Data-driven distributionally robust optimization using the Wasserstein metric: Performance guarantees and tractable reformulations P Mohajerin Esfahani, D Kuhn Mathematical Programming 171 (1), 115-166, 2018 | 1662 | 2018 |
Distributionally robust convex optimization W Wiesemann, D Kuhn, M Sim Operations research 62 (6), 1358-1376, 2014 | 1004 | 2014 |
Distributionally robust joint chance constraints with second-order moment information S Zymler, D Kuhn, B Rustem Mathematical Programming 137, 167-198, 2013 | 656 | 2013 |
Robust Markov Decision Processes W Wiesemann, D Kuhn, B Rustem Mathematics of Operations Research, 2010 | 457 | 2010 |
Wasserstein distributionally robust optimization: Theory and applications in machine learning D Kuhn, PM Esfahani, VA Nguyen, S Shafieezadeh-Abadeh Operations research & management science in the age of analytics, 130-166, 2019 | 448 | 2019 |
Distributionally robust logistic regression S Shafieezadeh Abadeh, PM Mohajerin Esfahani, D Kuhn Advances in neural information processing systems 28, 2015 | 345 | 2015 |
Primal and dual linear decision rules in stochastic and robust optimization D Kuhn, W Wiesemann, A Georghiou Mathematical Programming 130, 177-209, 2011 | 333 | 2011 |
Regularization via mass transportation S Shafieezadeh-Abadeh, D Kuhn, PM Esfahani Journal of Machine Learning Research 20 (103), 1-68, 2019 | 228 | 2019 |
Conic programming reformulations of two-stage distributionally robust linear programs over Wasserstein balls GA Hanasusanto, D Kuhn Operations Research 66 (3), 849-869, 2018 | 206 | 2018 |
K-Adaptability in Two-Stage Robust Binary Programming GA Hanasusanto, D Kuhn, W Wiesemann Operations Research 63 (4), 877-891, 2015 | 203 | 2015 |
Distributionally robust control of constrained stochastic systems BPG Van Parys, D Kuhn, PJ Goulart, M Morari IEEE Transactions on Automatic Control 61 (2), 430-442, 2015 | 194 | 2015 |
Generalized decision rule approximations for stochastic programming via liftings A Georghiou, W Wiesemann, D Kuhn Mathematical Programming 152, 301-338, 2015 | 192 | 2015 |
A distributionally robust perspective on uncertainty quantification and chance constrained programming GA Hanasusanto, V Roitch, D Kuhn, W Wiesemann Mathematical Programming 151, 35-62, 2015 | 188 | 2015 |
Data-driven chance constrained programs over Wasserstein balls Z Chen, D Kuhn, W Wiesemann Operations Research 72 (1), 410-424, 2024 | 182 | 2024 |
Worst-case value at risk of nonlinear portfolios S Zymler, D Kuhn, B Rustem Management Science 59 (1), 172-188, 2013 | 167 | 2013 |
Distributionally robust multi-item newsvendor problems with multimodal demand distributions GA Hanasusanto, D Kuhn, SW Wallace, S Zymler Mathematical Programming 152 (1), 1-32, 2015 | 165 | 2015 |
Ambiguous joint chance constraints under mean and dispersion information GA Hanasusanto, V Roitch, D Kuhn, W Wiesemann Operations Research 65 (3), 751-767, 2017 | 158 | 2017 |
From data to decisions: Distributionally robust optimization is optimal BPG Van Parys, PM Esfahani, D Kuhn Management Science 67 (6), 3387-3402, 2021 | 147 | 2021 |
Data-driven inverse optimization with imperfect information P Mohajerin Esfahani, S Shafieezadeh-Abadeh, GA Hanasusanto, ... Mathematical Programming 167, 191-234, 2018 | 135 | 2018 |
Maximizing the net present value of a project under uncertainty W Wiesemann, D Kuhn, B Rustem European Journal of Operational Research 202 (2), 356-367, 2010 | 117 | 2010 |