Abstract
We consider a variant of the planted clique problem where we are allowed unbounded computational time but can only investigate a small part of the graph by adaptive edge queries. We determine (up to logarithmic factors) the number of queries necessary both for detecting the presence of a planted clique and for finding the planted clique. Specifically, let G ~ G(n, 1/2, k) be a random graph on n vertices with a planted clique of size k. We show that no algorithm that makes at most q = o(n2/k2 + n) adaptive queries to the adjacency matrix of G is likely to find the planted clique. On the other hand, when k ≥ (2 + ε) log2 n there exists a simple algorithm (with unbounded computational power) that finds the planted clique with high probability by making q = O(n2/k2) log2 n + n log n) adaptive queries. For detection, the additive n term is not necessary: the number of queries needed to detect the presence of a planted clique is n2/k2 (up to logarithmic factors).
Original language | English (US) |
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Pages (from-to) | 759-773 |
Number of pages | 15 |
Journal | Alea |
Volume | 17 |
Issue number | 2 |
DOIs | |
State | Published - 2020 |
Funding
Received by the editors November 16th, 2019; accepted August 1st, 2020. 2010 Mathematics Subject Classification. 05C80, 60C05. Key words and phrases. Planted clique, random graph, adaptive query model. Research supported in part by NSF grant DMS 1811724.
Keywords
- Adaptive query model
- Planted clique
- Random graph
ASJC Scopus subject areas
- Statistics and Probability