Why walking the dog takes time: Frechet distance has no strongly subquadratic algorithms unless SETH fails K Bringmann 2014 IEEE 55th Annual Symposium on Foundations of Computer Science, 661-670, 2014 | 203 | 2014 |

Quadratic conditional lower bounds for string problems and dynamic time warping K Bringmann, M Künnemann 2015 IEEE 56th Annual Symposium on Foundations of Computer Science, 79-97, 2015 | 178 | 2015 |

Approximating the volume of unions and intersections of high-dimensional geometric objects K Bringmann, T Friedrich Computational Geometry 43 (6-7), 601-610, 2010 | 172 | 2010 |

Approximating the least hypervolume contributor: NP-hard in general, but fast in practice K Bringmann, T Friedrich International Conference on Evolutionary Multi-Criterion Optimization, 6-20, 2009 | 143 | 2009 |

Approximation-guided evolutionary multi-objective optimization K Bringmann, T Friedrich, F Neumann, M Wagner Twenty-Second International Joint Conference on Artificial Intelligence, 2011 | 89 | 2011 |

Approximating the least hypervolume contributor: NP-hard in general, but fast in practice K Bringmann, T Friedrich International Conference on Evolutionary Multi-Criterion Optimization, 6-20, 2009 | 89 | 2009 |

An efficient algorithm for computing hypervolume contributions K Bringmann, T Friedrich Evolutionary Computation 18 (3), 383-402, 2010 | 77 | 2010 |

Geometric inhomogeneous random graphs K Bringmann, R Keusch, J Lengler Theoretical Computer Science 760, 35-54, 2019 | 61 | 2019 |

Two-dimensional subset selection for hypervolume and epsilon-indicator K Bringmann, T Friedrich, P Klitzke Proceedings of the 2014 Annual Conference on Genetic and Evolutionary …, 2014 | 56 | 2014 |

Approximability of the discrete Fréchet distance K Bringmann, W Mulzer Journal of Computational Geometry 7 (2), 46-76, 2016 | 54 | 2016 |

Approximation quality of the hypervolume indicator K Bringmann, T Friedrich Artificial Intelligence 195, 265-290, 2013 | 54 | 2013 |

Don't be greedy when calculating hypervolume contributions K Bringmann, T Friedrich Proceedings of the tenth ACM SIGEVO workshop on Foundations of genetic …, 2009 | 49 | 2009 |

A near-linear pseudopolynomial time algorithm for subset sum K Bringmann Proceedings of the Twenty-Eighth Annual ACM-SIAM Symposium on Discrete …, 2017 | 46 | 2017 |

Efficient sampling methods for discrete distributions K Bringmann, K Panagiotou International Colloquium on Automata, Languages, and Programming, 133-144, 2012 | 43* | 2012 |

SETH-based lower bounds for subset sum and bicriteria path A Abboud, K Bringmann, D Hermelin, D Shabtay Proceedings of the Thirtieth Annual ACM-SIAM Symposium on Discrete …, 2019 | 42 | 2019 |

A dichotomy for regular expression membership testing K Bringmann, A Grønlund, KG Larsen 2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS …, 2017 | 36 | 2017 |

Sampling geometric inhomogeneous random graphs in linear time K Bringmann, R Keusch, J Lengler arXiv preprint arXiv:1511.00576, 2015 | 33 | 2015 |

Speeding up many-objective optimization by Monte Carlo approximations K Bringmann, T Friedrich, C Igel, T Voß Artificial Intelligence 204, 22-29, 2013 | 33 | 2013 |

Truly subcubic algorithms for language edit distance and RNA folding via fast bounded-difference min-plus product K Bringmann, F Grandoni, B Saha, VV Williams SIAM Journal on Computing 48 (2), 481-512, 2019 | 32 | 2019 |

The maximum hypervolume set yields near-optimal approximation K Bringmann, T Friedrich Proceedings of the 12th annual conference on Genetic and evolutionary …, 2010 | 32 | 2010 |