# F-IVM: Learning over Fast-Evolving Relational Data

arXiv: https://arxiv.org/abs/2006.00694 · HTML: https://mlsanity.com/paper/2006.00694/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 1 Jun 2020.

## Built on by (most cited first, 3 of 3)

- [ARM-Net: Adaptive Relation Modeling Network for Structured Data](https://mlsanity.com/paper/2107.01830/) (2021)
- [Powering In-Database Dynamic Model Slicing for Structured Data Analytics](https://mlsanity.com/paper/2405.00568/) (2024)
- [In-Database Data Imputation](https://mlsanity.com/paper/2401.03359/) (2024)

## Abstract (arXiv)

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.