- Andreas Kipf, Ryan Marcus, Alexander van Renen, Mihail Stoian, Alfons Kemper, Tim Kraska, Thomas Neumann:
RadixSpline: a single-pass learned index. aiDM@SIGMOD 2020: 5:1-5:5 - Lucas Woltmann
, Claudio Hartmann, Dirk Habich, Wolfgang Lehner:
Best of both worlds: combining traditional and machine learning models for cardinality estimation. aiDM@SIGMOD 2020: 4:1-4:8 - 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 [contents] - 2019
- Ali Hadian, Thomas Heinis:
Considerations for handling updates in learned index structures. aiDM@SIGMOD 2019: 3:1-3:4 - Vincenzo Di Cicco, Donatella Firmani, Nick Koudas, Paolo Merialdo, Divesh Srivastava:
Interpreting deep learning models for entity resolution: an experience report using LIME. aiDM@SIGMOD 2019: 8:1-8:4 - Raul Castro Fernandez, Samuel Madden:
Termite: a system for tunneling through heterogeneous data. aiDM@SIGMOD 2019: 7:1-7:8 - Benjamin Hilprecht, Carsten Binnig, Uwe Röhm:
Towards learning a partitioning advisor with deep reinforcement learning. aiDM@SIGMOD 2019: 6:1-6:4 - Bhavya Karki, Fan Hu, Nithin Haridas, Suhail Barot, Zihua Liu, Lucile Callebert, Matthias Grabmair, Anthony Tomasic:
Question answering via web extracted tables. aiDM@SIGMOD 2019: 4:1-4:8 - Yangjun Sheng, Anthony Tomasic, Tieying Zhang, Andrew Pavlo:
Scheduling OLTP transactions via learned abort prediction. aiDM@SIGMOD 2019: 1:1-1:8 - Lucas Woltmann, Claudio Hartmann, Maik Thiele, Dirk Habich, Wolfgang Lehner:
Cardinality estimation with local deep learning models. aiDM@SIGMOD 2019: 5:1-5:8 - Liqi Xu, Richard L. Cole, Daniel Ting:
Learning to optimize federated queries. aiDM@SIGMOD 2019: 2:1-2:7 - 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 [contents] - 2018
- Gabriel Campero Durand, Marcus Pinnecke, Rufat Piriyev, Mahmoud Mohsen, David Broneske, Gunter Saake, Maya S. Sekeran, Fabián Rodriguez, Laxmi Balami:
GridFormation: Towards Self-Driven Online Data Partitioning using Reinforcement Learning. aiDM@SIGMOD 2018: 1:1-1:7 - Kouki Kawabata, Yasuko Matsubara, Yasushi Sakurai:
StreamScope: Automatic Pattern Discovery over Data Streams. aiDM@SIGMOD 2018: 5:1-5:8 - Ryan Marcus, Olga Papaemmanouil:
Deep Reinforcement Learning for Join Order Enumeration. aiDM@SIGMOD 2018: 3:1-3:4 - Tova Milo, Amit Somech:
Deep Reinforcement-Learning Framework for Exploratory Data Analysis. aiDM@SIGMOD 2018: 4:1-4:4 - Ed Seabolt, Eser Kandogan, Mary Roth:
Contextual Intelligence for Unified Data Governance. aiDM@SIGMOD 2018: 2:1-2:9 - Rajesh Bordawekar, Oded Shmueli:
Proceedings of the First International Workshop on Exploiting Artificial Intelligence Techniques for Data Management, aiDM@SIGMOD 2018, Houston, TX, USA, June 10, 2018. ACM 2018 [contents]
