[1] BlockJoin: Efficient Matrix Partitioning Through Joins. Andreas Kunft, Asterios Katsifodimos, Sebastian Schelter, Volker Markl. International Conference on Very Large Databases (VLDB). 2018.
[2]Automatically Tracking Metadata and Provenance of Machine Learning. Sebastian Schelter, Joos-Hendrik Böse, Johannes Kirschnick, Thoralf Klein, Stephan Seufert. Experiments Machine Learning Systems workshop at the conference on Neural Information Processing Systems (NIPS). 2017.
[3] Probabilistic Demand Forecasting at Scale. Joos-Hendrik Böse, Valentin Flunkert, Jan Gasthaus, Tim Januschowski, Dustin Lange, David Salinas, Sebastian Schelter, Matthias Seeger, Yuyang Wang. International Conference on Very Large Databases (VLDB). 2017.
[4] The Stratosphere platform for big data analytics. Alexander Alexandrov, Rico Bergmann, Stephan Ewen, Johann-Christoph Freytag, Fabian Hueske, Arvid Heise, Odej Kao, Marcus Leich, Ulf Leser, Volker Markl, Felix Naumann, Mathias Peters, Astrid Rheinländer, Matthias Sax, Sebastian Schelter, Mareike Höger, Kostas Tzoumas, Daniel Warneke. VLDB Journal. 2014.
[5] All Roads Lead to Rome: Optimistic Recovery for Distributed Iterative Data Processing. Sebastian Schelter, Stephan Ewen, Kostas Tzoumas, Volker Markl. ACM Conference on Information and Knowledge Management (CIKM). 2013.
[6] Scalable Similarity-Based Neighborhood Methods with MapReduce. Sebastian Schelter, Christoph Boden, Volker Markl. ACM Conference on Recommender Systems (RecSys). 2012.