This paper develops more formally the tensor-decomposition framework for
semantic optimization.

Authors: Mahmoud Abo Khamis, Ryan R. Curtin, Benjamin Moseley, Hung Q. Ngo, Xuan
Long Nguyen, Dan Olteanu, Maximilian Schleich. 2020.

In ACM Transactions on Database Systems (TODS ‘20). Vol. 45, No. 4,
Article 17.

Motivated by fundamental applications in databases and relational machine
learning, we formulate and study the problem of answering functional aggregate
queries (FAQ) in which some of the input factors are defined by a collection of
additive inequalities between variables. We refer to these queries as FAQ-AI for
short. We present three applications of our FAQ-AI framework to relational
machine learning: k-means clustering, training linear support vector machines,
and training models using non-polynomial loss.

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Functional Aggregate Queries with Additive Inequalities