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.
Nearly optimal edge estimation with independent set queries
1 Pith paper cite this work. Polarity classification is still indexing.
abstract
We study the problem of estimating the number of edges of an unknown, undirected graph $G=([n],E)$ with access to an independent set oracle. When queried about a subset $S\subseteq [n]$ of vertices the independent set oracle answers whether $S$ is an independent set in $G$ or not. Our first main result is an algorithm that computes a $(1+\epsilon)$-approximation of the number of edges $m$ of the graph using $\min(\sqrt{m},n / \sqrt{m})\cdot\textrm{poly}(\log n,1/\epsilon)$ independent set queries. This improves the upper bound of $\min(\sqrt{m},n^2/m)\cdot\textrm{poly}(\log n,1/\epsilon)$ by Beame et al. \cite{BHRRS18}. Our second main result shows that ${\min(\sqrt{m},n/\sqrt{m}))/\textrm{polylog}(n)}$ independent set queries are necessary, thus establishing that our algorithm is optimal up to a factor of $\textrm{poly}(\log n, 1/\epsilon)$.
fields
cs.DS 1years
2019 1verdicts
REJECT 1representative citing papers
citing papers explorer
-
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.