Ching-An Cheng

103 papers A* 24A 9C 1Misc 4Journal 55Unranked 9

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	POLCA: Stochastic Generative Optimization with LLM. CoRR Xuanfei Ren, Allen Nie, Tengyang Xie, Ching-An Cheng
2026	J	`jnl`	Understanding the Challenges in Iterative Generative Optimization with LLMs. CoRR Allen Nie, Xavier Daull, Zhiyi Kuang, Abhinav Akkiraju, Anish Chaudhuri, Max Piasevoli, Ryan Rong, Yucheng Yuan, Prerit Choudhary, Shannon Xiao, Rasool Fakoor, Adith Swaminathan, Ching-An Cheng
2025	J	`jnl`	Provably Learning from Language Feedback. CoRR Wanqiao Xu, Allen Nie, Ruijie Zheng, Aditya Modi, Adith Swaminathan, Ching-An Cheng
2025	J	`jnl`	Rapidly Adapting Policies to the Real World via Simulation-Guided Fine-Tuning. CoRR Patrick Yin, Tyler Westenbroek, Simran Bagaria, Kevin Huang, Ching-An Cheng, Andrey Kobolov, Abhishek Gupta
2025	A*	`conf`	Rapidly Adapting Policies to the Real-World via Simulation-Guided Fine-Tuning. ICLR Patrick Yin, Tyler Westenbroek, Ching-An Cheng, Andrey Kolobov, Abhishek Gupta
2024	J	`jnl`	Direct Nash Optimization: Teaching Language Models to Self-Improve with General Preferences. CoRR Corby Rosset, Ching-An Cheng, Arindam Mitra, Michael Santacroce, Ahmed Awadallah, Tengyang Xie
2024	A*	`conf`	How to Solve Contextual Goal-Oriented Problems with Offline Datasets? NeurIPS Ying Fan, Jingling Li, Adith Swaminathan, Aditya Modi, Ching-An Cheng
2024	J	`jnl`	How to Solve Contextual Goal-Oriented Problems with Offline Datasets? CoRR Ying Fan, Jingling Li, Adith Swaminathan, Aditya Modi, Ching-An Cheng
2024	A*	`conf`	Improving Offline RL by Blending Heuristics. ICLR Sinong Geng, Aldo Pacchiano, Andrey Kolobov, Ching-An Cheng
2024	A*	`conf`	PRISE: LLM-Style Sequence Compression for Learning Temporal Action Abstractions in Control. ICML Ruijie Zheng, Ching-An Cheng, Hal Daumé III, Furong Huang, Andrey Kolobov
2024	J	`jnl`	PRISE: Learning Temporal Action Abstractions as a Sequence Compression Problem. CoRR Ruijie Zheng, Ching-An Cheng, Hal Daumé III, Furong Huang, Andrey Kolobov
2024	J	`jnl`	Streetwise Agents: Empowering Offline RL Policies to Outsmart Exogenous Stochastic Disturbances in RTC. CoRR Aditya Soni, Mayukh Das, Anjaly Parayil, Supriyo Ghosh, Shivam Shandilya, Ching-An Cheng, Vishak Gopal, Sami Khairy, Gabriel Mittag, Yasaman Hosseinkashi, Chetan Bansal
2024	J	`jnl`	The Importance of Directional Feedback for LLM-based Optimizers. CoRR Allen Nie, Ching-An Cheng, Andrey Kolobov, Adith Swaminathan
2024	J	`jnl`	Trace is the New AutoDiff - Unlocking Efficient Optimization of Computational Workflows. CoRR Ching-An Cheng, Allen Nie, Adith Swaminathan
2024	A*	`conf`	Trace is the Next AutoDiff: Generative Optimization with Rich Feedback, Execution Traces, and LLMs. NeurIPS Ching-An Cheng, Allen Nie, Adith Swaminathan
2023	A*	`conf`	Adversarial Model for Offline Reinforcement Learning. NeurIPS Mohak Bhardwaj, Tengyang Xie, Byron Boots, Nan Jiang, Ching-An Cheng
2023	J	`jnl`	Adversarial Model for Offline Reinforcement Learning. CoRR Mohak Bhardwaj, Tengyang Xie, Byron Boots, Nan Jiang, Ching-An Cheng
2023	Misc	`conf`	Goal Representations for Instruction Following: A Semi-Supervised Language Interface to Control. CoRL Vivek Myers, Andre Wang He, Kuan Fang, Homer Rich Walke, Philippe Hansen-Estruch, Ching-An Cheng, Mihai Jalobeanu, Andrey Kolobov, Anca D. Dragan, Sergey Levine
