| Data-driven robust optimization D Bertsimas, V Gupta, N Kallus Mathematical Programming 167 (2), 235-292, 2018 | 366 | 2018 |
| From predictive to prescriptive analytics D Bertsimas, N Kallus Management Science 66 (3), 1025-1044, 2020 | 192* | 2020 |
| Robust sample average approximation D Bertsimas, V Gupta, N Kallus Mathematical Programming 171 (1), 217-282, 2018 | 119* | 2018 |
| Predicting crowd behavior with big public data N Kallus Proceedings of the 23rd International Conference on World Wide Web, 625-630, 2014 | 90 | 2014 |
| Balanced policy evaluation and learning N Kallus Advances in neural information processing systems 31, 2018 | 81 | 2018 |
| Personalized diabetes management using electronic medical records D Bertsimas, N Kallus, AM Weinstein, YD Zhuo Diabetes care 40 (2), 210-217, 2017 | 74 | 2017 |
| Generalized optimal matching methods for causal inference. N Kallus Journal of Machine Learning Research 21 (62), 1-54, 2020 | 66* | 2020 |
| Recursive partitioning for personalization using observational data N Kallus International Conference on Machine Learning, 1789-1798, 2017 | 64* | 2017 |
| The power of optimization over randomization in designing experiments involving small samples D Bertsimas, M Johnson, N Kallus Operations Research 63 (4), 868-876, 2015 | 60 | 2015 |
| Confounding-robust policy improvement N Kallus, A Zhou arXiv preprint arXiv:1805.08593, 2018 | 59 | 2018 |
| Policy evaluation and optimization with continuous treatments N Kallus, A Zhou International Conference on Artificial Intelligence and Statistics, 1243-1251, 2018 | 54 | 2018 |
| Fairness under unawareness: Assessing disparity when protected class is unobserved J Chen, N Kallus, X Mao, G Svacha, M Udell Proceedings of the conference on fairness, accountability, and transparency …, 2019 | 52 | 2019 |
| Residual unfairness in fair machine learning from prejudiced data N Kallus, A Zhou International Conference on Machine Learning, 2439-2448, 2018 | 51 | 2018 |
| Optimal a priori balance in the design of controlled experiments N Kallus arXiv preprint arXiv:1312.0531, 2013 | 47 | 2013 |
| Double reinforcement learning for efficient off-policy evaluation in markov decision processes N Kallus, M Uehara Journal of Machine Learning Research 21 (167), 1-63, 2020 | 45 | 2020 |
| Efficiently breaking the curse of horizon: Double reinforcement learning in infinite-horizon processes N Kallus, M Uehara arXiv preprint arXiv:1909.05850, 2019 | 35* | 2019 |
| Dynamic assortment personalization in high dimensions N Kallus, M Udell arXiv preprint arXiv:1610.05604, 2016 | 31 | 2016 |
| Inventory management in the era of big data D Bertsimas, N Kallus, A Hussain Production and Operations Management 25 (12), 2006-2009, 2016 | 30 | 2016 |
| Deep generalized method of moments for instrumental variable analysis A Bennett, N Kallus, T Schnabel arXiv preprint arXiv:1905.12495, 2019 | 28 | 2019 |
| Intrinsically efficient, stable, and bounded off-policy evaluation for reinforcement learning N Kallus, M Uehara arXiv preprint arXiv:1906.03735, 2019 | 27 | 2019 |
