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Introduction to NIPS 2017 Competition Track

  • Sergio Escalera
  • Markus Weimer
  • Mikhail Burtsev
  • Valentin Malykh
  • Varvara Logacheva
  • Ryan Lowe
  • Iulian Vlad Serban
  • Yoshua Bengio
  • Alexander Rudnicky
  • Alan W. Black
  • Shrimai Prabhumoye
  • Łukasz Kidziński
  • Sharada Prasanna Mohanty
  • Carmichael F. Ong
  • Jennifer L. Hicks
  • Sergey Levine
  • Marcel Salathé
  • Scott Delp
  • Iker Huerga
  • Alexander Grigorenko
  • Leifur Thorbergsson
  • Anasuya Das
  • Kyla Nemitz
  • Jenna Sandker
  • Stephen King
  • Alexander S. Ecker
  • Leon A. Gatys
  • Matthias Bethge
  • Jordan Boyd-Graber
  • Shi Feng
  • Pedro Rodriguez
  • Mohit Iyyer
  • He He
  • Hal DauméIII
  • Sean McGregor
  • Amir Banifatemi
  • Alexey Kurakin
  • Ian Goodfellow
  • Samy Bengio
Conference paper
Part of the The Springer Series on Challenges in Machine Learning book series (SSCML)

Abstract

Competitions have become a popular tool in the data science community to solve hard problems, assess the state of the art and spur new research directions. Companies like Kaggle and open source platforms like Codalab connect people with data and a data science problem to those with the skills and means to solve it. Hence, the question arises: What, if anything, could NIPS add to this rich ecosystem?

In 2017, we embarked to find out. We attracted 23 potential competitions, of which we selected five to be NIPS 2017 competitions. Our final selection features competitions advancing the state of the art in other sciences such as “Classifying Clinically Actionable Genetic Mutations” and “Learning to Run”. Others, like “The Conversational Intelligence Challenge” and “Adversarial Attacks and Defences” generated new data sets that we expect to impact the progress in their respective communities for years to come. And “Human-Computer Question Answering Competition” showed us just how far we as a field have come in ability and efficiency since the break-through performance of Watson in Jeopardy. Two additional competitions, DeepArt and AI XPRIZE Milestions, were also associated to the NIPS 2017 competition track, whose results are also presented within this chapter.

Notes

Acknowledgements

The NIPS 2017 Competition track was sponsored by NIPS and ChaLearn.

The Conversational Intelligence Challenge was partially sponsored by Facebook, Flint Capital, IVADO, Microsoft Maluuba, Element AI.

The Learning to Run Challenge was organized by the Mobilize Center at Stanford University, a National Institutes of Health Big Data to Knowledge (BD2K) Center of Excellence supported through Grant U54EB020405, and by the crowdAI.org platform. The challenge was partially sponsored by NVIDIA, Amazon Web Services and Toyota Research Institute.

The Neural Art Challenge was sponsored by a number of sponsors, who we would like to thank. DeepArt.io sponsored the high-resolution renderings. ChaLearn.org sponsored the printing of the posters. Prices were sponsored by NVIDIA.

The IBM Watson AI XPRIZE is sponsored by IBM Watson.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Sergio Escalera
    • 1
  • Markus Weimer
    • 2
  • Mikhail Burtsev
    • 3
  • Valentin Malykh
    • 3
  • Varvara Logacheva
    • 3
  • Ryan Lowe
    • 4
  • Iulian Vlad Serban
    • 5
  • Yoshua Bengio
    • 5
  • Alexander Rudnicky
    • 6
  • Alan W. Black
    • 6
  • Shrimai Prabhumoye
    • 6
  • Łukasz Kidziński
    • 8
  • Sharada Prasanna Mohanty
    • 7
  • Carmichael F. Ong
    • 8
  • Jennifer L. Hicks
    • 9
  • Sergey Levine
    • 10
  • Marcel Salathé
    • 11
  • Scott Delp
    • 8
  • Iker Huerga
    • 12
  • Alexander Grigorenko
    • 13
  • Leifur Thorbergsson
    • 14
  • Anasuya Das
    • 14
  • Kyla Nemitz
    • 12
  • Jenna Sandker
    • 15
  • Stephen King
    • 15
  • Alexander S. Ecker
    • 23
  • Leon A. Gatys
    • 16
  • Matthias Bethge
    • 23
  • Jordan Boyd-Graber
    • 17
  • Shi Feng
    • 18
  • Pedro Rodriguez
    • 18
  • Mohit Iyyer
    • 24
  • He He
    • 25
  • Hal DauméIII
    • 26
  • Sean McGregor
    • 19
    • 20
  • Amir Banifatemi
    • 21
  • Alexey Kurakin
    • 27
  • Ian Goodfellow
    • 22
  • Samy Bengio
    • 22
  1. 1.Department Mathematics & InformaticsUniversity of BarcelonaBarcelonaSpain
  2. 2.Microsoft (United States)RedmondUSA
  3. 3.Moscow Institute of Physics and TechnologyMoscowRussia
  4. 4.McGill UniversityMontrealCanada
  5. 5.University of MontrealMontrealCanada
  6. 6.Carnegie Mellon UniversityPittsburghUSA
  7. 7.École Polytechnique Fédérale de LausanneLausanneSwitzerland
  8. 8.Stanford UniversityStanfordUSA
  9. 9.Department of BioengineeringStanford UniversityStanfordUSA
  10. 10.Department of Electrical Engineering and Computer SciencesUniversity of CaliforniaBerkeleyUSA
  11. 11.School of Computer and Communication Sciences, EPFLLausanneSwitzerland
  12. 12.Director of Engineering and Applied Machine LearningMemorial Sloan Kettering Cancer CenterNew YorkUSA
  13. 13.Lead Data ScientistMemorial Sloan Kettering Cancer CenterNew YorkUSA
  14. 14.Sr Data ScientistMemorial Sloan Kettering Cancer CenterNew YorkUSA
  15. 15.Talent Community ManagerMemorial Sloan Kettering Cancer CenterNew YorkUSA
  16. 16.University of TuebingenTuebingenGermany
  17. 17.Computer Science, iSchool UMIACS, Language ScienceUniversity of MarylandCollege ParkUSA
  18. 18.Computer ScienceUniversity of MarylandCollege ParkUSA
  19. 19.Technical LeadIBM Watson AI XPRIZE, XPRIZE FoundationCulver CityUSA
  20. 20.Member of Technical StaffSyntiant CorporationIrvineUSA
  21. 21.Artificial Intelligence Lead and IBM Watson AI XPRIZE Lead, XPRIZE FoundationCulver CityUSA
  22. 22.Google BrainMountain ViewUSA
  23. 23.University of TübingenTübingenGermany
  24. 24.UMass AmherstAmherstUSA
  25. 25.Stanford UniversityCaliforniaUSA
  26. 26.University of MarylandMarylandUSA
  27. 27.Google, San FranciscoBay AreaUSA

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