2023	J	`jnl`	Goal Representations for Instruction Following: A Semi-Supervised Language Interface to Control. CoRR Vivek Myers, Andre He, Kuan Fang, Homer Walke, Philippe Hansen-Estruch, Ching-An Cheng, Mihai Jalobeanu, Andrey Kolobov, Anca D. Dragan, Sergey Levine
2023	A*	`conf`	Hindsight Learning for MDPs with Exogenous Inputs. ICML Sean R. Sinclair, Felipe Vieira Frujeri, Ching-An Cheng, Luke Marshall, Hugo de Oliveira Barbalho, Jingling Li, Jennifer Neville, Ishai Menache, Adith Swaminathan
2023	J	`jnl`	Improving Offline RL by Blending Heuristics. CoRR Sinong Geng, Aldo Pacchiano, Andrey Kolobov, Ching-An Cheng
2023	J	`jnl`	Interactive Robot Learning from Verbal Correction. CoRR Huihan Liu, Alice Chen, Yuke Zhu, Adith Swaminathan, Andrey Kolobov, Ching-An Cheng
2023	J	`jnl`	LLF-Bench: Benchmark for Interactive Learning from Language Feedback. CoRR Ching-An Cheng, Andrey Kolobov, Dipendra Misra, Allen Nie, Adith Swaminathan
2023	A*	`conf`	MAHALO: Unifying Offline Reinforcement Learning and Imitation Learning from Observations. ICML Anqi Li, Byron Boots, Ching-An Cheng
2023	J	`jnl`	MAHALO: Unifying Offline Reinforcement Learning and Imitation Learning from Observations. CoRR Anqi Li, Byron Boots, Ching-An Cheng
2023	Misc	`conf`	PLEX: Making the Most of the Available Data for Robotic Manipulation Pretraining. CoRL Garrett Thomas, Ching-An Cheng, Ricky Loynd, Felipe Vieira Frujeri, Vibhav Vineet, Mihai Jalobeanu, Andrey Kolobov
2023	J	`jnl`	PLEX: Making the Most of the Available Data for Robotic Manipulation Pretraining. CoRR Garrett Thomas, Ching-An Cheng, Ricky Loynd, Vibhav Vineet, Mihai Jalobeanu, Andrey Kolobov
2023	A*	`conf`	Provable Reset-free Reinforcement Learning by No-Regret Reduction. ICML Hoai-An Nguyen, Ching-An Cheng
2023	J	`jnl`	Provable Reset-free Reinforcement Learning by No-Regret Reduction. CoRR Hoai-An Nguyen, Ching-An Cheng
2023	A*	`conf`	Provably Efficient Lifelong Reinforcement Learning with Linear Representation. ICLR Sanae Amani, Lin Yang, Ching-An Cheng
2023	A*	`conf`	Survival Instinct in Offline Reinforcement Learning. NeurIPS Anqi Li, Dipendra Misra, Andrey Kolobov, Ching-An Cheng
2023	J	`jnl`	Survival Instinct in Offline Reinforcement Learning. CoRR Anqi Li, Dipendra Misra, Andrey Kolobov, Ching-An Cheng
2022	J	`jnl`	ARMOR: A Model-based Framework for Improving Arbitrary Baseline Policies with Offline Data. CoRR Tengyang Xie, Mohak Bhardwaj, Nan Jiang, Ching-An Cheng
2022	A*	`conf`	Adversarially Trained Actor Critic for Offline Reinforcement Learning. ICML Ching-An Cheng, Tengyang Xie, Nan Jiang, Alekh Agarwal
2022	J	`jnl`	Adversarially Trained Actor Critic for Offline Reinforcement Learning. CoRR Ching-An Cheng, Tengyang Xie, Nan Jiang, Alekh Agarwal
2022	J	`jnl`	Hindsight Learning for MDPs with Exogenous Inputs. CoRR Sean R. Sinclair, Felipe Frujeri, Ching-An Cheng, Adith Swaminathan
2022	A*	`conf`	MoCapAct: A Multi-Task Dataset for Simulated Humanoid Control. NeurIPS Nolan Wagener, Andrey Kolobov, Felipe Vieira Frujeri, Ricky Loynd, Ching-An Cheng, Matthew J. Hausknecht
2022	J	`jnl`	MoCapAct: A Multi-Task Dataset for Simulated Humanoid Control. CoRR Nolan Wagener, Andrey Kolobov, Felipe Vieira Frujeri, Ricky Loynd, Ching-An Cheng, Matthew J. Hausknecht
