Nathan Kallus
Title
Cited by
Cited by
Year
Data-driven robust optimization
D Bertsimas, V Gupta, N Kallus
Mathematical Programming 167 (2), 235-292, 2018
3362018
From predictive to prescriptive analytics
D Bertsimas, N Kallus
Management Science 66 (3), 1025-1044, 2020
157*2020
Robust sample average approximation
D Bertsimas, V Gupta, N Kallus
Mathematical Programming 171 (1-2), 217-282, 2018
108*2018
Predicting crowd behavior with big public data
N Kallus
Proceedings of the 23rd International Conference on World Wide Web, 625-630, 2014
862014
Balanced policy evaluation and learning
N Kallus
Advances in neural information processing systems, 8895-8906, 2018
612018
Recursive partitioning for personalization using observational data
N Kallus
International Conference on Machine Learning, 1789-1798, 2017
57*2017
Personalized diabetes management using electronic medical records
D Bertsimas, N Kallus, AM Weinstein, YD Zhuo
Diabetes care 40 (2), 210-217, 2017
562017
Generalized optimal matching methods for causal inference
N Kallus
arXiv preprint arXiv:1612.08321, 2016
55*2016
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
552015
Confounding-robust policy improvement
N Kallus, A Zhou
Advances in neural information processing systems, 9269-9279, 2018
502018
Dynamic assortment personalization in high dimensions
N Kallus, M Udell
Operations Research, 2020
44*2020
Optimal a priori balance in the design of controlled experiments
N Kallus
arXiv preprint arXiv:1312.0531, 2013
422013
Policy evaluation and optimization with continuous treatments
N Kallus, A Zhou
arXiv preprint arXiv:1802.06037, 2018
402018
Residual unfairness in fair machine learning from prejudiced data
N Kallus, A Zhou
arXiv preprint arXiv:1806.02887, 2018
372018
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
322019
The power and limits of predictive approaches to observational-data-driven optimization
D Bertsimas, N Kallus
arXiv preprint arXiv:1605.02347, 2016
25*2016
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
242020
Inventory management in the era of big data
D Bertsimas, N Kallus, A Hussain
Production and Operations Management 25 (12), 2006-2009, 2016
242016
Removing hidden confounding by experimental grounding
N Kallus, AM Puli, U Shalit
Advances in neural information processing systems, 10888-10897, 2018
202018
Scheduling, revenue management, and fairness in an academic-hospital radiology division
R Baum, D Bertsimas, N Kallus
Academic radiology 21 (10), 1322-1330, 2014
202014
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