Nan Jiang
Nan Jiang
Assistant Professor of Computer Science, UIUC
E-mail confirmado em illinois.edu - Página inicial
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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
2392015
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
1102016
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
702018
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
682015
Information-Theoretic Considerations in Batch Reinforcement Learning
J Chen, N Jiang
Proceedings of the 36th International Conference on Machine Learning (ICML …, 2019
502019
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
43*2019
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
402019
Abstraction Selection in Model-based Reinforcement Learning
N Jiang, A Kulesza, S Singh
Proceedings of the 32nd International Conference on Machine Learning (ICML …, 2015
392015
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
35*2018
Repeated Inverse Reinforcement Learning
K Amin, N Jiang, S Singh
Advances in Neural Information Processing Systems, 2017, 2017
352017
Improving UCT planning via approximate homomorphisms
N Jiang, S Singh, R Lewis
Proceedings of the 2014 international conference on Autonomous agents and …, 2014
312014
Minimax Weight and Q-Function Learning for Off-Policy Evaluation
M Uehara, J Huang, N Jiang
arXiv preprint arXiv:1910.12809, 2019
252019
Low-Rank Spectral Learning with Weighted Loss Functions
A Kulesza, N Jiang, S Singh
Proceedings of the 18th International Conference on Artificial Intelligence …, 2015
252015
Open Problem: The Dependence of Sample Complexity Lower Bounds on Planning Horizon
N Jiang, A Agarwal
Conference On Learning Theory, 3395-3398, 2018
222018
Spectral learning of predictive state representations with insufficient statistics
A Kulesza, N Jiang, S Singh
Proceedings of the 29th AAAI Conference on Artificial Intelligence, 2015
182015
Markov decision processes with continuous side information
A Modi, N Jiang, S Singh, A Tewari
Algorithmic Learning Theory, 597-618, 2018
152018
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
122019
Improving predictive state representations via gradient descent
N Jiang, A Kulesza, S Singh
30th AAAI Conference on Artificial Intelligence, 2016
122016
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
92020
Reinforcement Learning: Theory and Algorithms
A Agarwal, N Jiang, SM Kakade
92019
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