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Workshop on Interactive and Adaptive Learning in an Open World

  • Alexander FreytagEmail author
  • Vittorio Ferrari
  • Mario Fritz
  • Uwe Franke
  • Terrence Boult
  • Juergen Gall
  • Walter Scheirer
  • Angela Yao
  • Erik Rodner
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11134)

Abstract

Next generation machine learning requires stepping away from classical batch learning towards interactive and adaptive learning. This is essential to cope with demanding machine learning applications we have already today. Our workshop at ECCV 2018 in Munich therefore served as a discussion forum for experts in this field and in the following we give a brief overview. Please note that this discussion paper has not been not peer-reviewed and only contains the subjective summary of the workshop organizers.

Keywords

Interactive learning Adaptive learning Open set Continuous learning 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Alexander Freytag
    • 1
    Email author
  • Vittorio Ferrari
    • 2
    • 3
  • Mario Fritz
    • 4
  • Uwe Franke
    • 5
  • Terrence Boult
    • 6
  • Juergen Gall
    • 7
  • Walter Scheirer
    • 8
  • Angela Yao
    • 7
  • Erik Rodner
    • 1
  1. 1.Carl Zeiss AGJenaGermany
  2. 2.GoogleMountain ViewUSA
  3. 3.University of EdinburghEdinburghUK
  4. 4.CISPA Helmholtz Center i.G.SaarbrückenGermany
  5. 5.Daimler AGStuttgartGermany
  6. 6.University of Colorado, Colorado SpringsColorado SpringsUSA
  7. 7.University of BonnBonnGermany
  8. 8.University of Notre DameNotre DameUSA

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