Quantum Machine Learning for Join Order Optimization using Variational Quantum Circuits-Reference-Cited by-同舟云学术

Quantum Machine Learning for Join Order Optimization using Variational Quantum Circuits

Published:2023-06-18 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the International Workshop on Big Data in Emergent Distributed Environments
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Author:

Winker Tobias¹^ORCID,Çalikyilmaz Umut¹^ORCID,Gruenwald Le²^ORCID,Groppe Sven¹^ORCID

Affiliation:

1. University of Lübeck, Lübeck, Germany

2. University of Oklahoma, Norman, USA

Funder

German Federal Ministry of Education and Research

Publisher

ACM

Reference41 articles.

1. [n. d.]. Reinforcement Learning with Tree-LSTM for Join Order Selection. https://github.com/TsinghuaDatabaseGroup/AI4DBCode/tree/master/RTOS. Commit bcb1fa8cab96b835138435151ed126c391d6a3d3. [n. d.]. Reinforcement Learning with Tree-LSTM for Join Order Selection. https://github.com/TsinghuaDatabaseGroup/AI4DBCode/tree/master/RTOS. Commit bcb1fa8cab96b835138435151ed126c391d6a3d3.

2. Learning-based Query Performance Modeling and Prediction

3. Matthias C Caro , Hsin-Yuan Huang , M Cerezo , Kunal Sharma , Andrew Sornborger , Lukasz Cincio , and Patrick J Coles . 2022. Generalization in quantum machine learning from few training data. Nat. Commun. 13, 1 ( 2022 ). Matthias C Caro, Hsin-Yuan Huang, M Cerezo, Kunal Sharma, Andrew Sornborger, Lukasz Cincio, and Patrick J Coles. 2022. Generalization in quantum machine learning from few training data. Nat. Commun. 13, 1 (2022).

4. Efficient Join Order Selection Learning with Graph-based Representation

5. Variational Quantum Reinforcement Learning via Evolutionary Optimization

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