Bayesian marginal inference via candidate's formula. - Chuhsing Kate Hsiao; Su-Yun Huang; Ching-Wei Chang (Stat. Comput., 2004)

Model selection for support vector machines via uniform design. - Chien-Ming Huang 002; Yuh-Jye Lee; Dennis K. J. Lin; Su-Yun Huang (Comput. Stat. Data Anal., 2007)

Reduced Support Vector Machines: A Statistical Theory. - Yuh-Jye Lee; Su-Yun Huang (IEEE Trans. Neural Networks, 2007)

A new regularized least squares support vector regression for gene selection. - Pei-Chun Chen; Su-Yun Huang; Wei J. Chen; Chuhsing Kate Hsiao (BMC Bioinform., 2009)

Robust Kernel Principal Component Analysis. - Su-Yun Huang; Yi-Ren Yeh; Shinto Eguchi (Neural Comput., 2009)

Nonlinear Dimension Reduction with Kernel Sliced Inverse Regression. - Yi-Ren Yeh; Su-Yun Huang; Yuh-Jye Lee (IEEE Trans. Knowl. Data Eng., 2009)

Multiclass support vector classification via coding and regression. - Pei-Chun Chen; Kuang-Yao Lee; Tsung-Ju Lee; Yuh-Jye Lee; Su-Yun Huang (Neurocomputing, 2010)

Statistical Analysis of Biomarkers for Personalized Medicine. - Shinto Eguchi; Shigeyuki Matsui; Su-Yun Huang; Chuhsing Kate Hsiao (Comput. Math. Methods Medicine, 2013)

Robust Independent Component Analysis via Minimum Gamma -Divergence Estimation. - Pengwen Chen; Hung Hung; Osamu Komori; Su-Yun Huang; Shinto Eguchi (IEEE J. Sel. Top. Signal Process., 2013)

Asymptotic error bounds for kernel-based Nyström low-rank approximation matrices. - Lo-Bin Chang; Zhidong Bai; Su-Yun Huang; Chii-Ruey Hwang (J. Multivar. Anal., 2013)

On the weak convergence and Central Limit Theorem of blurring and nonblurring processes with application to robust location estimation. - Ting-Li Chen; Hironori Fujisawa; Su-Yun Huang; Chii-Ruey Hwang (J. Multivar. Anal., 2016)

2SDR: Applying Kronecker Envelope PCA to denoise Cryo-EM Images. - Szu-Chi Chung; Po-Yao Niu; Su-Yun Huang; Wei-Hau Chang; I-Ping Tu (CoRR, 2019)

The generalized degrees of freedom of multilinear principal component analysis. - I-Ping Tu; Su-Yun Huang; Dai-Ni Hsieh (J. Multivar. Anal., 2019)

Altered Functional Complexity Associated with Structural Features in Schizophrenic Brain: A Resting-state fMRI Study. - Yi-Ju Lee; Su-Yun Huang; Shih-Jen Tsai; Albert C. Yang (COMPLEXIS, 2020)

TensorProjection Layer: A Tensor-Based Dimensionality Reduction Method in CNN. - Toshinari Morimoto; Su-Yun Huang (CoRR, 2020)

On asymptotic normality of cross data matrix-based PCA in high dimension low sample size. - Shao-Hsuan Wang; Su-Yun Huang; Ting-Li Chen (J. Multivar. Anal., 2020)

On the asymptotic normality and efficiency of Kronecker envelope principal component analysis. - Shih-Hao Huang; Su-Yun Huang (J. Multivar. Anal., 2021)

Robust Aggregation for Federated Learning by Minimum γ-Divergence Estimation. - Cen-Jhih Li; Pin-Han Huang; Yi-Ting Ma; Hung Hung; Su-Yun Huang (Entropy, 2022)

Perturbation theory for cross data matrix-based PCA. - Shao-Hsuan Wang; Su-Yun Huang (J. Multivar. Anal., 2022)

Robust Self-Tuning Semiparametric PCA for Contaminated Elliptical Distribution. - Hung Hung; Su-Yun Huang; Shinto Eguchi (IEEE Trans. Signal Process., 2022)

A Generalized Mean Approach for Distributed-PCA. - Zhi-Yu Jou; Su-Yun Huang; Hung Hung; Shinto Eguchi (CoRR, 2024)

A Geometric Algorithm for Contrastive Principal Component Analysis in High Dimension. - Rung-Sheng Lu; Shao-Hsuan Wang; Su-Yun Huang (J. Comput. Graph. Stat., 2024)