Trace is the New AutoDiff — Unlocking Efficient Optimization of Computational Workflows
Ching-An Cheng, Allen Nie, Adith Swaminathan
June 2024
Ching-An Cheng
Senior Researcher
Publications
Publications by Year
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PRISE: LLM-Style Sequence Compression for Learning Temporal Action Abstractions in Control
Ruijie Zheng, Ching-An Cheng, Hal Daumé III, Furong Huang, Andrey Kolobov
ICML 2024 | June 2024
ORAL
Transferring World Models from Simulation for Efficient Real-World Finetuning
Patrick Yin, Tyler Westenbroek, Simran Bagaria, Kevin Huang, Ching-An Cheng, Andrey Kolobov, Abhishek Gupta
Under submission | June 2024
Improving Offline RL by Blending Heuristics
Sinong Geng, Aldo Pacchiano, Andrey Kolobov, Ching-An Cheng
ICLR 2024 | May 2024
SPOTLIGHT
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Importance of Directional Feedback for LLM-based Optimizers
Allen Nie, Ching-An Cheng, Andrey Kolobov, Adith Swaminathan
NeurIPS 2023 Foundation Models for Decision Making Workshop | December 2023
LLF-Bench: Benchmark for Interactive Learning from Language Feedback
Ching-An Cheng, Andrey Kolobov, Dipendra Misra, Allen Nie, Adith Swaminathan
December 2023
December 2023
Adversarial Model for Offline Reinforcement Learning
Mohak Bhardwaj, Tengyang Xie, Byron Boots, Nan Jiang, Ching-An Cheng
NeurIPS 2023 | December 2023
Survival Instinct in Offline Reinforcement Learning
Anqi Li, Dipendra Misra, Andrey Kolobov, Ching-An Cheng
NeurIPS 2023 | December 2023
SPOTLIGHT
Learning Multi-Task Action Abstractions as a Sequence Compression Problem
Ruijie Zheng, Ching-An Cheng, Furong Huang, Andrey Kolobov
CoRL 2023 Pre-Training for Robot Learning Workshop | November 2023
Interactive Robot Learning from Verbal Correction
Huihan Liu, Alice Chen, Yuke Zhu, Adith Swaminathan, Andrey Kolobov, Ching-An Cheng
CoRL 2023 Workshop on Language and Robot Learning (LangRob) | November 2023
Simple Data Sharing for Multi-Tasked Goal-Oriented Problems
Ying Fan, Jingling Li, Adith Swaminathan, Aditya Modi, Ching-An Cheng
NeurIPS 2023 | October 2023
Hindsight Learning for MDPs with Exogenous Inputs
Sean R. Sinclair, Felipe Vieira Frujeri, Ching-An Cheng, Luke Marshall, Hugo Barbalho, Jingling Li, Jennifer Neville, Ishai Menache, Adith Swaminathan
2023 International Conference on Machine Learning | July 2023
Goal Representations for Instruction Following: A Semi-Supervised Language Interface to Control
Vivek Myers, Andre He, Kuan Fang, Homer Walke, Philippe Hansen-Estruch, Ching-An Cheng, Mihai Jalobeanu, Andrey Kolobov, Anca Dragan, Sergey Levine
CoRL 2023 | June 2023
PLEX: Making the Most of the Available Data for Robotic Manipulation Pretraining
Garrett Thomas, Ching-An Cheng, Ricky Loynd, Felipe Vieira Frujeri, Vibhav Vineet, Mihai Jalobeanu, Andrey Kolobov
CoRL 2023 | June 2023
Survival Instinct in Offline Reinforcement Learning and Implicit Human Bias in Data
Anqi Li, Dipendra Misra, Andrey Kolobov, Ching-An Cheng
ICML 2023 - Interactive Learning with Implicit Human Feedback Workshop | June 2023
ORAL
MAHALO: Unifying Offline Reinforcement Learning and Imitation Learning from Observations
Anqi Li, Byron Boots, Ching-An Cheng
ICML 2023 | June 2023
Provable Reset-free Reinforcement Learning by No-Regret Reduction
Hoai-An Nguyen, Ching-An Cheng
