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TU Berlin

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Publications

2017

Bonaventura Del Monte, Jeyhun Karimov, Alireza Rezaei Mahdiraji, Tilmann Rabl, Volker Markl (2017). PROTEUS: Scalable Online Machine Learning for Predictive Analytics and Real-Time Interactive Visualization. in Proc. 20th International Conference on Extending Database Technology (EDBT)

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Bonaventura Del Monte (2017). Efficient Migration of Very Large Distributed State for Scalable Stream Processing. Proceedings of the VLDB 2017 PhD Workshop

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Christoph Boden, Alexander Alexandrov, Andreas Kunft, Tilmann Rabl, Volker Markl (2017). PEEL: A Framework for benchmarking distributed systems and algorithms. Ninth TPC Technology Conference on Performance Evaluation & Benchmarking (TPCTC 2017) @VLDB 2017


Christoph Boden, Andrea Spina, Tilmann Rabl, Volker Markl. (2017). Benchmarking Data Flow Systems for Scalable Machine Learning. Proceedings of the 4th ACM SIGMOD Workshop on Algorithms and Systems for MapReduce and Beyond (BeyondMR'17), Jan Hidders (Ed.). ACM, New York, NY, USA, Article 5, 10 pages., 10.

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Tilmann Rabl, Arne Jacobsen (2017). Query Centric Partitioning and Allocation for Partially Replicated Database Systems. In Proceedings of the 2017 ACM International Conference on Management of Data (SIGMOD '17). ACM, New York, NY, USA,, 315-330..

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Sebastian Dorok, Sebastian Breß, Jens Teubner, Horstfried Läpple, Gunter Saake, Volker Markl (2017). Efficient Storage and Analysis of Genome Data in Databases. Proceedings of 17th Conference on Database Systems for Business, Technology, and Web (BTW), LNI 2017, 423-442.

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Jonas Traub, Nikolaas Steenbergen, Philipp Grulich, Tilmann Rabl, and Volker Markl. (2017). I²: Interactive Real-Time Visualization for Streaming Data.. in Proc. 20th International Conference on Extending Database Technology (EDBT), March 21-24, 2017.

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Christoph Boden, Tilmann Rabl, Volker Markl (2017). Distributed Machine Learning - but at what COST?. ML Systems Workshop@ NIPS2017

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Jonas Traub, Sebastian Breß, Tilmann Rabl, Asterios Katsifodimos, Volker Markl (2017). Optimized On-Demand Data Streaming from Sensor Nodes. In Proceedings of SoCC ’17, Santa Clara, CA, USA, September 24–27, 12.

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Martin Kiefer, Max Heimel, Sebastian Breß, Volker Markl (2017). Estimating Join Selectivities using Bandwidth-Optimized Kernel Density Models. Proceedings of the VLDB Endowment, Volume 10, No. 13. 2017 (to be presented in VLDB 2018)

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