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Ye Tian
Ye Tian
Ph.D. Student in Statistics, Columbia University
Verified email at columbia.edu - Homepage
Title
Cited by
Cited by
Year
Transfer learning under high-dimensional generalized linear models
Y Tian, Y Feng
Journal of the American Statistical Association 118 (544), 2684-2697, 2023
1142023
RaSE: Random subspace ensemble classification
Y Tian, Y Feng
Journal of Machine Learning Research 22, 1-93, 2021
392021
Learning from similar linear representations: Adaptivity, minimaxity, and robustness
Y Tian, Y Gu, Y Feng
arXiv preprint arXiv:2303.17765, 2023
152023
Unsupervised multi-task and transfer learning on gaussian mixture models
Y Tian, H Weng, Y Feng
arXiv preprint arXiv:2209.15224, 2022
132022
Rase: A variable screening framework via random subspace ensembles
Y Tian, Y Feng
Journal of the American Statistical Association 118 (541), 457-468, 2023
122023
Neyman-pearson multi-class classification via cost-sensitive learning
Y Tian, Y Feng
Journal of the American Statistical Association, 1-23, 2024
72024
Towards the Theory of Unsupervised Federated Learning: Non-asymptotic Analysis of Federated EM Algorithms
Y Tian, H Weng, Y Feng
Forty-first International Conference on Machine Learning, 2024
5*2024
Thors: An efficient approach for making classifiers cost-sensitive
Y Tian, W Zhang
IEEE Access 7, 97704-97718, 2019
42019
A Multilayer Correlated Topic Model
Y Tian
arXiv preprint arXiv:2101.02028, 2021
22021
Federated Transfer Learning with Differential Privacy
M Li, Y Tian, Y Feng, Y Yu
arXiv preprint arXiv:2403.11343, 2024
12024
Comments on: Statistical inference and large-scale multiple testing for high-dimensional regression models
Y Tian, Y Feng
Test 32 (4), 1172-1176, 2023
12023
L1‐Penalized Multinomial Regression: Estimation, Inference, and Prediction, With an Application to Risk Factor Identification for Different Dementia Subtypes
Y Tian, H Rusinek, AV Masurkar, Y Feng
Statistics in Medicine, 2024
2024
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Articles 1–12