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Enabling and Optimizing Non-linear Feature Interactions in Factorized Linear Algebra

Summary: Introduces nonlinear pairwise feature interactions in factorized linear algebra for cross-table ML. Presents rewrite framework to exploit join+interaction redundancy; MorpheusFI prototype shows up to 5x speedups over materialized and 10x over SGD. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
h8147e6157f598835
Venue
SIGMOD
Year
2019
Pagerank
8.8750296e-05
Overall Rank
2,199 | 85.22%
DOI
10.1145/3299869.3319878

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{li_sigmod19,
        title = {{Enabling and Optimizing Non-linear Feature Interactions in Factorized Linear Algebra}},
        author = {Li, Side and Chen, Lingjiao and Kumar, Arun},
        series = {{SIGMOD} '19},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3299869.3319878},
        url = {https://dl.acm.org/doi/10.1145/3299869.3319878},
        year = {2019}
}

Incoming Citations (Sorted by Pagerank)

Showing 15 of 15 citing papers.

Rank Citing Paper Year Venue Pagerank
950 Lakehouse: A New Generation of Open Platforms that Unify Data Warehousing and Advanced Analytics 2021 CIDR 0.00012895553
3,449 Robust and Transferable Log-based Anomaly Detection 2023 SIGMOD 7.2931951e-05
4,489 ARM-Net: Adaptive Relation Modeling Network for Structured Data 2021 SIGMOD 6.5781098e-05
4,974 SPORES: Sum-Product Optimization via Relational Equality Saturation for Large Scale Linear Algebra 2020 VLDB 6.3318399e-05
7,201 Coresets over Multiple Tables for Feature-rich and Data-efficient Machine Learning 2023 VLDB 5.5871656e-05
8,798 Towards A Polyglot Framework for Factorized ML 2021 VLDB 5.2746322e-05
9,144 Cerebro: A Layered Data Platform for Scalable Deep Learning 2021 CIDR 5.2201471e-05
9,212 Powering In-Database Dynamic Model Slicing for Structured Data Analytics 2024 VLDB 5.2060505e-05
9,556 Towards an Optimized GROUP BY Abstraction for Large-Scale Machine Learning 2021 VLDB 5.1572248e-05
9,876 MINT: Detecting Fraudulent Behaviors from Time-series Relational Data 2023 VLDB 5.1176637e-05
10,602 TranSQL+: Serving Large Language Models with SQL on Low-Resource Hardware 2026 SIGMOD 4.9793485e-05
10,653 InferF: Declarative Factorization of AI/ML Inferences over Joins 2026 SIGMOD 4.9793485e-05
11,706 Regularized Pairwise Relationship based Analytics for Structured Data 2023 SIGMOD 4.9793485e-05
11,791 Demonstration of OpenDBML, a Framework for Democratizing In-Database Machine Learning 2023 VLDB 4.9793485e-05
11,870 Givens QR Decomposition over Relational Databases 2022 SIGMOD 4.9793485e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 14 of 14 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
415 SystemML: Declarative Machine Learning on Spark 2016 VLDB 0.0001865959
521 Learning Linear Regression Models over Factorized Joins 2016 SIGMOD 0.00016929744
672 The TileDB Array Data Storage Manager 2017 VLDB 0.0001489638
730 Learning Generalized Linear Models Over Normalized Data 2015 SIGMOD 0.00014406936
777 To Join or Not to Join? Thinking Twice about Joins before Feature Selection 2016 SIGMOD 0.00014054709
851 Scaling Factorization Machines to Relational Data 2013 VLDB 0.00013457975
1,009 Simulation of Database-Valued Markov Chains Using SimSQL 2013 SIGMOD 0.00012539827
1,044 RIOT: I/O-Efficient Numerical Computing without SQL 2009 CIDR 0.00012332595
1,256 Towards Linear Algebra over Normalized Data 2017 VLDB 0.00011314687
1,614 Compressed Linear Algebra for Large-Scale Machine Learning 2016 VLDB 0.00010071891
3,330 SPOOF: Sum-Product Optimization and Operator Fusion for Large-Scale Machine Learning 2017 CIDR 7.4173693e-05
3,373 F: Regression Models over Factorized Views 2016 VLDB 7.3661025e-05
5,682 Demonstration of Santoku: Optimizing Machine Learning over Normalized Data 2015 VLDB 6.0397904e-05
6,987 SparkR: Scaling R Programs with Spark 2016 SIGMOD 5.6283496e-05
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