Ching-An Cheng

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 87

Top Topics

Gaussian Process

Policy Gradient

Function Approximation

Top Venues

Publications

Ruijie Zheng, Ching-An Cheng, Hal Daumé III, Furong Huang, Andrey Kolobov
PRISE: Learning Temporal Action Abstractions as a Sequence Compression Problem. CoRR (2024)
Allen Nie, Ching-An Cheng, Andrey Kolobov, Adith Swaminathan
The Importance of Directional Feedback for LLM-based Optimizers. CoRR (2024)
Sinong Geng, Aldo Pacchiano, Andrey Kolobov, Ching-An Cheng
Improving Offline RL by Blending Heuristics. ICLR (2024)
Ching-An Cheng, Allen Nie, Adith Swaminathan
Trace is the New AutoDiff - Unlocking Efficient Optimization of Computational Workflows. CoRR (2024)
Corby Rosset, Ching-An Cheng, Arindam Mitra, Michael Santacroce, Ahmed Awadallah, Tengyang Xie
Direct Nash Optimization: Teaching Language Models to Self-Improve with General Preferences. CoRR (2024)
Vivek Myers, Andre He, Kuan Fang, Homer Walke, Philippe Hansen-Estruch, Ching-An Cheng, Mihai Jalobeanu, Andrey Kolobov, Anca D. Dragan, Sergey Levine
Goal Representations for Instruction Following: A Semi-Supervised Language Interface to Control. CoRR (2023)
Hoai-An Nguyen, Ching-An Cheng
Provable Reset-free Reinforcement Learning by No-Regret Reduction. CoRR (2023)
Anqi Li, Byron Boots, Ching-An Cheng
MAHALO: Unifying Offline Reinforcement Learning and Imitation Learning from Observations. ICML (2023)
Huihan Liu, Alice Chen, Yuke Zhu, Adith Swaminathan, Andrey Kolobov, Ching-An Cheng
Interactive Robot Learning from Verbal Correction. CoRR (2023)
Anqi Li, Dipendra Misra, Andrey Kolobov, Ching-An Cheng
Survival Instinct in Offline Reinforcement Learning. CoRR (2023)
Sinong Geng, Aldo Pacchiano, Andrey Kolobov, Ching-An Cheng
Improving Offline RL by Blending Heuristics. CoRR (2023)
Garrett Thomas, Ching-An Cheng, Ricky Loynd, Vibhav Vineet, Mihai Jalobeanu, Andrey Kolobov
PLEX: Making the Most of the Available Data for Robotic Manipulation Pretraining. CoRR (2023)
Mohak Bhardwaj, Tengyang Xie, Byron Boots, Nan Jiang, Ching-An Cheng
Adversarial Model for Offline Reinforcement Learning. CoRR (2023)
Anqi Li, Byron Boots, Ching-An Cheng
MAHALO: Unifying Offline Reinforcement Learning and Imitation Learning from Observations. CoRR (2023)
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
Goal Representations for Instruction Following: A Semi-Supervised Language Interface to Control. CoRL (2023)
Ching-An Cheng, Andrey Kolobov, Dipendra Misra, Allen Nie, Adith Swaminathan
LLF-Bench: Benchmark for Interactive Learning from Language Feedback. CoRR (2023)
Anqi Li, Dipendra Misra, Andrey Kolobov, Ching-An Cheng
Survival Instinct in Offline Reinforcement Learning. NeurIPS (2023)
Sean R. Sinclair, Felipe Vieira Frujeri, Ching-An Cheng, Luke Marshall, Hugo De Oliveira Barbalho, Jingling Li, Jennifer Neville, Ishai Menache, Adith Swaminathan
Hindsight Learning for MDPs with Exogenous Inputs. ICML (2023)
Hoai-An Nguyen, Ching-An Cheng
Provable Reset-free Reinforcement Learning by No-Regret Reduction. ICML (2023)
Garrett Thomas, Ching-An Cheng, Ricky Loynd, Felipe Vieira Frujeri, Vibhav Vineet, Mihai Jalobeanu, Andrey Kolobov
PLEX: Making the Most of the Available Data for Robotic Manipulation Pretraining. CoRL (2023)
Sanae Amani, Lin Yang, Ching-An Cheng
Provably Efficient Lifelong Reinforcement Learning with Linear Representation. ICLR (2023)
Mohak Bhardwaj, Tengyang Xie, Byron Boots, Nan Jiang, Ching-An Cheng
