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An Intermediate Representation for Hybrid Database and Machine Learning Workloads

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.

Computer Science
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An Intermediate Representation for Hybrid Database and Machine Learning Workloads

Semantic Scholar · Computer Science · 2021

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.

Source of record · Semantic Scholar

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