Finding Hidden Cliques in Linear Time with High Probability

Mathematics – Combinatorics

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

Scientific paper

We are given a graph $G$ with $n$ vertices, where a random subset of $k$ vertices has been made into a clique, and the remaining edges are chosen independently with probability $\tfrac12$. This random graph model is denoted $G(n,\tfrac12,k)$. The hidden clique problem is to design an algorithm that finds the $k$-clique in polynomial time with high probability. An algorithm due to Alon, Krivelevich and Sudakov uses spectral techniques to find the hidden clique with high probability when $k = c \sqrt{n}$ for a sufficiently large constant $c > 0$. Recently, an algorithm that solves the same problem was proposed by Feige and Ron. It has the advantages of being simpler and more intuitive, and of an improved running time of $O(n^2)$. However, the analysis in the paper gives success probability of only $2/3$. In this paper we present a new algorithm for finding hidden cliques that both runs in time $O(n^2)$, and has a failure probability that is less than polynomially small.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Finding Hidden Cliques in Linear Time with High Probability does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Finding Hidden Cliques in Linear Time with High Probability, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Finding Hidden Cliques in Linear Time with High Probability will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-286330

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.