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An Intermediate Representation for Optimizing Machine Learning Pipelines

Andreas Kunft, Asterios Katsifodimos, Sebastian Schelter, Sebastian Breß, Tilmann Rabl, Volker Markl

Proceedings of the VLDB Endowment, 1553-1567. 2019

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Myriad: Scalable and Expressive Data Generation.

Alexander Alexandrov, Kostas Tzoumas, Volker Markl

Proceedings of the VLDB Endowment, 1890-1893. 2012

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AJoin: Adhoc Stream Joins at Scale

Jeyhun Karimov, Tilmann Rabl, Volker Markl

Proceedings of the VLDB Endowment 2020

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Spinning Fast Iterative Data Flows

Stephan Ewen, Kostas Tzoumas, Moritz Kaufmann, Volker Markl

Proceedings of the VLDB Endowment (PVLDB),, 1268-1279. 2012

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Estimating Join Selectivities using Bandwidth-Optimized Kernel Density Models

Martin Kiefer, Max Heimel, Sebastian Breß, Volker Markl

Proceedings of the VLDB Endowment, Volume 10, No. 13. 2017 (to be presented in VLDB 2018) 2017

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STREAMLINE - Streamlined Analysis of Data at Rest and Data in Motion

Philipp M. Grulich, Tilmann Rabl, Volker Markl, Csaba Sidló, Andras Benczur

Proceedings of the Workshops of the EDBT/ICDT 2017 Joint Conference 2017

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Hardware-Oblivious Parallelism for In-Memory Column-Stores

Max Heimel and Michael Saecker and Holger Pirk and Stefan Manegold and Volker Markl

PVLDB, 709-720. 2013

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Scotch: Generating FPGA-Accelerators for Sketching at Line Rate

Martin Kiefer, Ilias Poulakis, Sebastian Breß, Volker Markl

PVLDB 2021

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Parallelizing query optimization

Wook-Shin Han and Wooseong Kwak and Jinsoo Lee and Guy M. Lohman and Volker Markl

PVLDB, 188-200. 2008

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Fault-Tolerance for Distributed Iterative Dataflows in Action

Chen Xu, Rudi Poepsel Lemaitre, Juan Soto, Volker Markl

PVLDB 11(12), 1990-1993. 2018

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