Publications IAM

In: Proceedings of the International Conference on Management of Data (SIGMOD/PODS) SIGMOD/PODS '21: Proceedings of the 2021 International Conference on Management of Data. ACM SIGMOD International Conference on Management of Data (SIGMOD-2021) Pages 2450-2463 ISBN 978-145038343-1 ACM New York, NY 2021.

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In: Datenbank-Spektrum (Spektrum) 21 3 Pages 203-212 Springer 2021.

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In: Design, Automation & Test in Europe. Design, Automation & Test in Europe (DATE-2020) March 9-13 Grenoble, France IEEE 2020.

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In: David Maier, Rachel Pottinger (editor). Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data. ACM SIGMOD International Conference on Management of Data (SIGMOD-2020) June 14-19 Portland OR United States Pages 1633-1649 ISBN 978-1-4503-6735-6 The Association for Computing Machinery 2020.

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In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data. ACM SIGMOD International Conference on Management of Data (SIGMOD) New York, NY, USA SIGMOD ’20 ISBN 9781450367356 Association for Computing Machinery 2020.

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In: Computing Research Repository eprint Journal (CoRR) abs/1910.07867 Pages 1-11 arXiv 2020.

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In: Proceedings of the VLDB Endowment (PVLDB) 13 12 Pages 2801-2804 VLDB Endowment 2020.

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In: DEBS'20: 14th ACM International Conference on Distributed and Event-Based Systems. ACM International Conference on Distributed and Event-Based Systems (DEBS-2020) ACM 2020.

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In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data. ACM SIGMOD International Conference on Management of Data (SIGMOD-2020) Pages 2487-2503 ACM 2020.

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In: SIGMOD '19: Proceedings of the 2019 International Conference on Management of Data. ACM SIGMOD International Conference on Management of Data (SIGMOD-2019) June 30-July 5 Amsterdam Netherlands Pages 607-622 ISBN 978-1-4503-5643-5 ACM New York, NY 6/2019.

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Intelligent Analytics for Massive Data

PUBLICATIONS

ExDRa: Exploratory Data Science on Federated Raw Data.

Continuous Training and Deployment of Deep Learning Models

Efficient Compilation and Execution of JVM-Based Data Processing Frameworks on Heterogeneous Co-Processors

Pump Up the Volume: Processing Large Data on GPUs with Fast Interconnects

Optimizing Machine Learning Workloads in Collaborative Environments

The NebulaStream Platform: Data and Application Management for the Internet of Things

Demand-based sensor data gathering with multi-query optimization

A Survey of Adaptive Sampling and Filtering Algorithms for the Internet of Things

Grizzly: Efficient Stream Processing Through Adaptive Query Compilation

AStream: Ad-hoc Shared Stream Processing

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