Counting $t$-cliques: Worst-case to average-case reductions and Direct interactive proof systems

Webpage for a paper by Oded Goldreich and Guy Rothblum


We present two main results regarding the complexity of counting the number of $t$-cliques in a graph.

  1. A worst-case to average-case reduction: We reduce counting $t$-cliques in any $n$-vertex graph to counting $t$-cliques in typical $n$-vertex graphs that are drawn from a simple distribution of min-entropy ${\widetilde\Omega}(n^2)$. For any constant $t$, the reduction runs in ${\widetilde O}(n^2)$-time, and yields a correct answer (w.h.p.) even when the ``average-case solver'' only succeeds with probability $1/\poly(\log n)$.
  2. A direct interactive proof system: We present a direct and simple interactive proof system for counting $t$-cliques in $n$-vertex graphs. The proof system uses $t-2$ rounds, the verifier runs in ${\widetilde O}(t^2n^2)$-time, and the prover can be implemented in ${\widetilde O}(t^{O(1)}\cdot n^2)$-time when given oracle access to counting $(t-1)$-cliques in ${\widetilde O}(t^{O(1)}\cdot n)$-vertex graphs.
The results are both obtained by considering weighted versions of the $t$-clique problem, where weights are assigned to vertices and/or to edges, and the weight of cliques is defined as the product of the corresponding weights. These weighted problems are shown to be easily reducible to the unweighted problem.

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