17 citations · 30 across the 9 of their papers we have counts for
9 papers
Blurring Mean Shift for Clustering Functional Data: A Scalable Algorithm and Convergence Analysis
Toshinari Morimoto, Ting-Li Chen, Su-Yun Huang +1
This paper extends the blurring mean shift algorithm from vector-valued data to functional data, enabling effective clustering in infinite-dimensional settings without requiring sp…
A Consistency Theorem for Randomized Singular Value Decomposition
Ting-Li Chen, Su-Yun Huang, Weichung Wang
The singular value decomposition (SVD) and the principal component analysis are fundamental tools and probably the most popular methods for data dimension reduction. The rapid grow…
On the asymptotic variance of reversible Markov chain without cycles
Chi-Hao Wu, Ting-Li Chen
Markov chain Monte Carlo(MCMC) is a popular approach to sample from high dimensional distributions, and the asymptotic variance is a commonly used criterion to evaluate the perform…
Integrating multiple random sketches for singular value decomposition
Ting-Li Chen, Dawei D. Chang, Su-Yun Huang +3
The singular value decomposition (SVD) of large-scale matrices is a key tool in data analytics and scientific computing. The rapid growth in the size of matrices further increases…
Functional Inverse Regression in an Enlarged Dimension Reduction Space
Ting-Li Chen, Su-Yun Huang, Yanyuan Ma +1
We consider an enlarged dimension reduction space in functional inverse regression. Our operator and functional analysis based approach facilitates a compact and rigorous formulati…
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 +1
This article studies the weak convergence and associated Central Limit Theorem for blurring and nonblurring processes. Then, they are applied to the estimation of location paramete…
On the Convergence and Consistency of the Blurring Mean-Shift Process
Ting-Li Chen
The mean-shift algorithm is a popular algorithm in computer vision and image processing. It can also be cast as a minimum gamma-divergence estimation. In this paper we focus on the…
-SUP: A clustering algorithm for cryo-electron microscopy images of asymmetric particles
Ting-Li Chen, Dai-Ni Hsieh, Hung Hung +5
Cryo-electron microscopy (cryo-EM) has recently emerged as a powerful tool for obtaining three-dimensional (3D) structures of biological macromolecules in native states. A minimum…
On the strengths of the self-updating process clustering algorithm
Shang-Ying Shiu, Ting-Li Chen
We introduce a simple, intuitive and yet powerful algorithm for clustering analysis. This algorithm is an iterative process on the sample space, which arises as an extension of the…