Tengyu Xu

According to our database, Tengyu Xu authored at least 27 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Provably Efficient Offline Reinforcement Learning With Trajectory-Wise Reward.

Tengyu Xu, Yue Wang, Shaofeng Zou, Yingbin Liang

IEEE Trans. Inf. Theory, September, 2024

Faster algorithm and sharper analysis for constrained Markov decision process.

Tianjiao Li, Ziwei Guan, Shaofeng Zou, Tengyu Xu, Yingbin Liang, Guanghui Lan

Oper. Res. Lett., 2024

Multi-IF: Benchmarking LLMs on Multi-Turn and Multilingual Instructions Following.

Yun He, Di Jin, Chaoqi Wang, Chloe Bi, Karishma Mandyam, Hejia Zhang, Chen Zhu, Ning Li, Tengyu Xu, Hongjiang Lv, Shruti Bhosale, Chenguang Zhu, Karthik Abinav Sankararaman, Eryk Helenowski, Melanie Kambadur, Aditya Tayade, Hao Ma, Han Fang, Sinong Wang

CoRR, 2024

The Perfect Blend: Redefining RLHF with Mixture of Judges.

Tengyu Xu, Eryk Helenowski, Karthik Abinav Sankararaman, Di Jin, Kaiyan Peng, Eric Han, Shaoliang Nie, Chen Zhu, Hejia Zhang, Wenxuan Zhou, Zhouhao Zeng, Yun He, Karishma Mandyam, Arya Talabzadeh, Madian Khabsa, Gabriel Cohen, Yuandong Tian, Hao Ma, Sinong Wang, Han Fang

CoRR, 2024

2023

Constraint-based multi-agent reinforcement learning for collaborative tasks.

Xiumin Shang, Tengyu Xu, Ioannis Karamouzas, Marcelo Kallmann

Comput. Animat. Virtual Worlds, 2023

2022

Provably Efficient Offline Reinforcement Learning with Trajectory-Wise Reward.

Tengyu Xu, Yingbin Liang

CoRR, 2022

Deterministic policy gradient: Convergence analysis.

Huaqing Xiong, Tengyu Xu, Lin Zhao, Yingbin Liang, Wei Zhang

Proceedings of the Uncertainty in Artificial Intelligence, 2022

A Unifying Framework of Off-Policy General Value Function Evaluation.

Tengyu Xu, Zhuoran Yang, Zhaoran Wang, Yingbin Liang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Model-Based Offline Meta-Reinforcement Learning with Regularization.

Sen Lin, Jialin Wan, Tengyu Xu, Yingbin Liang, Junshan Zhang

Proceedings of the Tenth International Conference on Learning Representations, 2022

PER-ETD: A Polynomially Efficient Emphatic Temporal Difference Learning Method.

Ziwei Guan, Tengyu Xu, Yingbin Liang

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

A Unified Off-Policy Evaluation Approach for General Value Function.

Tengyu Xu, Zhuoran Yang, Zhaoran Wang, Yingbin Liang

CoRR, 2021

Doubly Robust Off-Policy Actor-Critic: Convergence and Optimality.

Tengyu Xu, Zhuoran Yang, Zhaoran Wang, Yingbin Liang

Proceedings of the 38th International Conference on Machine Learning, 2021

CRPO: A New Approach for Safe Reinforcement Learning with Convergence Guarantee.

Tengyu Xu, Yingbin Liang, Guanghui Lan

Proceedings of the 38th International Conference on Machine Learning, 2021

Proximal Gradient Descent-Ascent: Variable Convergence under KŁ Geometry.

Ziyi Chen, Yi Zhou, Tengyu Xu, Yingbin Liang

Proceedings of the 9th International Conference on Learning Representations, 2021

Sample Complexity Bounds for Two Timescale Value-based Reinforcement Learning Algorithms.

Tengyu Xu, Yingbin Liang

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

When Will Generative Adversarial Imitation Learning Algorithms Attain Global Convergence.

Ziwei Guan, Tengyu Xu, Yingbin Liang

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Non-asymptotic Convergence of Adam-type Reinforcement Learning Algorithms under Markovian Sampling.

Huaqing Xiong, Tengyu Xu, Yingbin Liang, Wei Zhang

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

A Primal Approach to Constrained Policy Optimization: Global Optimality and Finite-Time Analysis.

Tengyu Xu, Yingbin Liang, Guanghui Lan

CoRR, 2020

Enhanced First and Zeroth Order Variance Reduced Algorithms for Min-Max Optimization.

Tengyu Xu, Zhe Wang, Yingbin Liang, H. Vincent Poor

CoRR, 2020

Non-asymptotic Convergence Analysis of Two Time-scale (Natural) Actor-Critic Algorithms.

Tengyu Xu, Zhe Wang, Yingbin Liang

CoRR, 2020

Improving Sample Complexity Bounds for Actor-Critic Algorithms.

Tengyu Xu, Zhe Wang, Yingbin Liang

CoRR, 2020

Improving Sample Complexity Bounds for (Natural) Actor-Critic Algorithms.

Tengyu Xu, Zhe Wang, Yingbin Liang

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Reanalysis of Variance Reduced Temporal Difference Learning.

Tengyu Xu, Zhe Wang, Yi Zhou, Yingbin Liang

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Finite-Sample Analysis for SARSA and Q-Learning with Linear Function Approximation.

Shaofeng Zou, Tengyu Xu, Yingbin Liang

CoRR, 2019

Finite-Sample Analysis for SARSA with Linear Function Approximation.

Shaofeng Zou, Tengyu Xu, Yingbin Liang

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Two Time-scale Off-Policy TD Learning: Non-asymptotic Analysis over Markovian Samples.

Tengyu Xu, Shaofeng Zou, Yingbin Liang

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

Convergence of SGD in Learning ReLU Models with Separable Data.

Tengyu Xu, Yi Zhou, Kaiyi Ji, Yingbin Liang

CoRR, 2018