English

Random Tensors and Planted Cliques

Data Structures and Algorithms 2015-05-13 v1 Computational Complexity

Abstract

The r-parity tensor of a graph is a generalization of the adjacency matrix, where the tensor's entries denote the parity of the number of edges in subgraphs induced by r distinct vertices. For r=2, it is the adjacency matrix with 1's for edges and -1's for nonedges. It is well-known that the 2-norm of the adjacency matrix of a random graph is O(\sqrt{n}). Here we show that the 2-norm of the r-parity tensor is at most f(r)\sqrt{n}\log^{O(r)}n, answering a question of Frieze and Kannan who proved this for r=3. As a consequence, we get a tight connection between the planted clique problem and the problem of finding a vector that approximates the 2-norm of the r-parity tensor of a random graph. Our proof method is based on an inductive application of concentration of measure.

Keywords

Cite

@article{arxiv.0905.2381,
  title  = {Random Tensors and Planted Cliques},
  author = {S. Charles Brubaker and Santosh Vempala},
  journal= {arXiv preprint arXiv:0905.2381},
  year   = {2015}
}
R2 v1 2026-06-21T13:02:22.069Z