2022	J	`jnl`	Provably Efficient Lifelong Reinforcement Learning with Linear Function Approximation. CoRR Sanae Amani, Lin F. Yang, Ching-An Cheng
2021	A*	`conf`	Bellman-consistent Pessimism for Offline Reinforcement Learning. NeurIPS Tengyang Xie, Ching-An Cheng, Nan Jiang, Paul Mineiro, Alekh Agarwal
2021	J	`jnl`	Bellman-consistent Pessimism for Offline Reinforcement Learning. CoRR Tengyang Xie, Ching-An Cheng, Nan Jiang, Paul Mineiro, Alekh Agarwal
2021	A*	`conf`	Cautiously Optimistic Policy Optimization and Exploration with Linear Function Approximation. COLT Andrea Zanette, Ching-An Cheng, Alekh Agarwal
2021	J	`jnl`	Cautiously Optimistic Policy Optimization and Exploration with Linear Function Approximation. CoRR Andrea Zanette, Ching-An Cheng, Alekh Agarwal
2021	A	`conf`	Explaining fast improvement in online imitation learning. UAI Xinyan Yan, Byron Boots, Ching-An Cheng
2021	A*	`conf`	Heuristic-Guided Reinforcement Learning. NeurIPS Ching-An Cheng, Andrey Kolobov, Adith Swaminathan
2021	J	`jnl`	Heuristic-Guided Reinforcement Learning. CoRR Ching-An Cheng, Andrey Kolobov, Adith Swaminathan
2021	—	`conf`	RMP2: A Structured Composable Policy Class for Robot Learning. Robotics: Science and Systems Anqi Li, Ching-An Cheng, Muhammad Asif Rana, Man Xie, Karl Van Wyk, Nathan D. Ratliff, Byron Boots
2021	J	`jnl`	RMP2: A Structured Composable Policy Class for Robot Learning. CoRR Anqi Li, Ching-An Cheng, Muhammad Asif Rana, Man Xie, Karl Van Wyk, Nathan D. Ratliff, Byron Boots
2021	J	`jnl`	RMPflow: A Geometric Framework for Generation of Multitask Motion Policies. IEEE Trans Autom. Sci. Eng. Ching-An Cheng, Mustafa Mukadam, Jan Issac, Stan Birchfield, Dieter Fox, Byron Boots, Nathan D. Ratliff
2021	A*	`conf`	Safe Reinforcement Learning Using Advantage-Based Intervention. ICML Nolan Wagener, Byron Boots, Ching-An Cheng
2021	J	`jnl`	Safe Reinforcement Learning Using Advantage-Based Intervention. CoRR Nolan Wagener, Byron Boots, Ching-An Cheng
2020	A	`conf`	A Reduction from Reinforcement Learning to No-Regret Online Learning. AISTATS Ching-An Cheng, Remi Tachet des Combes, Byron Boots, Geoffrey J. Gordon
2020	—	`—`	Efficient and principled robot learning: Theory and algorithms. Ching-An Cheng
2020	J	`jnl`	Explaining Fast Improvement in Online Policy Optimization. CoRR Xinyan Yan, Byron Boots, Ching-An Cheng
2020	A*	`conf`	Extending Riemmanian Motion Policies to a Class of Underactuated Wheeled-Inverted-Pendulum Robots. ICRA Bruce Wingo, Ching-An Cheng, Muhammad Ali Murtaza, Munzir Zafar, Seth Hutchinson
2020	J	`jnl`	Imitation learning for agile autonomous driving. Int. J. Robotics Res. Yunpeng Pan, Ching-An Cheng, Kamil Saigol, Keuntaek Lee, Xinyan Yan, Evangelos A. Theodorou, Byron Boots
2020	A*	`conf`	Intra Order-preserving Functions for Calibration of Multi-Class Neural Networks. NeurIPS Amir Rahimi, Amirreza Shaban, Ching-An Cheng, Richard Hartley, Byron Boots
2020	J	`jnl`	Intra Order-preserving Functions for Calibration of Multi-Class Neural Networks. CoRR Amir Rahimi, Amirreza Shaban, Ching-An Cheng, Byron Boots, Richard Hartley
2020	A	`conf`	Online Learning with Continuous Variations: Dynamic Regret and Reductions. AISTATS Ching-An Cheng, Jonathan Lee, Ken Goldberg, Byron Boots
