3 papers
stat.ME2025
Robust and Well-conditioned Sparse Estimation for High-dimensional Covariance Matrices
Shaoxin Wang, Ziyun Ma
Estimating covariance matrices with high-dimensional complex data presents significant challenges, particularly concerning positive definiteness, sparsity, and numerical stability.…
stat.ML2025
-norm Regularized Indefinite Kernel Logistic Regression
Shaoxin Wang, Hanjing Yao
Kernel logistic regression (KLR) is a powerful classification method widely applied across diverse domains. In many real-world scenarios, indefinite kernels capture more domain-spe…
stat.ME2025
A Bayesian Sparse Kronecker Product Decomposition Framework for Tensor Predictors with Mixed-Type Responses
Shao-Hsuan Wang, Hsin-Hsiung Huang
Ultra-high-dimensional tensor predictors are increasingly common in neuroimaging and other biomedical studies, yet existing methods rarely integrate continuous, count, and binary r…