Adversarial Model for Offline Reinforcement Learning. NeurIPS (2023)
Nolan Wagener, Andrey Kolobov, Felipe Vieira Frujeri, Ricky Loynd, Ching-An Cheng, Matthew J. Hausknecht
MoCapAct: A Multi-Task Dataset for Simulated Humanoid Control. CoRR (2022)
Nolan Wagener, Andrey Kolobov, Felipe Vieira Frujeri, Ricky Loynd, Ching-An Cheng, Matthew J. Hausknecht
MoCapAct: A Multi-Task Dataset for Simulated Humanoid Control. NeurIPS (2022)
Tengyang Xie, Mohak Bhardwaj, Nan Jiang, Ching-An Cheng
ARMOR: A Model-based Framework for Improving Arbitrary Baseline Policies with Offline Data. CoRR (2022)
Sanae Amani, Lin F. Yang, Ching-An Cheng
Provably Efficient Lifelong Reinforcement Learning with Linear Function Approximation. CoRR (2022)
Ching-An Cheng, Tengyang Xie, Nan Jiang, Alekh Agarwal
Adversarially Trained Actor Critic for Offline Reinforcement Learning. ICML (2022)
Ching-An Cheng, Tengyang Xie, Nan Jiang, Alekh Agarwal
Adversarially Trained Actor Critic for Offline Reinforcement Learning. CoRR (2022)
Sean R. Sinclair, Felipe Frujeri, Ching-An Cheng, Adith Swaminathan
Hindsight Learning for MDPs with Exogenous Inputs. CoRR (2022)
Ching-An Cheng, Andrey Kolobov, Adith Swaminathan
Heuristic-Guided Reinforcement Learning. NeurIPS (2021)
Andrea Zanette, Ching-An Cheng, Alekh Agarwal
Cautiously Optimistic Policy Optimization and Exploration with Linear Function Approximation. CoRR (2021)
Anqi Li, Ching-An Cheng, Muhammad Asif Rana, Man Xie, Karl Van Wyk, Nathan D. Ratliff, Byron Boots
RMP2: A Structured Composable Policy Class for Robot Learning. Robotics: Science and Systems (2021)
Andrea Zanette, Ching-An Cheng, Alekh Agarwal
Cautiously Optimistic Policy Optimization and Exploration with Linear Function Approximation. COLT (2021)
Ching-An Cheng, Andrey Kolobov, Adith Swaminathan
Heuristic-Guided Reinforcement Learning. CoRR (2021)
Nolan Wagener, Byron Boots, Ching-An Cheng
Safe Reinforcement Learning Using Advantage-Based Intervention. ICML (2021)
Ching-An Cheng, Mustafa Mukadam, Jan Issac, Stan Birchfield, Dieter Fox, Byron Boots, Nathan D. Ratliff
RMPflow: A Geometric Framework for Generation of Multitask Motion Policies. IEEE Trans Autom. Sci. Eng. 18 (3) (2021)
Tengyang Xie, Ching-An Cheng, Nan Jiang, Paul Mineiro, Alekh Agarwal
Bellman-consistent Pessimism for Offline Reinforcement Learning. CoRR (2021)
Nolan Wagener, Byron Boots, Ching-An Cheng
Safe Reinforcement Learning Using Advantage-Based Intervention. CoRR (2021)
Tengyang Xie, Ching-An Cheng, Nan Jiang, Paul Mineiro, Alekh Agarwal
Bellman-consistent Pessimism for Offline Reinforcement Learning. NeurIPS (2021)
Anqi Li, Ching-An Cheng, Muhammad Asif Rana, Man Xie, Karl Van Wyk, Nathan D. Ratliff, Byron Boots
RMP2: A Structured Composable Policy Class for Robot Learning. CoRR (2021)
Xinyan Yan, Byron Boots, Ching-An Cheng
Explaining fast improvement in online imitation learning. UAI (2021)
Amir Rahimi, Amirreza Shaban, Ching-An Cheng, Byron Boots, Richard Hartley
Intra Order-preserving Functions for Calibration of Multi-Class Neural Networks. CoRR (2020)
Xinyan Yan, Byron Boots, Ching-An Cheng
Explaining Fast Improvement in Online Policy Optimization. CoRR (2020)
Yunpeng Pan, Ching-An Cheng, Kamil Saigol, Keuntaek Lee, Xinyan Yan, Evangelos A. Theodorou, Byron Boots
Imitation learning for agile autonomous driving. Int. J. Robotics Res. 39 (2-3) (2020)
Ching-An Cheng, Mustafa Mukadam, Jan Issac, Stan Birchfield, Dieter Fox, Byron Boots, Nathan D. Ratliff
