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1257-1270 Online Estimation of the Koopman Operator Using Fourier Features Tahiya Salam, Alice Kate Li, M. Ani Hsieh; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1271-1283 Hybrid Multi-agent Deep Reinforcement Learning for Autonomous Mobility on Demand Systems Tobias Enders, James Harrison, Marco Pavone, Maximilian Schiffer; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1284-1296 Model-Based Reinforcement Learning for Cavity Filter Tuning Doumitrou Daniil Nimara, Mohammadreza Malek-Mohammadi, Petter Ogren, Jieqiang Wei, Vincent Huang; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1297-1307 FedSysID: A Federated Approach to Sample-Efficient System Identification Han Wang, Leonardo Felipe Toso, James Anderson; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1308-1320 Lipschitz constant estimation for 1D convolutional neural networks Patricia Pauli, Dennis Gramlich, Frank Allgöwer; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1321-1332 Rectified Pessimistic-Optimistic Learning for Stochastic Continuum-armed Bandit with Constraints Hengquan Guo, Zhu Qi, Xin Liu; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1333-1344 Best of Both Worlds in Online Control: Competitive Ratio and Policy Regret Gautam Goel, Naman Agarwal, Karan Singh, Elad Hazan; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1345-1356 Offline Model-Based Reinforcement Learning for Tokamak Control Ian Char, Joseph Abbate, Laszlo Bardoczi, Mark Boyer, Youngseog Chung, Rory Conlin, Keith Erickson, Viraj Mehta, Nathan Richner, Egemen Kolemen, Jeff Schneider; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1357-1372 A Dynamical Systems Perspective on Discrete Optimization Tong Guanchun, Michael Muehlebach; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1373-1386 Linear Stochastic Bandits over a Bit-Constrained Channel Aritra Mitra, Hamed Hassani, George J. Pappas; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1387-1399 Hybrid Systems Neural Control with Region-of-Attraction Planner Yue Meng, Chuchu Fan; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1400-1415 Online Saddle Point Tracking with Decision-Dependent Data Killian Reed Wood, Emiliano Dall’Anese; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1416-1428 Wing shape estimation with Extended Kalman filtering and KalmanNet neural network of a flexible wing aircraft Bence Zsombor Hadlaczky, Noémi Friedman, Béla Takarics, Balint Vanek; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1429-1440 Filter-Aware Model-Predictive Control Baris Kayalibay, Atanas Mirchev, Ahmed Agha, Patrick van der Smagt, Justin Bayer; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1441-1454 Hyperparameter Tuning of an Off-Policy Reinforcement Learning Algorithm for H∞ Tracking Control Alireza Farahmandi, Brian C Reitz, Mark Debord, Douglas Philbrick, Katia Estabridis, Gary Hewer; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1455-1466 DLKoopman: A deep learning software package for Koopman theory Sourya Dey, Eric William Davis; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1467-1479 Benchmarking Rigid Body Contact Models Michelle Guo, Yifeng Jiang, Andrew Everett Spielberg, Jiajun Wu, Karen Liu; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1480-1492 Model Predictive Control via On-Policy Imitation Learning Kwangjun Ahn, Zakaria Mhammedi, Horia Mania, Zhang-Wei Hong, Ali Jadbabaie; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1493-1505 subscribe via RSS |
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