21 citations · 86 across the 12 of their papers we have counts for
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stat.ME2022
Clustering High-dimensional Data via Feature Selection
Tianqi Liu, Yu Lu, Biqing Zhu +1
High-dimensional clustering analysis is a challenging problem in statistics and machine learning, with broad applications such as the analysis of microarray data and RNA-seq data.…
stat.ME2017★ 21 cited
Characterizing Spatiotemporal Transcriptome of Human Brain via Low Rank Tensor Decomposition
Tianqi Liu, Ming Yuan, Hongyu Zhao
Spatiotemporal gene expression data of the human brain offer insights on the spa- tial and temporal patterns of gene regulation during brain development. Most existing methods for…
stat.ME2016★ 1 cited
Ultrahigh Dimensional Feature Selection via Kernel Canonical Correlation Analysis
Tianqi Liu, Kuang-Yao Lee, Hongyu Zhao
High-dimensional variable selection is an important issue in many scientific fields, such as genomics. In this paper, we develop a sure independence feature screening pro- cedure b…