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aiDM@ACM SIGMOD Conference 2020: Portland, Oregon, USA
- Rajesh Bordawekar, Oded Shmueli, Nesime Tatbul, Tin Kam Ho:

Proceedings of the Third International Workshop on Exploiting Artificial Intelligence Techniques for Data Management, aiDM@SIGMOD 2020, Portland, Oregon, USA, June 19, 2020. ACM 2020, ISBN 978-1-4503-8029-4 - Vahid Ghadakchi, Mian Xie, Arash Termehchy:

Bandit join: preliminary results. 1:1-1:4 - Zhiwei Fan, Rathijit Sen, Paraschos Koutris, Aws Albarghouthi:

Automated tuning of query degree of parallelism via machine learning. 2:1-2:4 - Runsheng Benson Guo, Khuzaima Daudjee:

Research challenges in deep reinforcement learning-based join query optimization. 3:1-3:6 - Lucas Woltmann

, Claudio Hartmann
, Dirk Habich, Wolfgang Lehner
:
Best of both worlds: combining traditional and machine learning models for cardinality estimation. 4:1-4:8 - Andreas Kipf, Ryan Marcus, Alexander van Renen, Mihail Stoian, Alfons Kemper, Tim Kraska, Thomas Neumann:

RadixSpline: a single-pass learned index. 5:1-5:5 - Ahmed S. Abdelhamid, Walid G. Aref

:
PartLy: learning data partitioning for distributed data stream processing. 6:1-6:4

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