
arXiv: 1702.05543
The problem of (approximately) counting the independent sets of a bipartite graph (#BIS) is the canonical approximate counting problem that is complete in the intermediate complexity class #RH��_1. It is believed that #BIS does not have an efficient approximation algorithm but also that it is not NP-hard. We study the robustness of the intermediate complexity of #BIS by considering variants of the problem parameterised by the size of the independent set. We exhaustively map the complexity landscape for three problems, with respect to exact computation and approximation and with respect to conventional and parameterised complexity. The three problems are counting independent sets of a given size, counting independent sets with a given number of vertices in one vertex class and counting maximum independent sets amongst those with a given number of vertices in one vertex class. Among other things, we show that all of these problems are NP-hard to approximate within any polynomial ratio. (This is surprising because the corresponding problems without the size parameter are complete in #RH��_1, and hence are not believed to be NP-hard.) We also show that the first problem is #W[1]-hard to solve exactly but admits an FPTRAS, whereas the other two are W[1]-hard to approximate even within any polynomial ratio. Finally, we show that, when restricted to graphs of bounded degree, all three problems have efficient exact fixed-parameter algorithms.
to appear in Algorithmica
FOS: Computer and information sciences, name=Algorithms and Complexity, /dk/atira/pure/core/keywords/algorithms_and_complexity; name=Algorithms and Complexity, Parameterized complexity, tractability and kernelization, G.2.1, G.2.2, Computational Complexity (cs.CC), Independent sets, Parameterised complexity, approximate counting, F.2.2; G.2.1; G.2.2, /dk/atira/pure/core/keywords/algorithms_and_complexity, 004, Computer Science - Computational Complexity, Vertex subsets with special properties (dominating sets, independent sets, cliques, etc.), independent sets, Approximate counting, Graph theory (including graph drawing) in computer science, parameterised complexity, Computational difficulty of problems (lower bounds, completeness, difficulty of approximation, etc.), F.2.2, ddc: ddc:004
FOS: Computer and information sciences, name=Algorithms and Complexity, /dk/atira/pure/core/keywords/algorithms_and_complexity; name=Algorithms and Complexity, Parameterized complexity, tractability and kernelization, G.2.1, G.2.2, Computational Complexity (cs.CC), Independent sets, Parameterised complexity, approximate counting, F.2.2; G.2.1; G.2.2, /dk/atira/pure/core/keywords/algorithms_and_complexity, 004, Computer Science - Computational Complexity, Vertex subsets with special properties (dominating sets, independent sets, cliques, etc.), independent sets, Approximate counting, Graph theory (including graph drawing) in computer science, parameterised complexity, Computational difficulty of problems (lower bounds, completeness, difficulty of approximation, etc.), F.2.2, ddc: ddc:004
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 6 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
