@inproceedings{UrbanoRomero2024, author = {Urbano, Alonso and Romero, David W.}, title = {Self-Supervised Detection of Perfect and Partial Input-Dependent Symmetries}, booktitle = {Proceedings of the Geometry-grounded Representation Learning and Generative Modeling Workshop (GRaM) at ICML 2024}, year = {2024}, language = {en} } @inproceedings{ClauseckerSchintke2021, author = {Clausecker, Robert and Schintke, Florian}, title = {A Measure of Quality for IDA* Heuristics}, booktitle = {Proceedings of the Fourteenth International Symposium on Combinatorial Search (SoCS 2021)}, pages = {55 -- 63}, year = {2021}, language = {en} } @inproceedings{KaiserClausecker2021, author = {Kaiser, Benjamin and Clausecker, Robert}, title = {CleanMaple}, booktitle = {Proceedings of SAT Competition 2021 : Solver and Benchmark Descriptions}, pages = {24}, year = {2021}, language = {en} } @inproceedings{KaiserClausecker2021, author = {Kaiser, Benjamin and Clausecker, Robert}, title = {CleanMaple_PriPro, CaDiCaL_PriPro and CaDiCaL_PriPro_no_bin}, booktitle = {Proceedings of SAT Competition 2021 : Solver and Benchmark Descriptions}, pages = {25}, year = {2021}, language = {en} } @inproceedings{FuerstRakow2022, author = {F{\"u}rst, Steffen and Rakow, Christian}, title = {Parallelization of large-scale agent-based epidemiological simulations}, booktitle = {Proceedings of the 34th European Modeling \& Simulation Symposium}, doi = {https://doi.org/10.46354/i3m.2022.emss.008}, year = {2022}, abstract = {Agent-based epidemiological models have been applied widely successfully during the SARS-CoV-2 pandemic and assisted policymakers in assessing the effectiveness of intervention strategies. The computational complexity of agent-based models is still challenging, and therefore it is important to utilize modern multi-core systems as good as possible. In this paper, we are presenting our work on parallelizing the epidemiological simulation model MATSim Episim. Episim combines a large-scale person-centric human mobility model with a mechanistic model of infection and a person-centric disease progression model. In general, the parallelization of agent-based models with an inherent sequential structure — in the case of epidemiological models, the temporal order of the individual movements of the agents — is challenging. Especially when the underlying social network is irregular and dynamic, they require frequent communication between the processing elements. In Episim, however, we were able to take advantage of the fact that people are not contagious on the same day they become infected, and therefore immediate health synchronization is not required. By parallelizing some of the most computationally intensive submodels, we are now able to run MATSim Episim simulations up to eight times faster than the serial version. This makes it feasible to increase the number of agents, e.g. to run simulations for the whole of Germany instead of just Berlin as before.}, language = {en} } @inproceedings{ShinanoTateiwaNakamuraetal.2020, author = {Shinano, Yuji and Tateiwa, N. and Nakamura, S. and Yoshida, A. and Yasuda, M. and Kaji, S. and Fujisawa, K.}, title = {Massive Parallelization for Finding Shortest Lattice Vectors Based on Ubiquity Generator Framework}, booktitle = {2020 SC20: International Conference for High Performance Computing, Networking, Storage and Analysis (SC)}, doi = {10.1109/SC41405.2020.00064}, pages = {834 -- 848}, year = {2020}, abstract = {Lattice-based cryptography has received attention as a next-generation encryption technique, because it is believed to be secure against attacks by classical and quantum computers. Its essential security depends on the hardness of solving the shortest vector problem (SVP). In the cryptography, to determine security levels, it is becoming significantly more important to estimate the hardness of the SVP by high-performance computing. In this study, we develop the world's first distributed and asynchronous parallel SVP solver, the MAssively Parallel solver for SVP (MAP-SVP). It can parallelize algorithms for solving the SVP by applying the Ubiquity Generator framework, which is a generic framework for branch-and-bound algorithms. The MAP-SVP is suitable for massive-scale parallelization, owing to its small memory footprint, low communication overhead, and rapid checkpoint and restart mechanisms. We demonstrate its performance and scalability of the MAP-SVP by using up to 100,032 cores to solve instances of the Darmstadt SVP Challenge.}, language = {en} } @inproceedings{PfetschPokutta2020, author = {Pfetsch, Marc and Pokutta, Sebastian}, title = {IPBoost - Non-Convex Boosting via Integer Programming}, booktitle = {Proceedings of ICML}, arxiv = {http://arxiv.org/abs/2002.04679}, year = {2020}, language = {en} } @inproceedings{PokuttaSinghTorrico2020, author = {Pokutta, Sebastian and Singh, M. and Torrico, A.}, title = {On the Unreasonable Effectiveness of the Greedy Algorithm: Greedy Adapts to Sharpness}, booktitle = {Proceedings of ICML}, arxiv = {http://arxiv.org/abs/2002.04063}, year = {2020}, language = {en} } @inproceedings{DiakonikolasCardereraPokutta2020, author = {Diakonikolas, Jelena and Carderera, Alejandro and Pokutta, Sebastian}, title = {Locally Accelerated Conditional Gradients}, booktitle = {Proceedings of AISTATS}, arxiv = {http://arxiv.org/abs/1906.07867}, year = {2020}, language = {en} } @inproceedings{CombettesPokutta2020, author = {Combettes, Cyrille W. and Pokutta, Sebastian}, title = {Boosting Frank-Wolfe by Chasing Gradients}, booktitle = {Proceedings of ICML}, arxiv = {http://arxiv.org/abs/2003.06369}, year = {2020}, language = {en} }