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Lab Lunch Talk: Databases + ML = In-Database Learning

Speaker: Milos Nikolic

What
When Dec 10, 2019
from 01:00 PM to 02:00 PM
Where MF2
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Abstract:

I will present the idea of learning models over relational databases, an emerging approach known as in-database learning. I will demonstrate how one can cast a machine learning problem into a database problem by decomposing the learning task into a batch of SQL aggregates and by computing these aggregates over the input database. This approach benefits tremendously from structural properties of the relational data, factorized query evaluation, and query compilation. In practice, this can lead to orders of magnitude better performance than state-of-the-art data management and machine learning systems.

 

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