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Learning Generalized Linear Models Over Normalized Data

Summary: Factorized learning for gradient-descent GLMs over normalized data; pushes computations through joins to avoid I/O redundancy. Empirical results show factorized learning faster than join-then-learn, with a cost-based strategy; extends to multi-table joins and Hive. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
4995
Venue
SIGMOD
Year
2015
Pagerank
0.00014655327
Overall Rank
715 | 95.10%
DOI
10.1145/2723372.2723713

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{kumar_sigmod15,
        title = {{Learning Generalized Linear Models Over Normalized Data}},
        author = {Kumar, Arun and Naughton, Jeffrey and Patel, Jignesh M.},
        series = {{SIGMOD} '15},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/2723372.2723713},
        url = {https://dl.acm.org/doi/10.1145/2723372.2723713},
        year = {2015}
}

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