Deep Learning Through the Lens of Classical SQL

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dc.contributor.authorDu, Len
dc.date.accessioned2020-12-24T20:26:36Z
dc.date.available2020-12-24T20:26:36Z
dc.date.issued2021-01-05
dc.description.abstractIn-database machine learning has been very popular, almost being a cliche. However, can we do it the other way around? In this work, we say “yes” by applying plain old SQL to Deep Learning (DL), in a sense, hypothetically implementing deep learning algorithms with SQL. Most deep learning frameworks, as well as generic machine learning ones, share a de facto standard of multidimensional array operations, underneath fancier infrastructure such as automatic differentiation. As SQL tables can be regarded as generalizations of (multi-dimensional) arrays, we have found a way to express common deep learning operations in SQL, encouraging a different way of thinking and thus potentially novel models. In particular, one of the latest trend in deep learning was the introduction of sparsity in the name of Graph Convolutional Networks (GCNs), whereas we take sparsity almost for granted in the database world. As both databases and machine learning involve transformation of datasets, we hope this work can inspire further works utilizing the large body of existing wisdom, algorithms and technologies in the database field to advance the state-of-the-art in machine learning, rather than merely integrating machine learning into databases.
dc.format.extent10 pages
dc.identifier.doi10.24251/HICSS.2021.832
dc.identifier.isbn978-0-9981331-4-0
dc.identifier.urihttp://hdl.handle.net/10125/71453
dc.language.isoEnglish
dc.relation.ispartofProceedings of the 54th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectComputational Intelligence and State-of-the-Art Data Analytics
dc.subjectdata analytics
dc.subjectdatabase
dc.subjectdeep learning
dc.subjectgraph convolutional network
dc.subjectmachine learning
dc.titleDeep Learning Through the Lens of Classical SQL
prism.startingpage6924

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