RMPflow: A Geometric Framework for Generation of Multi-Task Motion Policies. CoRR (2020)
Ching-An Cheng, Remi Tachet des Combes, Byron Boots, Geoffrey J. Gordon
A Reduction from Reinforcement Learning to No-Regret Online Learning. AISTATS (2020)
Ching-An Cheng, Andrey Kolobov, Alekh Agarwal
Policy Improvement from Multiple Experts. CoRR (2020)
Ching-An Cheng, Andrey Kolobov, Alekh Agarwal
Policy Improvement via Imitation of Multiple Oracles. NeurIPS (2020)
Bruce Wingo, Ching-An Cheng, Muhammad Ali Murtaza, Munzir Zafar, Seth Hutchinson
Extending Riemmanian Motion Policies to a Class of Underactuated Wheeled-Inverted-Pendulum Robots. ICRA (2020)
Ching-An Cheng, Jonathan Lee, Ken Goldberg, Byron Boots
Online Learning with Continuous Variations: Dynamic Regret and Reductions. AISTATS (2020)
Amir Rahimi, Amirreza Shaban, Ching-An Cheng, Richard Hartley, Byron Boots
Intra Order-preserving Functions for Calibration of Multi-Class Neural Networks. NeurIPS (2020)
Mustafa Mukadam, Ching-An Cheng, Dieter Fox, Byron Boots, Nathan D. Ratliff
Riemannian Motion Policy Fusion through Learnable Lyapunov Function Reshaping. CoRL (2019)
Ching-An Cheng, Xinyan Yan, Nathan D. Ratliff, Byron Boots
Predictor-Corrector Policy Optimization. ICML (2019)
Mustafa Mukadam, Ching-An Cheng, Dieter Fox, Byron Boots, Nathan D. Ratliff
Riemannian Motion Policy Fusion through Learnable Lyapunov Function Reshaping. CoRR (2019)
Jonathan Lee, Ching-An Cheng, Ken Goldberg, Byron Boots
Continuous Online Learning and New Insights to Online Imitation Learning. CoRR (2019)
Anqi Li, Ching-An Cheng, Byron Boots, Magnus Egerstedt
Stable, Concurrent Controller Composition for Multi-Objective Robotic Tasks. CDC (2019)
Ching-An Cheng, Xinyan Yan, Byron Boots
Trajectory-wise Control Variates for Variance Reduction in Policy Gradient Methods. CoRR (2019)
Anqi Li, Ching-An Cheng, Byron Boots, Magnus Egerstedt
Stable, Concurrent Controller Composition for Multi-Objective Robotic Tasks. CoRR (2019)
Nolan Wagener, Ching-An Cheng, Jacob Sacks, Byron Boots
An Online Learning Approach to Model Predictive Control. CoRR (2019)
Amirreza Shaban, Ching-An Cheng, Nathan Hatch, Byron Boots
Truncated Back-propagation for Bilevel Optimization. AISTATS (2019)
Ching-An Cheng, Remi Tachet des Combes, Byron Boots, Geoffrey J. Gordon
A Reduction from Reinforcement Learning to No-Regret Online Learning. CoRR (2019)
Ching-An Cheng, Xinyan Yan, Evangelos A. Theodorou, Byron Boots
Accelerating Imitation Learning with Predictive Models. AISTATS (2019)
Nolan Wagener, Ching-An Cheng, Jacob Sacks, Byron Boots
An Online Learning Approach to Model Predictive Control. Robotics: Science and Systems (2019)
Ching-An Cheng, Xinyan Yan, Byron Boots
Trajectory-wise Control Variates for Variance Reduction in Policy Gradient Methods. CoRL (2019)
Ching-An Cheng, Jonathan Lee, Ken Goldberg, Byron Boots
Online Learning with Continuous Variations: Dynamic Regret and Reductions. CoRR (2019)
Ching-An Cheng, Xinyan Yan, Nathan D. Ratliff, Byron Boots
Predictor-Corrector Policy Optimization. CoRR (2018)
Ching-An Cheng, Mustafa Mukadam, Jan Issac, Stan Birchfield, Dieter Fox, Byron Boots, Nathan D. Ratliff
RMPflow: A Computational Graph for Automatic Motion Policy Generation. CoRR (2018)
Ching-An Cheng, Xinyan Yan, Nolan Wagener, Byron Boots
Fast Policy Learning through Imitation and Reinforcement. UAI (2018)
Ching-An Cheng, Mustafa Mukadam, Jan Issac, Stan Birchfield, Dieter Fox, Byron Boots, Nathan D. Ratliff
