Doubly robust off-policy value evaluation for reinforcement learning N Jiang, L Li International conference on machine learning, 652-661, 2016 | 824 | 2016 |
The global survival rate among adult out-of-hospital cardiac arrest patients who received cardiopulmonary resuscitation: a systematic review and meta-analysis S Yan, Y Gan, N Jiang, R Wang, Y Chen, Z Luo, Q Zong, S Chen, C Lv Critical care 24, 1-13, 2020 | 641 | 2020 |
Micro-or small-gas turbines TW Simon, N Jiang Proc. Int. Gas Turbine Congress, 2-7, 2003 | 445 | 2003 |
Contextual decision processes with low bellman rank are pac-learnable N Jiang, A Krishnamurthy, A Agarwal, J Langford, RE Schapire International Conference on Machine Learning, 1704-1713, 2017 | 443 | 2017 |
High-silica zeolites for adsorption of organic micro-pollutants in water treatment: A review N Jiang, R Shang, SGJ Heijman, LC Rietveld Water research 144, 145-161, 2018 | 422 | 2018 |
Multi-sensor information fusion based on machine learning for real applications in human activity recognition: State-of-the-art and research challenges S Qiu, H Zhao, N Jiang, Z Wang, L Liu, Y An, H Zhao, X Miao, R Liu, ... Information Fusion 80, 241-265, 2022 | 371 | 2022 |
Information-theoretic considerations in batch reinforcement learning J Chen, N Jiang International Conference on Machine Learning, 1042-1051, 2019 | 363 | 2019 |
Provably efficient rl with rich observations via latent state decoding S Du, A Krishnamurthy, N Jiang, A Agarwal, M Dudik, J Langford International Conference on Machine Learning, 1665-1674, 2019 | 250 | 2019 |
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 | 236 | 2021 |
Reinforcement learning: Theory and algorithms A Agarwal, N Jiang, SM Kakade, W Sun CS Dept., UW Seattle, Seattle, WA, USA, Tech. Rep 32, 96, 2019 | 236 | 2019 |
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, 2898-2933, 2019 | 231 | 2019 |
Synergetic degradation of Acid Orange 7 (AO7) dye by DBD plasma and persulfate K Shang, X Wang, J Li, H Wang, N Lu, N Jiang, Y Wu Chemical Engineering Journal 311, 378-384, 2017 | 219 | 2017 |
Electrodeposited nickel-sulfide films as competent hydrogen evolution catalysts in neutral water N Jiang, L Bogoev, M Popova, S Gul, J Yano, Y Sun Journal of Materials Chemistry A 2 (45), 19407-19414, 2014 | 214 | 2014 |
Enhanced catalytic performance of graphene-TiO2 nanocomposites for synergetic degradation of fluoroquinolone antibiotic in pulsed discharge plasma system H Guo, N Jiang, H Wang, K Shang, N Lu, J Li, Y Wu Applied Catalysis B: Environmental 248, 552-566, 2019 | 209 | 2019 |
Hierarchical imitation and reinforcement learning H Le, N Jiang, A Agarwal, M Dudík, Y Yue, H Daumé III International conference on machine learning, 2917-2926, 2018 | 201 | 2018 |
Atmospheric pressure plasma jet: Effect of electrode configuration, discharge behavior, and its formation mechanism N Jiang, A Ji, Z Cao Journal of Applied Physics 106 (1), 2009 | 192 | 2009 |
Particle image velocimetry measurement of indoor airflow field: A review of the technologies and applications X Cao, J Liu, N Jiang, Q Chen Energy and Buildings 69, 367-380, 2014 | 184 | 2014 |
Minimax weight and q-function learning for off-policy evaluation M Uehara, J Huang, N Jiang International Conference on Machine Learning, 9659-9668, 2020 | 178 | 2020 |
Prevalence and associated factors of antenatal depression: Systematic reviews and meta-analyses X Yin, N Sun, N Jiang, X Xu, Y Gan, J Zhang, L Qiu, C Yang, X Shi, ... Clinical psychology review 83, 101932, 2021 | 163 | 2021 |
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 | 157 | 2015 |