Covering Small Independent Sets and Separators with Applications to Parameterized Algorithms

Abstract

We present two new combinatorial tools for the design of parameterized algorithms. The first is a simple linear time randomized algorithm that given as input a d-degenerate graph G and an integer k, outputs an independent set Y, such that for every independent set X in G of size at most k, the probability that X is a subset of Y is at least [EQUATION]. The second is a new (deterministic) polynomial time graph sparsification procedure that given a graph G, a set T = {{s1, t1}, {s2, t2},..., {se, te}} of terminal pairs and an integer k, returns an induced subgraph G* of G that maintains all the inclusion minimal multicuts of G of size at most k, and does not contain any (k + 2)-vertex connected set of size 2O(k). In particular, G* excludes a clique of size 2O(k) as a topological minor. Put together, our new tools yield new randomized fixed parameter tractable (FPT) algorithms for Stable s-t Separator, Stable Odd Cycle Transversal and Stable Multicut on general graphs, and for Stable Directed Feedback Vertex Set on d-degenerate graphs, resolving two problems left open by Marx et al. [ACM Transactions on Algorithms, 2013]. All of our algorithms can be derandomized at the cost of a small overhead in the running time.