No. |
Title |
Author |
Year |
---|

1 |
Parameterized Lower Bounds for Problems in P via Fine-Grained Cross-Compositions |
Heeger, Klaus et al. |
2023 |

2 |
Applying a Cut-Based Data Reduction Rule for Weighted Cluster Editing in Polynomial Time |
Schulz, Hjalmar et al. |
2022 |

3 |
Covering Many (Or Few) Edges with k Vertices in Sparse Graphs |
Koana, Tomohiro et al. |
2022 |

4 |
There and Back Again: On Applying Data Reduction Rules by Undoing Others |
Figiel, Aleksander et al. |
2022 |

5 |
The PACE 2021 Parameterized Algorithms and Computational Experiments Challenge: Cluster Editing |
Kellerhals, Leon et al. |
2021 |

6 |
Using a Geometric Lens to Find k Disjoint Shortest Paths |
Bentert, Matthias et al. |
2021 |

7 |
An Adaptive Version of Brandes' Algorithm for Betweenness Centrality |
Bentert, Matthias et al. |
2018 |

8 |
Data Reduction for Maximum Matching on Real-World Graphs: Theory and Experiments |
Korenwein, Viatcheslav et al. |
2018 |

9 |
Parameterized Dynamic Cluster Editing |
Luo, Junjie et al. |
2018 |

10 |
A Parameterized Algorithmics Framework for Degree Sequence Completion Problems in Directed Graphs |
Bredereck, Robert et al. |
2017 |

11 |
The Power of Linear-Time Data Reduction for Maximum Matching |
Mertzios, George B. et al. |
2017 |

12 |
Fractals for Kernelization Lower Bounds, With an Application to Length-Bounded Cut Problems |
Fluschnik, Till et al. |
2016 |