◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

Z. Ke

13 papers hereh-index 181.1k citations55 works total

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

author position
  • first author6
  • middle author5
  • last author2

Across the 13 of 13 papers where every author was matched, so the position is known.

fields
  • stat.ME6
  • math.ST3
  • cs.DL1
  • cs.LG1
  • cs.SI1
  • stat.ML1
same name
  • Z. Ke — 3 papers
  • Z. Ke — 2 papers, h 18
  • Z. Ke — 1 paper, h 7
  • Z. Ke — 1 paper, h 10

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
20172022
most citedA Sharp Lower Bound for Mixed-membership Estimation

10 citations · 20 across the 9 of their papers we have counts for

collaborators
Showing math.STShow all

4 papers · 1 filter

math.ST2025

Network Goodness-of-Fit for the block-model family

Jiashun Jin, Zheng Tracy Ke, Jiajun Tang +1

The block-model family has four popular network models (SBM, DCBM, MMSBM, and DCMM). A fundamental problem is, how well each of these models fits with real networks. We propose GoF…

math.ST2022★ 3 cited

Power Enhancement and Phase Transitions for Global Testing of the Mixed Membership Stochastic Block Model

Louis Cammarata, Zheng Tracy Ke

The mixed-membership stochastic block model (MMSBM) is a common model for social networks. Given an n-node symmetric network generated from a K-community MMSBM, we would like t…

math.ST2019★ 1 cited

Optimal Adaptivity of Signed-Polygon Statistics for Network Testing

Jiashun Jin, Zheng Tracy Ke, Shengming Luo

Given a symmetric social network, we are interested in testing whether it has only one community or multiple communities. The desired tests should (a) accommodate severe degree het…

math.ST2017★ 10 cited

A Sharp Lower Bound for Mixed-membership Estimation

Jiashun Jin, Zheng Tracy Ke

Consider an undirected network with n nodes and K perceivable communities, where some nodes may have mixed memberships. We assume that for each node 1≤i≤n, there is…

◍wovepaper

Papers, researchers and institutions, woven together.

Explore
  • Search
  • Researchers
  • Institutions
Account
  • Library
  • Chat
Data
  • arXiv.org
  • Semantic Scholar
  • OpenAlex
  • Latest RSS
AboutContactPrivacyDevelopersllms.txtopenapi.json
Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.