« The Karger-Stein Algorithm is Optimal for k-cut
December 04, 2019, 11:00 AM - 12:00 PM
Location:
Conference Room 301
Rutgers University
CoRE Building
96 Frelinghuysen Road
Piscataway, NJ 08854
In the $k$-cut problem, we are given an edge-weighted graph and want to find the least-weight set of edges whose deletion breaks the graph into $k$ connected components. Algorithms due to Karger-Stein and Thorup showed how to find such a minimum $k$-cut in time approximately $O(n^{2k-2})$. The best lower bounds come from conjectures about the solvability of the $k$-clique problem and a reduction from $k$-clique to $k$-cut, and show that solving $k$-cut is likely to require time $Omega(n^k)$. Our recent results have given special-purpose algorithms that solve the problem in time $n^{1.98k + O(1)}$, and ones that have better performance for special classes of graphs (e.g., for small integer weights). |
In this work, we resolve the problem for general graphs, by showing that for any fixed $k geq 2$, the Karger-Stein algorithm outputs any fixed minimum $k$-cut with probability at least $widehat{O}(n^{-k})$, where $widehat{O}(cdot)$ hides a $2^{O(ln ln n)^2}$ factor. This also gives an extremal bound of $widehat{O}(n^k)$ on the number of minimum $k$-cuts in an $n$-vertex graph and an algorithm to compute a minimum $k$-cut in similar runtime. Both are tight up to $widehat{O}(1)$ factors. |
The first main ingredient in our result is a fine-grained analysis of how the graph shrinks---and how the average degree evolves---under the Karger-Stein process. The second ingredient is an extremal result bounding the number of cuts of size at most $(2-delta) OPT/k$, using the Sunflower lemma. |