Speaker：

Xinyu Zhang (CAS)

Time：

Thur., 16:00-17:00, Mar. 27, 2025

Venue：

B725, Shuangqing Complex Building A

Abstract:

This paper studies the general framework of representation learning and develops a frequentist model averaging framework to combine different representation learning methods. The weight choice criterion is K-fold cross-validation criterion. We prove the asymptotic optimality and the weight consistency. Numerical studies and real-data analysis demonstrate the superior performance of the proposed method.