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aiDM@ACM SIGMOD Conference 2019: Amsterdam, The Netherlands

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Rajesh Bordawekar, Oded Shmueli:
Proceedings of the Second International Workshop on Exploiting Artificial Intelligence Techniques for Data Management, aiDM@SIGMOD 2019, Amsterdam, The Netherlands, July 5, 2019. ACM 2019, ISBN 978-1-4503-6802-5
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Yangjun Sheng, Anthony Tomasic, Tieying Zhang, Andrew Pavlo:
Scheduling OLTP transactions via learned abort prediction. 1:1-1:8
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Liqi Xu, Richard L. Cole, Daniel Ting:
Learning to optimize federated queries. 2:1-2:7
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Ali Hadian, Thomas Heinis:
Considerations for handling updates in learned index structures. 3:1-3:4
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Bhavya Karki, Fan Hu, Nithin Haridas, Suhail Barot, Zihua Liu, Lucile Callebert, Matthias Grabmair, Anthony Tomasic:
Question answering via web extracted tables. 4:1-4:8
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Lucas Woltmann, Claudio Hartmann, Maik Thiele, Dirk Habich, Wolfgang Lehner:
Cardinality estimation with local deep learning models. 5:1-5:8
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Benjamin Hilprecht, Carsten Binnig, Uwe Röhm:
Towards learning a partitioning advisor with deep reinforcement learning. 6:1-6:4
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Raul Castro Fernandez, Samuel Madden:
Termite: a system for tunneling through heterogeneous data. 7:1-7:8
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Vincenzo Di Cicco, Donatella Firmani, Nick Koudas, Paolo Merialdo, Divesh Srivastava:
Interpreting deep learning models for entity resolution: an experience report using LIME. 8:1-8:4

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