Optimal-size problem kernels for d-Hitting Set in linear time and space

03/10/2020
by   René van Bevern, et al.
0

We improve two linear-time data reduction algorithms for the d-Hitting Set problem to work in linear space, thus obtaining the first algorithms for computing problem kernels of asymptotically optimal size O(k^d) for d-Hitting Set in linear time and space. We experimentally compare the two algorithms to a classical data reduction algorithm of Weihe and evaluate their combinations.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
02/28/2018

Fast Lempel-Ziv Decompression in Linear Space

We consider the problem of decompressing the Lempel-Ziv 77 representatio...
research
12/09/2019

Basis Prediction Networks for Effective Burst Denoising with Large Kernels

Bursts of images exhibit significant self-similarity across both time an...
research
11/08/2019

Space Efficient Construction of Lyndon Arrays in Linear Time

We present the first linear time algorithm to construct the 2n-bit versi...
research
06/30/2021

A Simple Linear-Time Algorithm for the Common Refinement of Rooted Phylogenetic Trees on a Common Leaf Set

Background. The supertree problem, i.e., the task of finding a common re...
research
01/26/2023

Relative-Interior Solution for (Incomplete) Linear Assignment Problem with Applications to Quadratic Assignment Problem

We study the set of optimal solutions of the dual linear programming for...
research
05/25/2021

A linear parallel algorithm to compute bisimulation and relational coarsest partitions

The most efficient way to calculate strong bisimilarity is by calculatio...
research
02/25/2021

A Linear Time Algorithm for Constructing Hierarchical Overlap Graphs

The hierarchical overlap graph (HOG) is a graph that encodes overlaps fr...

Please sign up or login with your details

Forgot password? Click here to reset