ICML 2023 | February 2023
Provably Efficient Lifelong Reinforcement Learning with Linear Function Representation
Sanae Amani, Lin Yang, Ching-An Cheng
ICLR 2023 | February 2023
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Adversarially Trained Actor Critic for Offline Reinforcement Learning
Ching-An Cheng, Tengyang Xie, Nan Jiang, Alekh Agarwal
ICML 2022 | July 2022
Outstanding Paper Runner Up Award
MoCapAct: A Multi-Task Dataset for Simulated Humanoid Control
Nolan Wagener, Andrey Kolobov, Felipe Vieira Frujeri, Ricky Loynd, Ching-An Cheng, Matthew Hausknecht
NeurIPS 2022 Datasets and Benchmarks Track | July 2022
-
Bellman-consistent Pessimism for Offline Reinforcement Learning
Tengyang Xie, Ching-An Cheng, Nan Jiang, Paul Mineiro, Alekh Agarwal
NeurIPS 2021 | December 2021
Oral Presentation
Heuristic-Guided Reinforcement Learning
Ching-An Cheng, Andrey Kolobov, Adith Swaminathan
NeurIPS 2021 | December 2021
Safe Reinforcement Learning Using Advantage-Based Intervention
Nolan Wagener, Byron Boots, Ching-An Cheng
2021 International Conference on Machine Learning | July 2021
Explaining Fast Improvement in Online Imitation Learning
Xinyan Yan, Byron Boots, Ching-An Cheng
Conference on Uncertainty in Artificial Intelligence (UAI) 2021 | June 2021
Cautiously Optimistic Policy Optimization and Exploration with Linear Function Approximation.
Andrea Zanette, Ching-An Cheng, Alekh Agarwal
COLT | March 2021
RMP2: A Structured Composable Policy Class for Robot Learning.
Anqi Li, Ching-An Cheng, Muhammad Asif Rana, Man Xie, Karl Van Wyk, Nathan D. Ratliff, Byron Boots
RSS | March 2021
-
Intra Order-preserving Functions for Calibration of Multi-Class Neural Networks
Amir Rahimi, Amirreza Shaban, Ching-An Cheng, Richard I Hartley, Byron Boots
NeurIPS | December 2020
Policy Improvement via Imitation of Multiple Oracles
Ching-An Cheng, Andrey Kolobov, Alekh Agarwal
NeurIPS 2020 | December 2020
SPOTLIGHT
A Reduction from Reinforcement Learning to No-Regret Online Learning
Ching-An Cheng, Remi Tachet des Combes, Byron Boots, Geoff Gordon
International Conference on Artificial Intelligence and Statistics | June 2020
Publications by Research Area
-
-
Trace is the New AutoDiff — Unlocking Efficient Optimization of Computational Workflows
Ching-An Cheng, Allen Nie, Adith Swaminathan
June 2024
PRISE: LLM-Style Sequence Compression for Learning Temporal Action Abstractions in Control
Ruijie Zheng, Ching-An Cheng, Hal Daumé III, Furong Huang, Andrey Kolobov
ICML 2024 | June 2024
ORAL
Transferring World Models from Simulation for Efficient Real-World Finetuning
Patrick Yin, Tyler Westenbroek, Simran Bagaria, Kevin Huang, Ching-An Cheng, Andrey Kolobov, Abhishek Gupta
Under submission | June 2024
Improving Offline RL by Blending Heuristics
Sinong Geng, Aldo Pacchiano, Andrey Kolobov, Ching-An Cheng
ICLR 2024 | May 2024
SPOTLIGHT
Importance of Directional Feedback for LLM-based Optimizers
Allen Nie, Ching-An Cheng, Andrey Kolobov, Adith Swaminathan
NeurIPS 2023 Foundation Models for Decision Making Workshop | December 2023
LLF-Bench: Benchmark for Interactive Learning from Language Feedback
Ching-An Cheng, Andrey Kolobov, Dipendra Misra, Allen Nie, Adith Swaminathan
December 2023
December 2023
Adversarial Model for Offline Reinforcement Learning
