| Robust Wasserstein profile inference and applications to machine learning J Blanchet, Y Kang, K Murthy Journal of Applied Probability 56 (3), 830-857, 2019 | 278 | 2019 |
| L-dex ratio in detecting breast cancer-related lymphedema: reliability, sensitivity, and specificity MR Fu, CM Cleland, AA Guth, M Kayal, J Haber, F Cartwright, R Kleinman, ... Lymphology 46 (2), 85-96, 2013 | 128 | 2013 |
| Psychosocial impact of living with cancer-related lymphedema MR Fu, Y Kang Seminars in oncology nursing 29 (1), 50-60, 2013 | 66 | 2013 |
| 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 | 45 | 2019 |
| Sample out-of-sample inference based on Wasserstein distance J Blanchet, Y Kang Operations Research 69 (3), 985-1013, 2021 | 31 | 2021 |
| Distributionally Robust Groupwise Regularization Estimator J Blanchet, Y Kang Proceedings of Machine Learning Research 77:97–112, 2017, 2017 | 29 | 2017 |
| Semi‐supervised Learning Based on Distributionally Robust Optimization J Blanchet, Y Kang Data Analysis and Applications 3: Computational, Classification, Financial …, 2020 | 28* | 2020 |
| Breast cancer‐related lymphedema and sexual experiences: a mixed‐method comparison study ME Radina, MR Fu, L Horstman, Y Kang Psycho‐Oncology 24 (12), 1655-1662, 2015 | 24 | 2015 |
| Reassessing the relationship between landscape alteration and aquatic ecosystem degradation from a hydrologically sensitive area perspective Z Qiu, JG Kennen, S Giri, T Walter, Y Kang, Z Zhang Science of the total environment 650, 2850-2862, 2019 | 17 | 2019 |
| Doubly Robust Data-Driven Distributionally Robust Optimization J Blanchet, Y Kang, F Zhang, F He, Z Hu Applied Modeling Techniques and Data Analysis 1, Computational Data Analysis …, 2021 | 16* | 2021 |
| A comparison of DEM‐based indexes for targeting the placement of vegetative buffers in agricultural watersheds MG Dosskey, Z Qiu, Y Kang JAWRA Journal of the American Water Resources Association 49 (6), 1270-1283, 2013 | 14 | 2013 |
| Choosing between alternative placement strategies for conservation buffers using Borda count Z Qiu, MG Dosskey, Y Kang Landscape and Urban Planning 153, 66-73, 2016 | 12 | 2016 |
| Measuring lymphedema symptom burdens: a psychometric study MR Fu, CM Cleland, Y Kang Multinational Association of Supportive Care in Cancer's Annual Meeting …, 2012 | 7 | 2012 |
| Machine Learning's Dropout Training is Distributionally Robust Optimal J Blanchet, Y Kang, JLM Olea, VA Nguyen, X Zhang arXiv preprint arXiv:2009.06111, 2020 | 6 | 2020 |
| A distributionally robust boosting algorithm J Blanchet, F Zhang, Y Kang, Z Hu 2019 Winter Simulation Conference (WSC), 3728-3739, 2019 | 6 | 2019 |
| A macro perspective on the relationship between farm size and agrochemicals use in China L Xie, Z Qiu, L You, Y Kang Sustainability 12 (21), 9299, 2020 | 5 | 2020 |
| Distributionally robust optimization and its applications in machine learning Y Kang Columbia University, 2017 | 3 | 2017 |
| Revealing the sources of arsenic in private well water using Random Forest Classification and Regression S Giri, Y Kang, K MacDonald, M Tippett, Z Qiu, RG Lathrop, CC Obropta Science of The Total Environment 857, 159360, 2023 | 2 | 2023 |
| L-Dex ratio in detecting and diagnosing breast cancer-related lymphedema: Reliability, sensitivity, and specificity. MR Fu, CM Cleland, AA Guth, M Kayal, J Haber, F Cartwright, R Kleinman, ... Journal of Clinical Oncology 31 (26_suppl), 12-12, 2013 | 2 | 2013 |
| Data on four criteria for targeting the placement of conservation buffers in agricultural landscapes Z Qiu, MG Dosskey, Y Kang Data in brief 7, 1254-1257, 2016 | 1 | 2016 |
Jose BlanchetStanford UniversityVerified email at stanford.edu
