Finding near-optimal independent sets at scale S Lamm, P Sanders, C Schulz, D Strash, RF Werneck 2016 Proceedings of the eighteenth workshop on algorithm engineering and …, 2016 | 105 | 2016 |

Communication-free massively distributed graph generation D Funke, S Lamm, U Meyer, M Penschuck, P Sanders, C Schulz, D Strash, ... Journal of Parallel and Distributed Computing 131, 200-217, 2019 | 77 | 2019 |

Thrill: High-performance algorithmic distributed batch data processing with C++ T Bingmann, M Axtmann, E Jöbstl, S Lamm, HC Nguyen, A Noe, S Schlag, ... 2016 IEEE International Conference on Big Data (Big Data), 172-183, 2016 | 69 | 2016 |

Exactly solving the maximum weight independent set problem on large real-world graphs S Lamm, C Schulz, D Strash, R Williger, H Zhang 2019 Proceedings of the Twenty-First Workshop on Algorithm Engineering and …, 2019 | 55 | 2019 |

WeGotYouCovered: The Winning Solver from the PACE 2019 Challenge, Vertex Cover Track∗ D Hespe, S Lamm, C Schulz, D Strash 2020 proceedings of the SIAM workshop on combinatorial scientific computing …, 2020 | 54* | 2020 |

Accelerating local search for the maximum independent set problem J Dahlum, S Lamm, P Sanders, C Schulz, D Strash, RF Werneck Experimental Algorithms: 15th International Symposium, SEA 2016, St …, 2016 | 43 | 2016 |

Efficient Parallel Random Sampling—Vectorized, Cache-Efficient, and Online P Sanders, S Lamm, L Hübschle-Schneider, E Schrade, C Dachsbacher ACM Transactions on Mathematical Software (TOMS) 44 (3), 29, 2018 | 37 | 2018 |

Graph partitioning for independent sets S Lamm, P Sanders, C Schulz International Symposium on Experimental Algorithms, 68-81, 2015 | 22 | 2015 |

Recent Advances in Scalable Network Generation M Penschuck, U Brandes, M Hamann, S Lamm, U Meyer, I Safro, ... Massive Graph Analytics, 333-376, 2022 | 20 | 2022 |

Engineering kernelization for maximum cut D Ferizovic, D Hespe, S Lamm, M Mnich, C Schulz, D Strash 2020 Proceedings of the Twenty-Second Workshop on Algorithm Engineering and …, 2020 | 17* | 2020 |

Boosting Data Reduction for the Maximum Weight Independent Set Problem Using Increasing Transformations∗ A Gellner, S Lamm, C Schulz, D Strash, B Zaválnij 2021 Proceedings of the Workshop on Algorithm Engineering and Experiments …, 2021 | 13 | 2021 |

Recent Advances in Practical Data Reduction. FN Abu-Khzam, S Lamm, M Mnich, A Noe, C Schulz, D Strash Algorithms for Big Data, 97-133, 2022 | 12 | 2022 |

Finding near-optimal weight independent sets at scale E Großmann, S Lamm, C Schulz, D Strash Proceedings of the Genetic and Evolutionary Computation Conference, 293-302, 2023 | 7 | 2023 |

Recent advances in practical data reduction F Abu-Khzam, S Lamm, M Mnich, A Noe, C Schulz, D Strash arXiv preprint arXiv:2012.12594, 2020 | 7 | 2020 |

Communication-efficient Massively Distributed Connected Components S Lamm, P Sanders 2022 IEEE International Parallel and Distributed Processing Symposium (IPDPS …, 2022 | 2 | 2022 |

Targeted Branching for the Maximum Independent Set Problem D Hespe, S Lamm, C Schorr arXiv preprint arXiv:2102.01540, 2021 | 2 | 2021 |

Scalable Graph Algorithms using Practically Efficient Data Reductions S Lamm Karlsruhe Institute of Technology, 2022 | 1 | 2022 |

Algorithmen II P Sanders, T Bingmann, S Lamm, D Hespe | | |