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Kai Zhou

The Hong Kong Polytechnic University

11 papers hereh-index 10378 citations35 works total

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

author position
  • first author3
  • middle author4
  • last author4

Across the 11 of 11 papers where every author was matched, so the position is known.

fields
  • cs.LG4
  • cs.SI4
  • cs.CR2
  • cs.AI1
affiliations
  • The Hong Kong Polytechnic University
Homepage
same name
  • Kai Zhou — 12 papers, h 10
  • Kai Zhou — 9 papers, h 4
  • Kai Zhou — 8 papers, h 5
  • Kai Zhou — 8 papers, h 2
  • Kai Zhou — 7 papers, h 2
  • Kai Zhou — 7 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
20182026
most citedRobust Collective Classification against Structural Attacks

2 citations · 2 across the 4 of their papers we have counts for

collaborators
Showing cs.SIShow all

4 papers · 1 filter

cs.SI2021

Strategic Evasion of Centrality Measures

Marcin Waniek, Jan Woźnica, Kai Zhou +3

Among the most fundamental tools for social network analysis are centrality measures, which quantify the importance of every node in the network. This centrality analysis typically…

cs.SI2020

Blocking Adversarial Influence in Social Networks

Feiran Jia, Kai Zhou, Charles Kamhoua +1

While social networks are widely used as a media for information diffusion, attackers can also strategically employ analytical tools, such as influence maximization, to maximize th…

cs.SI2018

Attacking Similarity-Based Link Prediction in Social Networks

Kai Zhou, Tomasz P. Michalak, Talal Rahwan +2

Link prediction is one of the fundamental problems in computational social science. A particularly common means to predict existence of unobserved links is via structural similarit…

cs.SI2018

Attack Tolerance of Link Prediction Algorithms: How to Hide Your Relations in a Social Network

Marcin Waniek, Kai Zhou, Yevgeniy Vorobeychik +3

Link prediction is one of the fundamental research problems in network analysis. Intuitively, it involves identifying the edges that are most likely to be added to a given network,…

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