ICML 2023poster9 citations
Auto-Differentiation of Relational Computations for Very Large Scale Machine Learning
Yuxin Tang, Zhimin Ding, Dimitrije Jankov, Binhang Yuan, Daniel Bourgeois, Chris Jermaine
Abstract
The relational data model was designed to facilitate large-scale data management and analytics. We consider the problem of how to differentiate computations expressed relationally. We show experimentally that a relational engine running an auto-differentiated relational algorithm can easily scale to very large datasets, and is competitive with state-of-the-art, special-purpose systems for large-scale distributed machine learning.
BibTeX
@inproceedings{icml2023_autodifferentiat,
title = {Auto-Differentiation of Relational Computations for Very Large Scale Machine Learning},
author = {Yuxin Tang and Zhimin Ding and Dimitrije Jankov and Binhang Yuan and Daniel Bourgeois and Chris Jermaine},
booktitle = {ICML 2023},
year = {2023}
}