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Yang Kang
Yang Kang
Department of Statistics, Columbia University
Zweryfikowany adres z stat.columbia.edu - Strona główna
Tytuł
Cytowane przez
Cytowane przez
Rok
Robust Wasserstein profile inference and applications to machine learning
J Blanchet, Y Kang, K Murthy
Journal of Applied Probability 56 (3), 830-857, 2019
3512019
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, 2013
1402013
Psychosocial impact of living with cancer-related lymphedema
MR Fu, Y Kang
Seminars in oncology nursing 29 (1), 50-60, 2013
782013
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
562019
Semi‐supervised Learning Based on Distributionally Robust Optimization
J Blanchet, Y Kang
Data Analysis and Applications 3: Computational, Classification, Financial …, 2020
38*2020
Sample out-of-sample inference based on Wasserstein distance
J Blanchet, Y Kang
Operations Research 69 (3), 985-1013, 2021
352021
Distributionally Robust Groupwise Regularization Estimator
J Blanchet, Y Kang
Proceedings of Machine Learning Research 77:97–112, 2017, 2017
352017
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
272015
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
242023
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
222019
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
17*2021
Dropout Training is Distributionally Robust Optimal
J Blanchet, Y Kang, JLM Olea, VA Nguyen, X Zhang
Journal of Machine Learning Research 24 (180), 1−60, 2023
15*2023
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
142013
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
122016
A distributionally robust boosting algorithm
J Blanchet, F Zhang, Y Kang, Z Hu
2019 Winter Simulation Conference (WSC), 3728-3739, 2019
102019
Measuring lymphedema symptom burdens: a psychometric study
MR Fu, CM Cleland, Y Kang
Multinational Association of Supportive Care in Cancer's Annual Meeting …, 2012
72012
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
52020
Distributionally robust optimization and its applications in machine learning
Y Kang
Columbia University, 2017
52017
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
32013
Psychosocial impact of lymphedema
M Fu, SH Ridner, M Kayal, Y Kang, CM Qiu
LymphLink 26 (1), 31-33, 2014
22014
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