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Auto-Differentiation of Relational Computations for Very Large Scale Machine Learning
Yuxin Tang · Zhimin Ding · Dimitrije Jankov · Binhang Yuan · Daniel Bourgeois · Chris Jermaine

Tue Jul 25 05:00 PM -- 06:30 PM (PDT) @ Exhibit Hall 1 #316

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.

Author Information

Yuxin Tang (Rice University)
Yuxin Tang

My name is Yuxin Tang, 5th year PhD student at Rice.

Zhimin Ding (Rice University)
Dimitrije Jankov (Rice University)
Binhang Yuan (Swiss Federal Institute of Technology)
Daniel Bourgeois (Rice University)
Chris Jermaine

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