Factorized Databases
Dan Olteanu, Maximilian Schleich · ACM SIGMOD Record · 2016
This paper overviews factorized databases and their application to machine learning. The key observation underlying this work is that state-of-the-art relational query processing entails a high degree of redundancy in the computation and representation of query results. This redundancy can be avoided and is not necessary for subsequent analytics such as learning regression models.