5 citations · 6 across the 5 of their papers we have counts for
5 papers
Generative and Nonparametric Approaches for Conditional Distribution Estimation: Methods, Perspectives, and Comparative Evaluations
Yen-Shiu Chin, Zhi-Yu Jou, Toshinari Morimoto +5
The inference of conditional distributions is a fundamental problem in statistics, essential for prediction, uncertainty quantification, and probabilistic modeling. A wide range of…
The -PCA Framework: A Unified and Efficiency-Preserving Approach with Robust Variants
Hung Hung, Zhi-Yu Jou, Su-Yun Huang +1
Principal component analysis (PCA) is a fundamental tool in multivariate statistics, yet its sensitivity to outliers and limitations in distributed environments restrict its effect…
A Generalized Mean Approach for Distributed-PCA
Zhi-Yu Jou, Su-Yun Huang, Hung Hung +1
Principal component analysis (PCA) is a widely used technique for dimension reduction. As datasets continue to grow in size, distributed-PCA (DPCA) has become an active research ar…
Robust mislabel logistic regression without modeling mislabel probabilities
Hung Hung, Zhi-Yu Jou, Su-Yun Huang
Logistic regression is among the most widely used statistical methods for linear discriminant analysis. In many applications, we only observe possibly mislabeled responses. Fitting…
A low-rank based estimation-testing procedure for matrix-covariate regression
Hung Hung, Zhi-Yu Jou
Matrix-covariate is now frequently encountered in many biomedical researches. It is common to fit conventional statistical models by vectorizing matrix-covariate. This strategy, ho…