Demonstration of OpenDBML, a Framework for Democratizing In-Database Machine Learning
Summary: OpenDBML provides a unifying Python API and web-based extension points for diverse in-database ML engines and a curated dataset library, abstracting away ad-hoc UIs and proprietary data formats. Demo scenarios showcase plug-in of new systems/datasets and end-to-end, join-free in-DB ML workflows. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
No non-self incoming citations found for this paper in this database.
Authors
- 1. Mahdi Ghorbani
- 2. Amir Shaikhha
Incoming Citations (Sorted by Pagerank)
Showing 0 of 0 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 7 of 7 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 850 | Scaling Factorization Machines to Relational Data | 2013 | VLDB | 0.00015955971 |
| 1,167 | Learning Generalized Linear Models Over Normalized Data | 2015 | SIGMOD | 0.00013547713 |
| 1,279 | Towards Linear Algebra over Normalized Data | 2017 | VLDB | 0.00012868394 |
| 2,194 | Enabling and Optimizing Non-linear Feature Interactions in Factorized Linear Algebra | 2019 | SIGMOD | 9.3138337e-05 |
| 3,277 | A Layered Aggregate Engine for Analytics Workloads | 2019 | SIGMOD | 7.2871625e-05 |
| 4,787 | The Relational Data Borg is Learning | 2020 | VLDB | 5.9224501e-05 |
| 8,757 | An Intermediate Representation for Hybrid Database and Machine Learning Workloads | 2021 | VLDB | 4.456315e-05 |
Previous
Page 1 / 1
Next