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cs.LG2026
A Decomposition Framework for Certifiably Optimal Orthogonal Sparse PCA
Difei Cheng, Qiao Hu
Sparse Principal Component Analysis (SPCA) is an important technique for high-dimensional data analysis, improving interpretability by imposing sparsity on principal components. Ho…
cs.LG2025
Online AUC Optimization Based on Second-order Surrogate Loss
JunRu Luo, Difei Cheng, Bo Zhang
The Area Under the Curve (AUC) is an important performance metric for classification tasks, particularly in class-imbalanced scenarios. However, minimizing the AUC presents signifi…
cs.LG2025
Stochastic Gradient Descent in Non-Convex Problems: Asymptotic Convergence with Relaxed Step-Size via Stopping Time Methods
Ruinan Jin, Difei Cheng, Hong Qiao +3
Stochastic Gradient Descent (SGD) is widely used in machine learning research. Previous convergence analyses of SGD under the vanishing step-size setting typically require Robbins-…