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Nathan Kallus
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연도
Data-driven robust optimization
D Bertsimas, V Gupta, N Kallus
Mathematical Programming 167 (2), 235-292, 2018
5502018
From predictive to prescriptive analytics
D Bertsimas, N Kallus
Management Science 66 (3), 1025-1044, 2020
3992020
Robust sample average approximation
D Bertsimas, V Gupta, N Kallus
Mathematical Programming 171 (1), 217-282, 2018
209*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
1772019
Balanced policy evaluation and learning
N Kallus
Advances in neural information processing systems 31, 2018
1262018
Confounding-robust policy improvement
N Kallus, A Zhou
Advances in neural information processing systems 31, 2018
1202018
Predicting crowd behavior with big public data
N Kallus
Proceedings of the 23rd International Conference on World Wide Web, 625-630, 2014
1152014
Double reinforcement learning for efficient off-policy evaluation in markov decision processes
N Kallus, M Uehara
Journal of Machine Learning Research 21 (167), 2020
1142020
Personalized diabetes management using electronic medical records
D Bertsimas, N Kallus, AM Weinstein, YD Zhuo
Diabetes care 40 (2), 210-217, 2017
1132017
Residual unfairness in fair machine learning from prejudiced data
N Kallus, A Zhou
International Conference on Machine Learning, 2439-2448, 2018
982018
Recursive partitioning for personalization using observational data
N Kallus
International conference on machine learning, 1789-1798, 2017
93*2017
Assessing algorithmic fairness with unobserved protected class using data combination
N Kallus, X Mao, A Zhou
Management Science 68 (3), 1959-1981, 2022
872022
Policy evaluation and optimization with continuous treatments
N Kallus, A Zhou
International conference on artificial intelligence and statistics, 1243-1251, 2018
872018
Dynamic assortment personalization in high dimensions
N Kallus, M Udell
Operations Research 68 (4), 1020-1037, 2020
85*2020
Generalized optimal matching methods for causal inference.
N Kallus
J. Mach. Learn. Res. 21, 62:1-62:54, 2020
852020
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
842015
Removing hidden confounding by experimental grounding
N Kallus, AM Puli, U Shalit
Advances in neural information processing systems 31, 2018
782018
Optimal a priori balance in the design of controlled experiments
N Kallus
Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2018
772018
Efficiently breaking the curse of horizon: Double reinforcement learning in infinite-horizon processes
N Kallus, M Uehara
arXiv preprint arXiv:1909.05850 3, 2019
65*2019
Deep generalized method of moments for instrumental variable analysis
A Bennett, N Kallus, T Schnabel
Advances in neural information processing systems 32, 2019
632019
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학술자료 1–20