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Sebastian Lamm
Sebastian Lamm
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Title
Cited by
Cited by
Year
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
782016
Thrill: High-performance algorithmic distributed batch data processing with C++
T Bingmann, M Axtmann, E JŲbstl, S Lamm, HC Nguyen, A Noe, S Schlag, ...
2016 IEEE International Conference on Big Data (Big Data), 172-183, 2016
612016
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
602019
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
392016
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
37*2020
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
342019
Efficient Parallel Random Sampling—Vectorized, Cache-Efficient, and Online
P Sanders, S Lamm, L HŁbschle-Schneider, E Schrade, C Dachsbacher
ACM Transactions on Mathematical Software (TOMS) 44 (3), 29, 2018
292018
Graph partitioning for independent sets
S Lamm, P Sanders, C Schulz
International Symposium on Experimental Algorithms, 68-81, 2015
212015
Recent Advances in Scalable Network Generation
M Penschuck, U Brandes, M Hamann, S Lamm, U Meyer, I Safro, ...
Massive Graph Analytics, 333-376, 2022
132022
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
132020
Recent advances in practical data reduction
FN Abu-Khzam, S Lamm, M Mnich, A Noe, C Schulz, D Strash
Algorithms for Big Data: DFG Priority Program 1736, 97-133, 2023
72023
Boosting Data Reduction for the Maximum Weight Independent Set Problem Using Increasing Transformations∗
A Gellner, S Lamm, C Schulz, D Strash, B ZavŠlnij
2021 Proceedings of the Workshop on Algorithm Engineering and Experiments†…, 2021
72021
Finding Near-Optimal Weight Independent Sets at Scale
E GroŖmann, S Lamm, C Schulz, D Strash
arXiv preprint arXiv:2208.13645, 2022
12022
Targeted Branching for the Maximum Independent Set Problem
D Hespe, S Lamm, C Schorr
arXiv preprint arXiv:2102.01540, 2021
12021
Communication-efficient Massively Distributed Connected Components
S Lamm, P Sanders
2022 IEEE International Parallel and Distributed Processing Symposium (IPDPS†…, 2022
2022
Scalable Graph Algorithms using Practically Efficient Data Reductions
S Lamm
Karlsruhe Institute of Technology, 2022
2022
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