Mohak Bhardwaj, Tengyang Xie, Byron Boots, Nan Jiang, Ching-An Cheng
NeurIPS 2023 | December 2023
Survival Instinct in Offline Reinforcement Learning
Anqi Li, Dipendra Misra, Andrey Kolobov, Ching-An Cheng
NeurIPS 2023 | December 2023
SPOTLIGHT
Learning Multi-Task Action Abstractions as a Sequence Compression Problem
Ruijie Zheng, Ching-An Cheng, Furong Huang, Andrey Kolobov
CoRL 2023 Pre-Training for Robot Learning Workshop | November 2023
Interactive Robot Learning from Verbal Correction
Huihan Liu, Alice Chen, Yuke Zhu, Adith Swaminathan, Andrey Kolobov, Ching-An Cheng
CoRL 2023 Workshop on Language and Robot Learning (LangRob) | November 2023
Simple Data Sharing for Multi-Tasked Goal-Oriented Problems
Ying Fan, Jingling Li, Adith Swaminathan, Aditya Modi, Ching-An Cheng
NeurIPS 2023 | October 2023
Hindsight Learning for MDPs with Exogenous Inputs
Sean R. Sinclair, Felipe Vieira Frujeri, Ching-An Cheng, Luke Marshall, Hugo Barbalho, Jingling Li, Jennifer Neville, Ishai Menache, Adith Swaminathan
2023 International Conference on Machine Learning | July 2023
Goal Representations for Instruction Following: A Semi-Supervised Language Interface to Control
Vivek Myers, Andre He, Kuan Fang, Homer Walke, Philippe Hansen-Estruch, Ching-An Cheng, Mihai Jalobeanu, Andrey Kolobov, Anca Dragan, Sergey Levine
CoRL 2023 | June 2023
PLEX: Making the Most of the Available Data for Robotic Manipulation Pretraining
Garrett Thomas, Ching-An Cheng, Ricky Loynd, Felipe Vieira Frujeri, Vibhav Vineet, Mihai Jalobeanu, Andrey Kolobov
CoRL 2023 | June 2023
Survival Instinct in Offline Reinforcement Learning and Implicit Human Bias in Data
Anqi Li, Dipendra Misra, Andrey Kolobov, Ching-An Cheng
ICML 2023 - Interactive Learning with Implicit Human Feedback Workshop | June 2023
ORAL
MAHALO: Unifying Offline Reinforcement Learning and Imitation Learning from Observations
Anqi Li, Byron Boots, Ching-An Cheng
ICML 2023 | June 2023
Provable Reset-free Reinforcement Learning by No-Regret Reduction
Hoai-An Nguyen, Ching-An Cheng
ICML 2023 | February 2023
Provably Efficient Lifelong Reinforcement Learning with Linear Function Representation
Sanae Amani, Lin Yang, Ching-An Cheng
ICLR 2023 | February 2023
Adversarially Trained Actor Critic for Offline Reinforcement Learning
Ching-An Cheng, Tengyang Xie, Nan Jiang, Alekh Agarwal
ICML 2022 | July 2022
Outstanding Paper Runner Up Award
MoCapAct: A Multi-Task Dataset for Simulated Humanoid Control
Nolan Wagener, Andrey Kolobov, Felipe Vieira Frujeri, Ricky Loynd, Ching-An Cheng, Matthew Hausknecht
NeurIPS 2022 Datasets and Benchmarks Track | July 2022
Bellman-consistent Pessimism for Offline Reinforcement Learning
Tengyang Xie, Ching-An Cheng, Nan Jiang, Paul Mineiro, Alekh Agarwal
NeurIPS 2021 | December 2021
Oral Presentation
Heuristic-Guided Reinforcement Learning
Ching-An Cheng, Andrey Kolobov, Adith Swaminathan
NeurIPS 2021 | December 2021
Safe Reinforcement Learning Using Advantage-Based Intervention
Nolan Wagener, Byron Boots, Ching-An Cheng
2021 International Conference on Machine Learning | July 2021
Explaining Fast Improvement in Online Imitation Learning
Xinyan Yan, Byron Boots, Ching-An Cheng
Conference on Uncertainty in Artificial Intelligence (UAI) 2021 | June 2021
Cautiously Optimistic Policy Optimization and Exploration with Linear Function Approximation.
