Siliang Zeng
Orcid: 0009-0002-5863-8659
According to our database1,
Siliang Zeng
authored at least 17 papers
between 2006 and 2024.
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Bibliography
2024
Joint Demonstration and Preference Learning Improves Policy Alignment with Human Feedback.
CoRR, 2024
Getting More Juice Out of the SFT Data: Reward Learning from Human Demonstration Improves SFT for LLM Alignment.
CoRR, 2024
2023
Understanding Expertise through Demonstrations: A Maximum Likelihood Framework for Offline Inverse Reinforcement Learning.
CoRR, 2023
When Demonstrations meet Generative World Models: A Maximum Likelihood Framework for Offline Inverse Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
ProfLLM: A framework for adapting offline large language models to few-shot expert knowledge.
Proceedings of the 4th International Conference on Artificial Intelligence and Computer Engineering, 2023
Proceedings of the Conference on Robot Learning, 2023
2022
SIAM J. Optim., December, 2022
Structural Estimation of Markov Decision Processes in High-Dimensional State Space with Finite-Time Guarantees.
CoRR, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
A Stochastic Linearized Augmented Lagrangian Method for Decentralized Bilevel Optimization.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Learning to Coordinate in Multi-Agent Systems: A Coordinated Actor-Critic Algorithm and Finite-Time Guarantees.
Proceedings of the Learning for Dynamics and Control Conference, 2022
2021
A Momentum-Assisted Single-Timescale Stochastic Approximation Algorithm for Bilevel Optimization.
CoRR, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
2020
Multi-Agent Reinforcement Learning for Adaptive Routing: A Hybrid Method using Eligibility Traces.
Proceedings of the 16th IEEE International Conference on Control & Automation, 2020
Network-Level System Performance Prediction Using Deep Neural Networks with Cross-Layer Information.
Proceedings of the 2020 IEEE International Conference on Communications, 2020
2006
Proceedings of the 2006 International Conference on Semantics, 2006