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Su-Yun Huang
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2020 – today
- 2024
- [i3]Zhi-Yu Jou, Su-Yun Huang, Hung Hung, Shinto Eguchi:
A Generalized Mean Approach for Distributed-PCA. CoRR abs/2410.00397 (2024) - 2022
- [j17]Cen-Jhih Li, Pin-Han Huang, Yi-Ting Ma, Hung Hung, Su-Yun Huang:
Robust Aggregation for Federated Learning by Minimum γ-Divergence Estimation. Entropy 24(5): 686 (2022) - [j16]Shao-Hsuan Wang, Su-Yun Huang
:
Perturbation theory for cross data matrix-based PCA. J. Multivar. Anal. 190: 104960 (2022) - [j15]Hung Hung
Robust Self-Tuning Semiparametric PCA for Contaminated Elliptical Distribution. IEEE Trans. Signal Process. 70: 5885-5897 (2022) - 2021
- [j14]Shih-Hao Huang
On the asymptotic normality and efficiency of Kronecker envelope principal component analysis. J. Multivar. Anal. 184: 104761 (2021) - 2020
- [j13]Shao-Hsuan Wang, Su-Yun Huang, Ting-Li Chen
On asymptotic normality of cross data matrix-based PCA in high dimension low sample size. J. Multivar. Anal. 175 (2020) - [c1]Yi-Ju Lee, Su-Yun Huang, Shih-Jen Tsai, Albert C. Yang:
Altered Functional Complexity Associated with Structural Features in Schizophrenic Brain: A Resting-state fMRI Study. COMPLEXIS 2020: 120-128 - [i2]Toshinari Morimoto, Su-Yun Huang:
TensorProjection Layer: A Tensor-Based Dimensionality Reduction Method in CNN. CoRR abs/2004.04454 (2020)
2010 – 2019
- 2019
- [j12]I-Ping Tu
The generalized degrees of freedom of multilinear principal component analysis. J. Multivar. Anal. 173: 26-37 (2019) - [i1]Szu-Chi Chung, Po-Yao Niu, Su-Yun Huang, Wei-Hau Chang, I-Ping Tu:
2SDR: Applying Kronecker Envelope PCA to denoise Cryo-EM Images. CoRR abs/1911.09816 (2019) - 2016
- [j11]Ting-Li Chen
On the weak convergence and Central Limit Theorem of blurring and nonblurring processes with application to robust location estimation. J. Multivar. Anal. 143: 165-184 (2016) - 2013
- [j10]Shinto Eguchi
Statistical Analysis of Biomarkers for Personalized Medicine. Comput. Math. Methods Medicine 2013: 467420:1-467420:2 (2013) - [j9]Pengwen Chen
Robust Independent Component Analysis via Minimum Gamma -Divergence Estimation. IEEE J. Sel. Top. Signal Process. 7(4): 614-624 (2013) - [j8]Lo-Bin Chang, Zhidong Bai
Asymptotic error bounds for kernel-based Nyström low-rank approximation matrices. J. Multivar. Anal. 120: 102-119 (2013) - 2010
- [j7]Pei-Chun Chen, Kuang-Yao Lee, Tsung-Ju Lee, Yuh-Jye Lee
Multiclass support vector classification via coding and regression. Neurocomputing 73(7-9): 1501-1512 (2010)
2000 – 2009
- 2009
- [j6]Pei-Chun Chen, Su-Yun Huang, Wei J. Chen
A new regularized least squares support vector regression for gene selection. BMC Bioinform. 10 (2009) - [j5]Su-Yun Huang, Yi-Ren Yeh, Shinto Eguchi
Robust Kernel Principal Component Analysis. Neural Comput. 21(11): 3179-3213 (2009) - [j4]Yi-Ren Yeh, Su-Yun Huang, Yuh-Jye Lee
Nonlinear Dimension Reduction with Kernel Sliced Inverse Regression. IEEE Trans. Knowl. Data Eng. 21(11): 1590-1603 (2009) - 2007
- [j3]Chien-Ming Huang, Yuh-Jye Lee
Model selection for support vector machines via uniform design. Comput. Stat. Data Anal. 52(1): 335-346 (2007) - [j2]Yuh-Jye Lee
Reduced Support Vector Machines: A Statistical Theory. IEEE Trans. Neural Networks 18(1): 1-13 (2007) - 2004
- [j1]Chuhsing Kate Hsiao
Bayesian marginal inference via candidate's formula. Stat. Comput. 14(1): 59-66 (2004)
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