עקוב אחר
Nan Jiang
Nan Jiang
Associate Professor of Computer Science, UIUC
כתובת אימייל מאומתת בדומיין illinois.edu - דף הבית
כותרת
צוטט על ידי
צוטט על ידי
שנה
Doubly Robust Off-policy Value Evaluation for Reinforcement Learning‏
N Jiang, L Li‏
Proceedings of the 33rd International Conference on Machine Learning (ICML-16), 2015‏
8862015
Contextual Decision Processes with Low Bellman Rank are PAC-Learnable‏
N Jiang, A Krishnamurthy, A Agarwal, J Langford, RE Schapire‏
Proceedings of the 34th International Conference on Machine Learning (ICML-17), 2016‏
5152016
Information-Theoretic Considerations in Batch Reinforcement Learning‏
J Chen, N Jiang‏
Proceedings of the 36th International Conference on Machine Learning (ICML …, 2019‏
4352019
Reinforcement Learning: Theory and Algorithms‏
A Agarwal, N Jiang, SM Kakade‏
3402019
Bellman-consistent pessimism for offline reinforcement learning‏
T Xie, CA Cheng, N Jiang, P Mineiro, A Agarwal‏
Advances in neural information processing systems 34, 6683-6694, 2021‏
3052021
Model-based RL in Contextual Decision Processes: PAC bounds and Exponential Improvements over Model-free Approaches‏
W Sun, N Jiang, A Krishnamurthy, A Agarwal, J Langford‏
Conference on Learning Theory, 2019‏
2862019
Provably efficient RL with Rich Observations via Latent State Decoding‏
SS Du, A Krishnamurthy, N Jiang, A Agarwal, M Dudík, J Langford‏
Proceedings of the 36th International Conference on Machine Learning (ICML …, 2019‏
2832019
Hierarchical Imitation and Reinforcement Learning‏
HM Le, N Jiang, A Agarwal, M Dudík, Y Yue, H Daumé III‏
Proceedings of the 35th International Conference on Machine Learning (ICML-18), 2018‏
2442018
Minimax Weight and Q-Function Learning for Off-Policy Evaluation‏
M Uehara, J Huang, N Jiang‏
arXiv preprint arXiv:1910.12809, 2019‏
2062019
Policy finetuning: Bridging sample-efficient offline and online reinforcement learning‏
T Xie, N Jiang, H Wang, C Xiong, Y Bai‏
Advances in neural information processing systems 34, 27395-27407, 2021‏
1922021
The Dependence of Effective Planning Horizon on Model Accuracy‏
N Jiang, A Kulesza, S Singh, R Lewis‏
Proceedings of the 2015 International Conference on Autonomous Agents and …, 2015‏
1782015
Empirical study of off-policy policy evaluation for reinforcement learning‏
C Voloshin, HM Le, N Jiang, Y Yue‏
arXiv preprint arXiv:1911.06854, 2019‏
1712019
Sample complexity of reinforcement learning using linearly combined model ensembles‏
A Modi, N Jiang, A Tewari, S Singh‏
International Conference on Artificial Intelligence and Statistics, 2010-2020, 2020‏
1652020
Iterative preference learning from human feedback: Bridging theory and practice for rlhf under kl-constraint‏
W Xiong, H Dong, C Ye, Z Wang, H Zhong, H Ji, N Jiang, T Zhang‏
Forty-first International Conference on Machine Learning, 2024‏
156*2024
Adversarially trained actor critic for offline reinforcement learning‏
CA Cheng, T Xie, N Jiang, A Agarwal‏
International Conference on Machine Learning, 3852-3878, 2022‏
1522022
On Oracle-Efficient PAC Reinforcement Learning with Rich Observations‏
C Dann, N Jiang, A Krishnamurthy, A Agarwal, J Langford, RE Schapire‏
Advances in Neural Information Processing Systems, 2018, 2018‏
1402018
Batch value-function approximation with only realizability‏
T Xie, N Jiang‏
International Conference on Machine Learning, 11404-11413, 2021‏
1322021
Offline reinforcement learning with realizability and single-policy concentrability‏
W Zhan, B Huang, A Huang, N Jiang, J Lee‏
Conference on Learning Theory, 2730-2775, 2022‏
1312022
Provably efficient q-learning with low switching cost‏
Y Bai, T Xie, N Jiang, YX Wang‏
Advances in Neural Information Processing Systems, 8004-8013, 2019‏
1202019
Q* approximation schemes for batch reinforcement learning: A theoretical comparison‏
T Xie, N Jiang‏
Conference on Uncertainty in Artificial Intelligence, 550-559, 2020‏
1122020
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מאמרים 1–20