Additive Stabilizers for Unstable Graphs
Karthekeyan Chandrasekaran, Corinna Gottschalk, Jochen K\"onemann,, Britta Peis, Daniel Schmand, Andreas Wierz

TL;DR
This paper investigates the stabilization of graphs through fractional edge weight increases, establishing complexity bounds, hardness results, and algorithms for specific graph classes, advancing understanding of graph stabilization problems.
Contribution
It introduces the first super-constant hardness results for graph stabilization and provides algorithms for stabilizing graphs by minimum weight increase.
Findings
Approximation of min additive stabilizer relates to densest-k-subgraph complexity.
No o(log|V|) approximation for min additive stabilizer unless NP=P.
Exact algorithms for certain graph classes and approximation algorithms with sqrt{|V|} factor.
Abstract
Stabilization of graphs has received substantial attention in recent years due to its connection to game theory. Stable graphs are exactly the graphs inducing a matching game with non-empty core. They are also the graphs that induce a network bargaining game with a balanced solution. A graph with weighted edges is called stable if the maximum weight of an integral matching equals the cost of a minimum fractional weighted vertex cover. If a graph is not stable, it can be stabilized in different ways. Recent papers have considered the deletion or addition of edges and vertices in order to stabilize a graph. In this work, we focus on a fine-grained stabilization strategy, namely stabilization of graphs by fractionally increasing edge weights. We show the following results for stabilization by minimum weight increase in edge weights (min additive stabilizer): (i) Any approximation algorithm…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
