17 citations · 49 across the 13 of their papers we have counts for
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stat.ML2023
Towards the Theory of Unsupervised Federated Learning: Non-asymptotic Analysis of Federated EM Algorithms
Ye Tian, Haolei Weng, Yang Feng
While supervised federated learning approaches have enjoyed significant success, the domain of unsupervised federated learning remains relatively underexplored. Several federated E…
stat.ML2023★ 3 cited
Learning from Similar Linear Representations: Adaptivity, Minimaxity, and Robustness
Ye Tian, Yuqi Gu, Yang Feng
Representation multi-task learning (MTL) has achieved tremendous success in practice. However, the theoretical understanding of these methods is still lacking. Most existing theore…
stat.ME2023★ 3 cited
-penalized Multinomial Regression: Estimation, inference, and prediction, with an application to risk factor identification for different dementia subtypes
Ye Tian, Henry Rusinek, Arjun V. Masurkar +1
High-dimensional multinomial regression models are very useful in practice but have received less research attention than logistic regression models, especially from the perspectiv…