: A Computational Graph for Automatic Motion Policy Generation. WAFR (2018)
Ching-An Cheng, Byron Boots
Convergence of Value Aggregation for Imitation Learning. CoRR (2018)
Jennifer L. Molnar, Ching-An Cheng, Lucas O. Tiziani, Byron Boots, Frank L. Hammond
Optical Sensing and Control Methods for Soft Pneumatically Actuated Robotic Manipulators. ICRA (2018)
Hugh Salimbeni, Ching-An Cheng, Byron Boots, Marc Peter Deisenroth
Orthogonally Decoupled Variational Gaussian Processes. CoRR (2018)
Ching-An Cheng, Xinyan Yan, Evangelos A. Theodorou, Byron Boots
Model-Based Imitation Learning with Accelerated Convergence. CoRR (2018)
Hugh Salimbeni, Ching-An Cheng, Byron Boots, Marc Peter Deisenroth
Orthogonally Decoupled Variational Gaussian Processes. NeurIPS (2018)
Ching-An Cheng, Xinyan Yan, Nolan Wagener, Byron Boots
Fast Policy Learning through Imitation and Reinforcement. CoRR (2018)
Yunpeng Pan, Ching-An Cheng, Kamil Saigol, Keuntaek Lee, Xinyan Yan, Evangelos A. Theodorou, Byron Boots
Agile Autonomous Driving using End-to-End Deep Imitation Learning. Robotics: Science and Systems (2018)
Amirreza Shaban, Ching-An Cheng, Nathan Hatch, Byron Boots
Truncated Back-propagation for Bilevel Optimization. CoRR (2018)
Ching-An Cheng, Byron Boots
Convergence of Value Aggregation for Imitation Learning. AISTATS (2018)
Mustafa Mukadam, Ching-An Cheng, Xinyan Yan, Byron Boots
Approximately Optimal Continuous-Time Motion Planning and Control via Probabilistic Inference. CoRR (2017)
Ching-An Cheng, Byron Boots
Variational Inference for Gaussian Process Models with Linear Complexity. NIPS (2017)
Ching-An Cheng, Byron Boots
Variational Inference for Gaussian Process Models with Linear Complexity. CoRR (2017)
Mustafa Mukadam, Ching-An Cheng, Xinyan Yan, Byron Boots
Approximately optimal continuous-time motion planning and control via Probabilistic Inference. ICRA (2017)
Yunpeng Pan, Ching-An Cheng, Kamil Saigol, Keuntaek Lee, Xinyan Yan, Evangelos A. Theodorou, Byron Boots
Agile Off-Road Autonomous Driving Using End-to-End Deep Imitation Learning. CoRR (2017)
Ching-An Cheng, Han-Pang Huang
Learn the Lagrangian: A Vector-Valued RKHS Approach to Identifying Lagrangian Systems. IEEE Trans. Cybern. 46 (12) (2016)
Ching-An Cheng, Han-Pang Huang, Huan-Kun Hsu, Wei-Zh Lai, Chih-Chun Cheng
Learning the Inverse Dynamics of Robotic Manipulators in Structured Reproducing Kernel Hilbert Space. IEEE Trans. Cybern. 46 (7) (2016)
Ching-An Cheng, Byron Boots
Incremental Variational Sparse Gaussian Process Regression. NIPS (2016)
Sheng-Yen Lo, Ching-An Cheng, Han-Pang Huang
Virtual Impedance Control for Safe Human-Robot Interaction. J. Intell. Robotic Syst. 82 (1) (2016)
Che-Hsuan Chang, Han-Pang Huang, Huan-Kun Hsu, Ching-An Cheng
Humanoid robot push-recovery strategy based on CMP criterion and angular momentum regulation. AIM (2015)
Ming-Bao Huang, Han-Pang Huang, Chih-Chun Cheng, Ching-An Cheng
Efficient grasp synthesis and control strategy for robot hand-arm system. CASE (2015)
Ching-An Cheng, Tzu-Hao Huang, Han-Pang Huang
Bayesian human intention estimator for exoskeleton system. AIM (2013)
Tzu-Hao Huang, Ching-An Cheng, Han-Pang Huang
Self-learning assistive exoskeleton with sliding mode admittance control. IROS (2013)
Tzu-Hao Huang, Han-Pang Huang, Ching-An Cheng, Jiun-Yih Kuan, Po-Ting Lee, Shih-Yi Huang
Design of a new hybrid control and knee orthosis for human walking and rehabilitation. IROS (2012)