2020	J	`jnl`	Policy Improvement from Multiple Experts. CoRR Ching-An Cheng, Andrey Kolobov, Alekh Agarwal
2020	A*	`conf`	Policy Improvement via Imitation of Multiple Oracles. NeurIPS Ching-An Cheng, Andrey Kolobov, Alekh Agarwal
2020	J	`jnl`	RMPflow: A Geometric Framework for Generation of Multi-Task Motion Policies. CoRR Ching-An Cheng, Mustafa Mukadam, Jan Issac, Stan Birchfield, Dieter Fox, Byron Boots, Nathan D. Ratliff
2019	J	`jnl`	A Reduction from Reinforcement Learning to No-Regret Online Learning. CoRR Ching-An Cheng, Remi Tachet des Combes, Byron Boots, Geoffrey J. Gordon
2019	A	`conf`	Accelerating Imitation Learning with Predictive Models. AISTATS Ching-An Cheng, Xinyan Yan, Evangelos A. Theodorou, Byron Boots
2019	—	`conf`	An Online Learning Approach to Model Predictive Control. Robotics: Science and Systems Nolan Wagener, Ching-An Cheng, Jacob Sacks, Byron Boots
2019	J	`jnl`	An Online Learning Approach to Model Predictive Control. CoRR Nolan Wagener, Ching-An Cheng, Jacob Sacks, Byron Boots
2019	J	`jnl`	Continuous Online Learning and New Insights to Online Imitation Learning. CoRR Jonathan Lee, Ching-An Cheng, Ken Goldberg, Byron Boots
2019	J	`jnl`	Online Learning with Continuous Variations: Dynamic Regret and Reductions. CoRR Ching-An Cheng, Jonathan Lee, Ken Goldberg, Byron Boots
2019	A*	`conf`	Predictor-Corrector Policy Optimization. ICML Ching-An Cheng, Xinyan Yan, Nathan D. Ratliff, Byron Boots
2019	Misc	`conf`	Riemannian Motion Policy Fusion through Learnable Lyapunov Function Reshaping. CoRL Mustafa Mukadam, Ching-An Cheng, Dieter Fox, Byron Boots, Nathan D. Ratliff
2019	J	`jnl`	Riemannian Motion Policy Fusion through Learnable Lyapunov Function Reshaping. CoRR Mustafa Mukadam, Ching-An Cheng, Dieter Fox, Byron Boots, Nathan D. Ratliff
2019	—	`conf`	Stable, Concurrent Controller Composition for Multi-Objective Robotic Tasks. CDC Anqi Li, Ching-An Cheng, Byron Boots, Magnus Egerstedt
2019	J	`jnl`	Stable, Concurrent Controller Composition for Multi-Objective Robotic Tasks. CoRR Anqi Li, Ching-An Cheng, Byron Boots, Magnus Egerstedt
2019	Misc	`conf`	Trajectory-wise Control Variates for Variance Reduction in Policy Gradient Methods. CoRL Ching-An Cheng, Xinyan Yan, Byron Boots
2019	J	`jnl`	Trajectory-wise Control Variates for Variance Reduction in Policy Gradient Methods. CoRR Ching-An Cheng, Xinyan Yan, Byron Boots
2019	A	`conf`	Truncated Back-propagation for Bilevel Optimization. AISTATS Amirreza Shaban, Ching-An Cheng, Nathan Hatch, Byron Boots
2018	—	`conf`	Agile Autonomous Driving using End-to-End Deep Imitation Learning. Robotics: Science and Systems Yunpeng Pan, Ching-An Cheng, Kamil Saigol, Keuntaek Lee, Xinyan Yan, Evangelos A. Theodorou, Byron Boots
2018	A	`conf`	Convergence of Value Aggregation for Imitation Learning. AISTATS Ching-An Cheng, Byron Boots
2018	J	`jnl`	Convergence of Value Aggregation for Imitation Learning. CoRR Ching-An Cheng, Byron Boots
2018	A	`conf`	Fast Policy Learning through Imitation and Reinforcement. UAI Ching-An Cheng, Xinyan Yan, Nolan Wagener, Byron Boots
2018	J	`jnl`	Fast Policy Learning through Imitation and Reinforcement. CoRR Ching-An Cheng, Xinyan Yan, Nolan Wagener, Byron Boots
2018	J	`jnl`	Model-Based Imitation Learning with Accelerated Convergence. CoRR Ching-An Cheng, Xinyan Yan, Evangelos A. Theodorou, Byron Boots
