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TU Berlin

Inhalt des Dokuments

Publikationen

I

Scotty: Efficient Window Aggregation for out-of-order Stream Processing

Jonas Traub Philipp Grulich Alejandro Rodríıguez Cuéllar Sebastian Breß Asterios Katsifodimos Tilmann Rabl Volker Markl

International Conference on Data Engineering (ICDE 2018), 1300-1303. 2018

Link zur Publikation Download Bibtex Eintrag

Correlation Support for Risk Evaluation in Databases

Katrin Eisenreich, Jochen Adamek, Philipp Rösch, Volker Markl, Gregor Hackenbroich

International Conference on Data Engineering (ICDE) 2012

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Scalable Detection of Concept Drifts on Data Streams with Parallel Adaptive Windowing

Philipp M. Grulich, René Saitenmacher, Jonas Traub, Sebastian Breß, Tilmann Rabl, Volker Markl

International Conference on Extending Database Technology (EDBT 2018). 2018, 477-480. 2018

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Bridging the Gap: Towards Optimization Across Linear and Relational Algebra

Andreas Kunft Alexander Alexandrov Asterios Katsifodimos Volker Markl

International Workshop on Algorithms and Systems for MapReduce and Beyond (BeyondMR), in conjunction with SIGMOD/PODS in San Francisco 2016

Link zur Publikation Download Bibtex Eintrag

i

A distributed data exchange engine for polystores

Abdulrahman Kaitoua, Tilmann Rabl, Volker Markl

it - Information Technology 2020

Link zur Publikation Download Bibtex Eintrag

J

Cost-Based Predictive Spatiotemporal Join

Wook-Shin Han, Jaehwa Kim, Byung Suk Lee, Yufei Tao, Ralf Rantzau, Volker Markl

Journal IEEE Transactions on Knowledge and Data Engineering., 220-233. 2009

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M

Distributed Machine Learning - but at what COST?

Christoph Boden, Tilmann Rabl, Volker Markl

ML Systems Workshop@ NIPS2017 2017

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N

PEEL: A Framework for benchmarking distributed systems and algorithms

Christoph Boden, Alexander Alexandrov, Andreas Kunft, Tilmann Rabl, Volker Markl

Ninth TPC Technology Conference on Performance Evaluation & Benchmarking (TPCTC 2017) @VLDB 2017 2017

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P


p

Towards Unsupervised Data Quality Validation on Dynamic Data

Sergey Redyuk, Volker Markl, Sebastian Schelter

presented at International Workshop on Explainability for Trustworthy ML Pipelines (ETMLP) 2020

Link zur Publikation Download Bibtex Eintrag

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