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Contraction Clustering (RASTER): A Very Fast Big Data Algorithm for Sequential and Parallel Density-Based Clustering in Linear Time, Constant Memory, and a Single Pass., , , , and . CoRR, (2019)S-RASTER: contraction clustering for evolving data streams., , , , and . J. Big Data, 7 (1): 62 (2020)A Performance Evaluation of Federated Learning Algorithms., , , , and . DIDL@Middleware, page 1-8. ACM, (2018)Contraction Clustering (Raster) - A Big Data Algorithm for Density-Based Clustering in Constant Memory and Linear Time., , and . MOD, volume 10710 of Lecture Notes in Computer Science, page 63-75. Springer, (2017)Functional Federated Learning in Erlang (ffl-erl)., , and . WFLP, volume 11285 of Lecture Notes in Computer Science, page 162-178. Springer, (2018)Active-Code Replacement in the OODIDA Data Analytics Platform., , and . Euro-Par Workshops, volume 11997 of Lecture Notes in Computer Science, page 715-719. Springer, (2019)OODIDA: On-board/Off-board Distributed Data Analytics for Connected Vehicles., , and . CoRR, (2019)S-RASTER: Contraction Clustering for Evolving Data Streams., , , , and . CoRR, (2019)Facilitating rapid prototyping in the distributed data analytics platform OODIDA via active-code replacement., , , , and . Array, (2020)OODIDA: On-Board/Off-Board Distributed Real-Time Data Analytics for Connected Vehicles., , , , and . Data Sci. Eng., 6 (1): 102-117 (2021)