2018	A*	`conf`	Optical Sensing and Control Methods for Soft Pneumatically Actuated Robotic Manipulators. ICRA Jennifer L. Molnar, Ching-An Cheng, Lucas O. Tiziani, Byron Boots, Frank L. Hammond
2018	A*	`conf`	Orthogonally Decoupled Variational Gaussian Processes. NeurIPS Hugh Salimbeni, Ching-An Cheng, Byron Boots, Marc Peter Deisenroth
2018	J	`jnl`	Orthogonally Decoupled Variational Gaussian Processes. CoRR Hugh Salimbeni, Ching-An Cheng, Byron Boots, Marc Peter Deisenroth
2018	J	`jnl`	Predictor-Corrector Policy Optimization. CoRR Ching-An Cheng, Xinyan Yan, Nathan D. Ratliff, Byron Boots
2018	C	`conf`	RMP WAFR Ching-An Cheng, Mustafa Mukadam, Jan Issac, Stan Birchfield, Dieter Fox, Byron Boots, Nathan D. Ratliff
2018	J	`jnl`	RMPflow: A Computational Graph for Automatic Motion Policy Generation. CoRR Ching-An Cheng, Mustafa Mukadam, Jan Issac, Stan Birchfield, Dieter Fox, Byron Boots, Nathan D. Ratliff
2018	J	`jnl`	Truncated Back-propagation for Bilevel Optimization. CoRR Amirreza Shaban, Ching-An Cheng, Nathan Hatch, Byron Boots
2017	J	`jnl`	Agile Off-Road Autonomous Driving Using End-to-End Deep Imitation Learning. CoRR Yunpeng Pan, Ching-An Cheng, Kamil Saigol, Keuntaek Lee, Xinyan Yan, Evangelos A. Theodorou, Byron Boots
2017	J	`jnl`	Approximately Optimal Continuous-Time Motion Planning and Control via Probabilistic Inference. CoRR Mustafa Mukadam, Ching-An Cheng, Xinyan Yan, Byron Boots
2017	A*	`conf`	Approximately optimal continuous-time motion planning and control via Probabilistic Inference. ICRA Mustafa Mukadam, Ching-An Cheng, Xinyan Yan, Byron Boots
2017	—	`conf`	Variational Inference for Gaussian Process Models with Linear Complexity. NIPS Ching-An Cheng, Byron Boots
2017	J	`jnl`	Variational Inference for Gaussian Process Models with Linear Complexity. CoRR Ching-An Cheng, Byron Boots
2016	—	`conf`	Incremental Variational Sparse Gaussian Process Regression. NIPS Ching-An Cheng, Byron Boots
2016	J	`jnl`	Learn the Lagrangian: A Vector-Valued RKHS Approach to Identifying Lagrangian Systems. IEEE Trans. Cybern. Ching-An Cheng, Han-Pang Huang
2016	J	`jnl`	Learning the Inverse Dynamics of Robotic Manipulators in Structured Reproducing Kernel Hilbert Space. IEEE Trans. Cybern. Ching-An Cheng, Han-Pang Huang, Huan-Kun Hsu, Wei-Zh Lai, Chih-Chun Cheng
2016	J	`jnl`	Virtual Impedance Control for Safe Human-Robot Interaction. J. Intell. Robotic Syst. Sheng-Yen Lo, Ching-An Cheng, Han-Pang Huang
2015	—	`conf`	Efficient grasp synthesis and control strategy for robot hand-arm system. CASE Ming-Bao Huang, Han-Pang Huang, Chih-Chun Cheng, Ching-An Cheng
2015	—	`conf`	Humanoid robot push-recovery strategy based on CMP criterion and angular momentum regulation. AIM Che-Hsuan Chang, Han-Pang Huang, Huan-Kun Hsu, Ching-An Cheng
2013	—	`conf`	Bayesian human intention estimator for exoskeleton system. AIM Ching-An Cheng, Tzu-Hao Huang, Han-Pang Huang
2013	A	`conf`	Self-learning assistive exoskeleton with sliding mode admittance control. IROS Tzu-Hao Huang, Ching-An Cheng, Han-Pang Huang
2012	A	`conf`	Design of a new hybrid control and knee orthosis for human walking and rehabilitation. IROS Tzu-Hao Huang, Han-Pang Huang, Ching-An Cheng, Jiun-Yih Kuan, Po-Ting Lee, Shih-Yi Huang