Andrea Zanette, Ching-An Cheng, Alekh Agarwal
COLT | March 2021
RMP2: A Structured Composable Policy Class for Robot Learning.
Anqi Li, Ching-An Cheng, Muhammad Asif Rana, Man Xie, Karl Van Wyk, Nathan D. Ratliff, Byron Boots
RSS | March 2021
Policy Improvement via Imitation of Multiple Oracles
Ching-An Cheng, Andrey Kolobov, Alekh Agarwal
NeurIPS 2020 | December 2020
SPOTLIGHT
Intra Order-preserving Functions for Calibration of Multi-Class Neural Networks
Amir Rahimi, Amirreza Shaban, Ching-An Cheng, Richard I Hartley, Byron Boots
NeurIPS | December 2020
A Reduction from Reinforcement Learning to No-Regret Online Learning
Ching-An Cheng, Remi Tachet des Combes, Byron Boots, Geoff Gordon
International Conference on Artificial Intelligence and Statistics | June 2020
-
Hindsight Learning for MDPs with Exogenous Inputs
Sean R. Sinclair, Felipe Vieira Frujeri, Ching-An Cheng, Luke Marshall, Hugo Barbalho, Jingling Li, Jennifer Neville, Ishai Menache, Adith Swaminathan
2023 International Conference on Machine Learning | July 2023
Publications by Type
-
-
PRISE: LLM-Style Sequence Compression for Learning Temporal Action Abstractions in Control
Ruijie Zheng, Ching-An Cheng, Hal Daumé III, Furong Huang, Andrey Kolobov
ICML 2024 | June 2024
ORAL
Transferring World Models from Simulation for Efficient Real-World Finetuning
Patrick Yin, Tyler Westenbroek, Simran Bagaria, Kevin Huang, Ching-An Cheng, Andrey Kolobov, Abhishek Gupta
Under submission | June 2024
Improving Offline RL by Blending Heuristics
Sinong Geng, Aldo Pacchiano, Andrey Kolobov, Ching-An Cheng
ICLR 2024 | May 2024
SPOTLIGHT
Importance of Directional Feedback for LLM-based Optimizers
Allen Nie, Ching-An Cheng, Andrey Kolobov, Adith Swaminathan
NeurIPS 2023 Foundation Models for Decision Making Workshop | December 2023
Adversarial Model for Offline Reinforcement Learning
Mohak Bhardwaj, Tengyang Xie, Byron Boots, Nan Jiang, Ching-An Cheng
NeurIPS 2023 | December 2023
Survival Instinct in Offline Reinforcement Learning
Anqi Li, Dipendra Misra, Andrey Kolobov, Ching-An Cheng
NeurIPS 2023 | December 2023
SPOTLIGHT
Simple Data Sharing for Multi-Tasked Goal-Oriented Problems
Ying Fan, Jingling Li, Adith Swaminathan, Aditya Modi, Ching-An Cheng
NeurIPS 2023 | October 2023
Hindsight Learning for MDPs with Exogenous Inputs
Sean R. Sinclair, Felipe Vieira Frujeri, Ching-An Cheng, Luke Marshall, Hugo Barbalho, Jingling Li, Jennifer Neville, Ishai Menache, Adith Swaminathan
2023 International Conference on Machine Learning | July 2023
Goal Representations for Instruction Following: A Semi-Supervised Language Interface to Control
Vivek Myers, Andre He, Kuan Fang, Homer Walke, Philippe Hansen-Estruch, Ching-An Cheng, Mihai Jalobeanu, Andrey Kolobov, Anca Dragan, Sergey Levine
CoRL 2023 | June 2023
PLEX: Making the Most of the Available Data for Robotic Manipulation Pretraining
Garrett Thomas, Ching-An Cheng, Ricky Loynd, Felipe Vieira Frujeri, Vibhav Vineet, Mihai Jalobeanu, Andrey Kolobov
CoRL 2023 | June 2023
Survival Instinct in Offline Reinforcement Learning and Implicit Human Bias in Data
