Database meets deep learning: Challenges and opportunities

  • Wei Wang
  • , Meihui Zhang
  • , Gang Chen
  • , H. V. Jagadish
  • , Beng Chin Ooi
  • , Kian Lee Tan

Research output: Contribution to journalArticlepeer-review

131 Citations (Scopus)

Abstract

Deep learning has recently become very popular on account of its incredible success in many complex datadriven applications, including image classification and speech recognition. The database community has worked on data-driven applications for many years, and therefore should be playing a lead role in supporting this new wave. However, databases and deep learning are different in terms of both techniques and applications. In this paper, we discuss research problems at the intersection of the two fields. In particular, we discuss possible improvements for deep learning systems from a database perspective, and analyze database applications that may benefit from deep learning techniques.

Original languageEnglish
Pages (from-to)17-22
Number of pages6
JournalSIGMOD Record
Volume45
Issue number2
DOIs
Publication statusPublished - Jun 2016
Externally publishedYes

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