Ching-An Cheng
36 papers · 2016–2025 · 8 conferences · across top CS/AI conferences
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(36)
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Conferences
NIPS (12)
ICML (7)
AISTATS (5)
CORL (4)
ICLR (3)
RSS (3)
COLT (1)
UAI (1)
Top co-authors
Keywords
policy optimization
(8)
offline reinforcement learning
(7)
online learning
(6)
reinforcement learning
(6)
imitation learning
(5)
adversarial training
(3)
policy learning
(3)
markov decision process
(3)
gaussian process
(2)
reward function
(2)
model-based reinforcement learning
(2)
hyperparameter tuning
(2)
automatic differentiation
(2)
variational inference
(2)
policy gradient
(2)
sublinear regret
(2)
representation learning
(1)
stochastic gradient
(1)
deep reinforcement learning
(1)
few-shot learning
(1)
Papers
Rapidly Adapting Policies to the Real-World via Simulation-Guided Fine-Tuning
ICLR 2025
PRISE: LLM-Style Sequence Compression for Learning Temporal Action Abstractions in Control
ICML 2024
How to Solve Contextual Goal-Oriented Problems with Offline Datasets?
NIPS 2024
Improving Offline RL by Blending Heuristics
ICLR 2024
Trace is the Next AutoDiff: Generative Optimization with Rich Feedback, Execution Traces, and LLMs
NIPS 2024
Survival Instinct in Offline Reinforcement Learning
NIPS 2023
Goal Representations for Instruction Following: A Semi-Supervised Language Interface to Control
CORL 2023
Hindsight Learning for MDPs with Exogenous Inputs
ICML 2023
Provably Efficient Lifelong Reinforcement Learning with Linear Representation
ICLR 2023
MAHALO: Unifying Offline Reinforcement Learning and Imitation Learning from Observations
ICML 2023
Adversarial Model for Offline Reinforcement Learning
NIPS 2023
Provable Reset-free Reinforcement Learning by No-Regret Reduction
ICML 2023
PLEX: Making the Most of the Available Data for Robotic Manipulation Pretraining
CORL 2023
MoCapAct: A Multi-Task Dataset for Simulated Humanoid Control
NIPS 2022
Adversarially Trained Actor Critic for Offline Reinforcement Learning
ICML 2022
Explaining fast improvement in online imitation learning
UAI 2021
Safe Reinforcement Learning Using Advantage-Based Intervention
ICML 2021
Bellman-consistent Pessimism for Offline Reinforcement Learning
NIPS 2021
Heuristic-Guided Reinforcement Learning
NIPS 2021
RMP2: A Structured Composable Policy Class for Robot Learning
RSS 2021
Cautiously Optimistic Policy Optimization and Exploration with Linear Function Approximation
COLT 2021
Intra Order-preserving Functions for Calibration of Multi-Class Neural Networks
NIPS 2020
Online Learning with Continuous Variations: Dynamic Regret and Reductions
AISTATS 2020
Policy Improvement via Imitation of Multiple Oracles
NIPS 2020
A Reduction from Reinforcement Learning to No-Regret Online Learning
AISTATS 2020
Accelerating Imitation Learning with Predictive Models
AISTATS 2019
Riemannian Motion Policy Fusion through Learnable Lyapunov Function Reshaping
CORL 2019
Trajectory-wise Control Variates for Variance Reduction in Policy Gradient Methods
CORL 2019
Truncated Back-propagation for Bilevel Optimization
AISTATS 2019
Predictor-Corrector Policy Optimization
ICML 2019
An Online Learning Approach to Model Predictive Control
RSS 2019
Convergence of Value Aggregation for Imitation Learning
AISTATS 2018
Agile Autonomous Driving using End-to-End Deep Imitation Learning
RSS 2018
Orthogonally Decoupled Variational Gaussian Processes
NIPS 2018
Variational Inference for Gaussian Process Models with Linear Complexity
NIPS 2017
Incremental Variational Sparse Gaussian Process Regression
NIPS 2016