Independent Set, Induced Matching, and Pricing: Connections and Tight (Subexponential Time) Approximation Hardnesses

Abstract

We present a series of almost settled inapproximability results for three fundamental problems. The first in our series is the subexponential-time inapproximability of the independent set problem, a question studied in the area of parameterized complexity. The second is the hardness of approximating the bipartite induced matching problem on bounded-degree bipartite graphs. The last in our series is the tight hardness of approximating the k-hypergraph pricing problem, a fundamental problem arising from the area of algorithmic game theory. In particular, assuming the Exponential Time Hypothesis, our two main results are: For any r larger than some constant, any r-approximation algorithm for the independent set problem must run in at least 2n1-e/r1+e time. This nearly matches the upper bound of 2n/r [23]. It also improves some hardness results in the domain of parameterized complexity (e.g., [26], [19]). For any k larger than some constant, there is no polynomial time min{k1-e, n1/2-e} time min -approximation algorithm for the k-hypergraph pricing problem , where n is the number of vertices in an input graph. This almost matches the upper bound of min{O(k), O(√n) } min (by Balcan and Blum [3] and an algorithm in this paper). We note an interesting fact that, in contrast to n1/2-e hardness for polynomial-time algorithms, the k-hypergraph pricing problem admits nδ approximation for any δ > 0 in quasi-polynomial time. This puts this problem in a rare approximability class in which approximability thresholds can be improved significantly by allowing algorithms to run in quasi-polynomial time. The proofs of our hardness results rely on unexpectedly tight connections between the three problems. First, we establish a connection between the first and second problems by proving a new graph-theoretic property related to an induced matching number of dispersers. Then, we show that the n1/2-e hardness of the last problem follows from nearly tight subexponential time inapproximability of the first problem, illustrating a rare application of the second type of inapproximability result to the first one. Finally, to prove the subexponential-time inapproximability of the first problem, we construct a new PCP with several properties; it is sparse and has nearly-linear size, large degree, and small free-bit complexity. Our PCP requires no ground-breaking ideas but rather a very careful assembly of the existing ingredients in the PCP literature.