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)
Incoming Non-self Citations Over Time
Authors
- 1. Arun Kumar
- 2. Jeffrey Naughton
- 3. Jignesh M. Patel
Incoming Citations (Sorted by Pagerank)
Showing 2 of 52 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 11,284 | Demonstration of OpenDBML, a Framework for Democratizing In-Database Machine Learning | 2023 | VLDB | 4.1905499e-05 |
| 11,681 | doppioDB 2.0: Hardware Techniques for Improved Integration of Machine Learning into Databases | 2019 | VLDB | 4.1905499e-05 |
Outgoing Citations (Sorted by Pagerank)
Showing 15 of 15 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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