Baby pih: Parameterized inapproximability of min csp

V Guruswami, X Ren, S Sandeep - arXiv preprint arXiv:2310.16344, 2023 - arxiv.org
The Parameterized Inapproximability Hypothesis (PIH) is the analog of the PCP theorem in
the world of parameterized complexity. It asserts that no FPT algorithm can distinguish a …

[PDF][PDF] Parameterized Inapproximability Hypothesis under Exponential Time Hypothesis

V Guruswami, B Lin, X Ren, Y Sun, K Wu - Proceedings of the 56th …, 2024 - dl.acm.org
The Parameterized Inapproximability Hypothesis (PIH) asserts that no fixed parameter
tractable (FPT) algorithm can distinguish a satisfiable CSP instance, parameterized by the …

Parameterized Inapproximability Hypothesis under ETH

V Guruswami, B Lin, X Ren, Y Sun, K Wu - arXiv preprint arXiv:2311.16587, 2023 - arxiv.org
The Parameterized Inapproximability Hypothesis (PIH) asserts that no fixed parameter
tractable (FPT) algorithm can distinguish a satisfiable CSP instance, parameterized by the …

Fine Grained Lower Bounds for Multidimensional Knapsack

I Doron-Arad, A Kulik, P Manurangsi - arXiv preprint arXiv:2407.10146, 2024 - arxiv.org
We study the $ d $-dimensional knapsack problem. We are given a set of items, each with a
$ d $-dimensional cost vector and a profit, along with a $ d $-dimensional budget vector. The …

On Equivalence of Parameterized Inapproximability of k-Median, k-Max-Coverage, and 2-CSP

CS Karthik, E Lee, P Manurangsi - 19th International Symposium …, 2024 - drops.dagstuhl.de
Abstract Parameterized Inapproximability Hypothesis (PIH) is a central question in the field
of parameterized complexity. PIH asserts that given as input a 2-CSP on k variables and …

On Equivalence of Parameterized Inapproximability of k-Median, k-Max-Coverage, and 2-CSP

E Lee, P Manurangsi - arXiv preprint arXiv:2407.08917, 2024 - arxiv.org
Parameterized Inapproximability Hypothesis (PIH) is a central question in the field of
parameterized complexity. PIH asserts that given as input a 2-CSP on $ k $ variables and …

Sampling with a Black Box: Faster Parameterized Approximation Algorithms for Vertex Deletion Problems

BC Esmer, A Kulik - arXiv preprint arXiv:2407.12654, 2024 - arxiv.org
In this paper we introduce Sampling with a Black Box, a generic technique for the design of
parameterized approximation algorithms for vertex deletion problems (eg, Vertex Cover …