Challenges in Machine Learning (CiML) @NeurIPS 2019
Machine Learning Competitions for All NeurIPS 2019 workshop Friday December 13th, 2019. 08:00 AM - 06:00 PM West 215 + 216

[Program] - [Invited Speakers] - [Committee] - [Organizers] - [CALL-FOR-ABSTRACTS]
[Accepted Abstracts] - [Open Space Summary] - [Pictures]

Video Recordings
  • Part 1(Start until first coffee break)
  • Part 2(Coffee break until lunch break)
  • Part 3(Lunch until coffee break)
  • The open space was not recorded, but summaries can be foundhere.

  • Presentations Workshop presentations can be found on theprogram page.
    Invited Speakers

    Afbeeldingsresultaat voor frank hutter challenges

    Amir Banifatemi


    Emily M. Bender (University of Washington)

    Dina Machuve


    Frank Hutter (University of Freiburg)


    Challenges in machine learning and data science are open online competitions that address problems by providing datasets or simulated environments. They measure the performance of machine learning algorithms with respect to a given problem, resulting in a leaderboard. The playful nature of challenges naturally attracts students, making challenges a great teaching resource. However, in addition to the use of challenges as educational tools, challenges have a role to play towards a better democratization of AI and machine learning. They function as cost effective problem-solving tools and a means of encouraging the development of re-usable problem templates and open-sourced solutions. However, at present, the geographic, sociological repartition of challenge participants and organizers is very biased. While recent successes in machine learning have raised much hopes, there is a growing concern that the societal and economical benefits might increasingly be in the power and under control of a few.

    CiML (Challenges in Machine Learning) is a forum that brings together workshop organizers, platform providers, and participants to discuss best practices in challenge organization and new methods and application opportunities to design high impact challenges. Following the success of previous years' workshops, we will reconvene and discuss new opportunities for broadening our community.

    For this sixth edition of the CiML workshop at NeurIPS our objective is twofold: (1) We aim to enlarge the community, fostering diversity in the community of participants and organizers; (2) We aim to promote the organization of challenges for the benefit of more diverse communities.

    The workshop provides room for discussions on these topics, and aims to bring together potential partners to organize such challenges and stimulate "machine learning for good", i.e. the organization of challenges for the benefit of society. We have invited prominent speakers that have experience in this domain.

    Workshop Audience

    The CiML workshop is targeted at workshop organizers, participants, and anyone with a scientific problem involving machine learning that may be formulated as a challenge. The emphasis of the CiML workshop is on challenge design. Hence it complements nicely the workshop on the NeurIPS 2019 competition track and will help pave the way toward next year's competition program.

    Important Dates
    • Abstract submission deadline:September 16th, 2019(submission closed).
    • Acceptance decisions:October 1st, 2019.
    • Finalized program on website:October 7th, 2019.

    Related workshops: Workshop on the NeurIPS 2019 competition program
    Subpages(8):Accepted AbstractsCall for AbstractsCommitteeOpen SpaceOrganizersPicturesProgramSpeakers