A randomized algorithm estimates m(H) within factor (1 +/- epsilon) using O_d(log^{5d+5} n / epsilon^4) GPIS queries for d-uniform hypergraphs, if the sparsification lemma is valid.
On Triangle Estimation using Tripartite Independent Set Queries
1 Pith paper cite this work. Polarity classification is still indexing.
abstract
Estimating the number of triangles in a graph is one of the most fundamental problems in sublinear algorithms. In this work, we provide an algorithm that approximately counts the number of triangles in a graph using only polylogarithmic queries when \emph{the number of triangles on any edge in the graph is polylogarithmically bounded}. Our query oracle {\em Tripartite Independent Set} (TIS) takes three disjoint sets of vertices $A$, $B$ and $C$ as inputs, and answers whether there exists a triangle having one endpoint in each of these three sets. Our query model generally belongs to the class of \emph{group queries} (Ron and Tsur, ACM ToCT, 2016; Dell and Lapinskas, STOC 2018) and in particular is inspired by the {\em Bipartite Independent Set} (BIS) query oracle of Beame {\em et al.} (ITCS 2018). We extend the algorithmic framework of Beame {\em et al.}, with \tis replacing \bis, for approximately counting triangles in graphs.
fields
cs.DS 1years
2019 1verdicts
REJECT 1representative citing papers
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Hyperedge Estimation using Polylogarithmic Subset Queries
A randomized algorithm estimates m(H) within factor (1 +/- epsilon) using O_d(log^{5d+5} n / epsilon^4) GPIS queries for d-uniform hypergraphs, if the sparsification lemma is valid.