F-IVM: Learning over Fast-Evolving Relational Data

@article{Nikolic2020FIVMLO,
  title={F-IVM: Learning over Fast-Evolving Relational Data},
  author={M. Nikolic and Haozhe Zhang and Ahmet Kara and D. Olteanu},
  journal={Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data},
  year={2020}
}
  • M. Nikolic, Haozhe Zhang, +1 author D. Olteanu
  • Published 2020
  • Computer Science
  • Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data
  • F-IVM is a system for real-time analytics such as machine learning applications over training datasets defined by queries over fast-evolving relational databases. We will demonstrate F-IVM for three such applications: model selection, Chow-Liu trees, and ridge linear regression. 
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