Anqi Li, Dipendra Misra, Andrey Kolobov, Ching-An Cheng
ICML 2023 - Interactive Learning with Implicit Human Feedback Workshop | June 2023
ORAL
MAHALO: Unifying Offline Reinforcement Learning and Imitation Learning from Observations
Anqi Li, Byron Boots, Ching-An Cheng
ICML 2023 | June 2023
Provable Reset-free Reinforcement Learning by No-Regret Reduction
Hoai-An Nguyen, Ching-An Cheng
ICML 2023 | February 2023
Provably Efficient Lifelong Reinforcement Learning with Linear Function Representation
Sanae Amani, Lin Yang, Ching-An Cheng
ICLR 2023 | February 2023
Adversarially Trained Actor Critic for Offline Reinforcement Learning
Ching-An Cheng, Tengyang Xie, Nan Jiang, Alekh Agarwal
ICML 2022 | July 2022
Outstanding Paper Runner Up Award
MoCapAct: A Multi-Task Dataset for Simulated Humanoid Control
Nolan Wagener, Andrey Kolobov, Felipe Vieira Frujeri, Ricky Loynd, Ching-An Cheng, Matthew Hausknecht
NeurIPS 2022 Datasets and Benchmarks Track | July 2022
Bellman-consistent Pessimism for Offline Reinforcement Learning
Tengyang Xie, Ching-An Cheng, Nan Jiang, Paul Mineiro, Alekh Agarwal
NeurIPS 2021 | December 2021
Oral Presentation
Heuristic-Guided Reinforcement Learning
Ching-An Cheng, Andrey Kolobov, Adith Swaminathan
NeurIPS 2021 | December 2021
Safe Reinforcement Learning Using Advantage-Based Intervention
Nolan Wagener, Byron Boots, Ching-An Cheng
2021 International Conference on Machine Learning | July 2021
Explaining Fast Improvement in Online Imitation Learning
Xinyan Yan, Byron Boots, Ching-An Cheng
Conference on Uncertainty in Artificial Intelligence (UAI) 2021 | June 2021
Cautiously Optimistic Policy Optimization and Exploration with Linear Function Approximation.
Andrea Zanette, Ching-An Cheng, Alekh Agarwal
COLT | March 2021
RMP2: A Structured Composable Policy Class for Robot Learning.
Anqi Li, Ching-An Cheng, Muhammad Asif Rana, Man Xie, Karl Van Wyk, Nathan D. Ratliff, Byron Boots
RSS | March 2021
Policy Improvement via Imitation of Multiple Oracles
Ching-An Cheng, Andrey Kolobov, Alekh Agarwal
NeurIPS 2020 | December 2020
SPOTLIGHT
Intra Order-preserving Functions for Calibration of Multi-Class Neural Networks
Amir Rahimi, Amirreza Shaban, Ching-An Cheng, Richard I Hartley, Byron Boots
NeurIPS | December 2020
A Reduction from Reinforcement Learning to No-Regret Online Learning
Ching-An Cheng, Remi Tachet des Combes, Byron Boots, Geoff Gordon
International Conference on Artificial Intelligence and Statistics | June 2020
-
LLF-Bench: Benchmark for Interactive Learning from Language Feedback
Ching-An Cheng, Andrey Kolobov, Dipendra Misra, Allen Nie, Adith Swaminathan
December 2023
December 2023
-
Learning Multi-Task Action Abstractions as a Sequence Compression Problem
Ruijie Zheng, Ching-An Cheng, Furong Huang, Andrey Kolobov
CoRL 2023 Pre-Training for Robot Learning Workshop | November 2023
Interactive Robot Learning from Verbal Correction
Huihan Liu, Alice Chen, Yuke Zhu, Adith Swaminathan, Andrey Kolobov, Ching-An Cheng
CoRL 2023 Workshop on Language and Robot Learning (LangRob) | November 2023