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Volume 14, No. 12
An Intermediate Representation for Hybrid Database and Machine Learning Workloads
Authors:
Amir Shaikhha (University of Edinburgh), Maximilian Schleich (University of Washington), Dan Olteanu (University of Zurich)
Abstract
IFAQ is an intermediate representation and compilation framework for hybrid database and machine learning workloads expressible using iterative programs with functional aggregate queries. We demonstrate IFAQ for several OLAP queries, linear algebra expressions, and learning factorization machines over training datasets defined by feature extraction queries over relational databases.
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