Parallel Tempering for the planted clique problem

02/16/2018 ∙ by Maria Chiara Angelini, et al. ∙ 0

The theoretical information threshold for the planted clique problem is 2_2(N), however no polynomial algorithm is known to recover a planted clique of size O(N^1/2-ϵ), ϵ>0. In this paper we will apply a standard method for the analysis of disordered models, the Parallel-Tempering (PT) algorithm, to the clique problem, showing numerically that its time-scaling in the hard region is indeed polynomial for the analyzed sizes. We also apply PT to a different but connected model, the Sparse Planted Independent Set problem. In this situation thresholds should be sharper and finite size corrections should be less important. Also in this case PT shows a polynomial scaling in the hard region for the recovery.

READ FULL TEXT
POST COMMENT

Comments

There are no comments yet.

Authors

page 1

page 2

page 3

page 4

This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.