Optimal-size problem kernels for $d$-Hitting Set in linear time and space. van Bevern, R. & Smirnov, P. V. *Information Processing Letters*, 2020. Preprint Code Poster doi abstract bibtex 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.

@article{BS20,
title = {Optimal-size problem kernels for $d$-Hitting Set in
linear time and space},
author = {René van Bevern and Pavel V. Smirnov},
year = {2020},
date = {2020-10-01},
journal = {Information Processing Letters},
volyme = {163},
pages = {105998},
doi = {10.1016/j.ipl.2020.105998},
url_Preprint = {https://arxiv.org/abs/2003.04578},
url_Code = {https://gitlab.com/PavelSmirnov/hs-lintimespace},
url_Poster = {https://figshare.com/articles/poster/Optimal-size_problem_kernels_for_d-Hitting_Set_in_linear_time_and_space/12782975},
abstract = {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.}
}

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