| Quantifying distributional model risk via optimal transport J Blanchet, K Murthy Mathematics of Operations Research 44 (2), 565-600, 2019 | 313 | 2019 |
| Robust Wasserstein profile inference and applications to machine learning J Blanchet, Y Kang, K Murthy Journal of Applied Probability 56 (3), 830-857, 2019 | 281 | 2019 |
| Data-driven optimal transport cost selection for distributionally robust optimization J Blanchet, Y Kang, K Murthy, F Zhang 2019 winter simulation conference (WSC), 3740-3751, 2019 | 46 | 2019 |
| Optimal transport-based distributionally robust optimization: Structural properties and iterative schemes J Blanchet, K Murthy, F Zhang Mathematics of Operations Research 47 (2), 1500-1529, 2022 | 45 | 2022 |
| Confidence regions in Wasserstein distributionally robust estimation J Blanchet, K Murthy, N Si Biometrika 109 (2), 295-315, 2022 | 39 | 2022 |
| On distributionally robust extreme value analysis J Blanchet, F He, K Murthy Extremes 23, 317-347, 2020 | 32 | 2020 |
| Statistical analysis of Wasserstein distributionally robust estimators J Blanchet, K Murthy, VA Nguyen Tutorials in Operations Research: Emerging Optimization Methods and Modeling …, 2021 | 17 | 2021 |
| State-independent importance sampling for random walks with regularly varying increments KRA Murthy, S Juneja, J Blanchet Stochastic Systems 4 (2), 321-374, 2015 | 10 | 2015 |
| Exact simulation of multidimensional reflected Brownian motion J Blanchet, K Murthy Journal of Applied Probability 55 (1), 137-156, 2018 | 9 | 2018 |
| Testing group fairness via optimal transport projections N Si, K Murthy, J Blanchet, VA Nguyen International Conference on Machine Learning, 9649-9659, 2021 | 8 | 2021 |
| Tail asymptotics for delay in a half-loaded GI/GI/2 queue with heavy-tailed job sizes J Blanchet, KR A. Murthy Queueing Systems 81, 301-340, 2015 | 7 | 2015 |
| Exploiting partial correlations in distributionally robust optimization D Padmanabhan, K Natarajan, K Murthy Mathematical Programming 186, 209-255, 2021 | 5 | 2021 |
| Optimizing tail risks using an importance sampling based extrapolation for heavy-tailed objectives A Deo, K Murthy 2020 59th IEEE Conference on Decision and Control (CDC), 1070-1077, 2020 | 4 | 2020 |
| Exact simulation of multidimensional reflected Brownian motion J Blanchet, KRA Murthy arXiv preprint arXiv:1405.6469, 2014 | 4 | 2014 |
| Efficient black-box importance sampling for VaR and CVaR estimation A Deo, K Murthy 2021 Winter Simulation Conference (WSC), 1-12, 2021 | 3 | 2021 |
| Achieving efficiency in black box simulation of distribution tails with self-structuring importance samplers A Deo, K Murthy arXiv preprint arXiv:2102.07060, 2021 | 3 | 2021 |
| The Limit of the Marginal Distribution Model in Consumer Choice Y Ruan, X Li, K Murthy, K Natarajan arXiv preprint arXiv:2208.06115, 2022 | 2 | 2022 |
| Incorporating views on marginal distributions in the calibration of risk models S Dey, S Juneja, KRA Murthy Operations Research Letters 43 (1), 46-51, 2015 | 2 | 2015 |
| State-independent Importance Sampling for Random Walks with Independent Increments KRA Murthy, S Juneja, J Blanchet Preprint, 2013 | 2 | 2013 |
| Admission Control in the Presence of Arrival Forecasts with Blocking-Based Policy Optimization K Murthy, D Padmanabhan, S Bhat 2022 Winter Simulation Conference (WSC), 2270-2281, 2022 | 1 | 2022 |
Jose BlanchetStanford UniversityVerified email at stanford.edu
