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researcher

D. Han

4 papers hereh-index 283.1k citations126 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • last author3

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • math.ST3
  • stat.ML1
same name
  • D. Han — 30 papers, h 15
  • D. Han — 29 papers, h 31
  • D. Han — 20 papers, h 26
  • D. Han — 7 papers, h 6
  • D. Han — 7 papers, h 16
  • D. Han — 6 papers, h 4

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20182020
most citedOptimal Sequential Tests for Monitoring Changes in the Distribution of Finite Observation Sequences

4 citations · 5 across the 4 of their papers we have counts for

collaborators

4 papers

math.ST2020

Homogeneity Test of Several High-Dimensional Covariance Matrices for Stationary Processes under Non-normality

Abdullah Qayed, Dong Han

This article presents a homogeneity test for testing the equality of several high-dimensional covariance matrices for stationary processes with ignoring the assumption of normality…

math.ST2019★ 1 cited

Optimal Sequential Tests for Detection of Changes under Finite measure space for Finite Sequences of Networks

Lei Qiao, Dong Han

This paper considers the change-point problem for finite sequences of networks. To avoid the difficulty of computing the normalization coefficient, such as in Exponential random gr…

math.ST2019★ 4 cited

Optimal Sequential Tests for Monitoring Changes in the Distribution of Finite Observation Sequences

Dong Han, Fugee Tsung, Jinguo Xian

This article develops a method to construct the optimal sequential test for monitoring the changes in the distribution of finite observation sequences with a general dependence str…

stat.ML2018

Multi-distance Support Matrix Machines

Yunfei Ye, Dong Han

Real-world data such as digital images, MRI scans and electroencephalography signals are naturally represented as matrices with structural information. Most existing classifiers ai…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.