8 citations · 8 across the 3 of their papers we have counts for
12 papers
Learning Low-dimensional Manifolds for Scoring of Tissue Microarray Images
Donghui Yan, Jian Zou, Zhenpeng Li
Tissue microarray (TMA) images have emerged as an important high-throughput tool for cancer study and the validation of biomarkers. Efforts have been dedicated to further improve t…
Estimating the Number of Infected Cases in COVID-19 Pandemic
Donghui Yan, Ying Xu, Pei Wang
The COVID-19 pandemic has caused major disturbance to human life. An important reason behind the widespread social anxiety is the huge uncertainty about the pandemic. A fundamental…
: A Divide-and-conquer Algorithm for Large-scale Kernel Learning with Application to Clustering
Ke Alexander Wang, Xinran Bian, Pan Liu +1
Divide-and-conquer is a general strategy to deal with large scale problems. It is typically applied to generate ensemble instances, which potentially limits the problem size it can…
Similarity Kernel and Clustering via Random Projection Forests
Donghui Yan, Songxiang Gu, Ying Xu +1
Similarity plays a fundamental role in many areas, including data mining, machine learning, statistics and various applied domains. Inspired by the success of ensemble methods and…
Learning over inherently distributed data
Donghui Yan, Ying Xu
The recent decades have seen a surge of interests in distributed computing. Existing work focus primarily on either distributed computing platforms, data query tools, or, algorithm…
A First Course in Data Science
Donghui Yan, Gary E. Davis
Data science is a discipline that provides principles, methodology and guidelines for the analysis of data for tools, values, or insights. Driven by a huge workforce demand, many a…