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20112023
most citedSimple and Deep Graph Convolutional Networks

402 citations · 556 across the 19 of their papers we have counts for

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Showing cs.DSShow all

7 papers · 1 filter

cs.DS2023

On Coresets for Clustering in Small Dimensional Euclidean Spaces

Lingxiao Huang, Ruiyuan Huang, Zengfeng Huang +1

We consider the problem of constructing small coresets for -Median in Euclidean spaces. Given a large set of data points , a coreset is a much smaller set…

cs.DS2020★ 51 cited

Personalized PageRank to a Target Node, Revisited

Hanzhi Wang, Zhewei Wei, Junhao Gan +2

Personalized PageRank (PPR) is a widely used node proximity measure in graph mining and network analysis. Given a source node and a target node , the PPR value repr…

cs.DS2018

Efficient and High-Quality Seeded Graph Matching: Employing High Order Structural Information

Haida Zhang, Zengfeng Huang, Xuemin Lin +3

Driven by many real applications, we study the problem of seeded graph matching. Given two graphs and , and a small set of pre-matched node…

cs.DS2017

Communication complexity of approximate maximum matching in the message-passing model

Zengfeng Huang, Bozidar Radunovic, Milan Vojnovic +1

We consider the communication complexity of finding an approximate maximum matching in a graph in a multi-party message-passing communication model. The maximum matching problem is…

cs.DS2016★ 1 cited

Dynamic Graph Stream Algorithms in Space

Zengfeng Huang, Pan Peng

In this paper we study graph problems in dynamic streaming model, where the input is defined by a sequence of edge insertions and deletions. As many natural problems require …

cs.DS2014

Tracking the Frequency Moments at All Times

Zengfeng Huang, Wai Ming Tai, Ke Yi

The traditional requirement for a randomized streaming algorithm is just {\em one-shot}, i.e., algorithm should be correct (within the stated $\eps$-error bound) at the end of the…

cs.DS2011★ 2 cited

Randomized Algorithms for Tracking Distributed Count, Frequencies, and Ranks

Zengfeng Huang, Ke Yi, Qin Zhang

We show that randomization can lead to significant improvements for a few fundamental problems in distributed tracking. Our basis is the {\em count-tracking} problem, where there a…