Towards a Parameterized Approximation Dichotomy of MinCSP for Linear Equations over Finite Commutative Rings
Konrad K. Dabrowski, Peter Jonsson, Sebastian Ordyniak, George Osipov,, Magnus Wahlstr\"om

TL;DR
This paper explores the parameterized approximability of the MIN-r-LIN(R) problem over finite commutative rings, developing algorithms for certain classes and establishing hardness results for others, advancing the classification of MinCSP problems.
Contribution
It introduces a constant-factor FPT-approximation algorithm for Bergen rings and other classes, and proves strong lower bounds for non-Helly and non-lineal rings, advancing the understanding of MinCSP complexity.
Findings
Developed FPT-approximation for Bergen rings and related classes.
Proved non-FPT-approximability within any constant for r>2.
Identified classes where MIN-2-LIN(R) is not FPT-approximable.
Abstract
We consider the MIN-r-LIN(R) problem: given a system S of length-r linear equations over a ring R, find a subset of equations Z of minimum cardinality such that S-Z is satisfiable. The problem is NP-hard and UGC-hard to approximate within any constant even when r=|R|=2, so we focus on parameterized approximability with solution size as the parameter. For a large class of infinite rings R called Euclidean domains, Dabrowski et al. [SODA-2023] obtained an FPT-algorithm for MIN-2-LIN(R) using an LP-based approach based on work by Wahlstr\"om [SODA-2017]. Here, we consider MIN-r-LIN(R) for finite commutative rings R, initiating a line of research with the ultimate goal of proving dichotomy theorems that separate problems that are FPT-approximable within a constant from those that are not. A major motivation is that our project is a promising step for more ambitious classification projects…
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Taxonomy
TopicsMatrix Theory and Algorithms · Advanced Optimization Algorithms Research · Tensor decomposition and applications
