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Open Space Topic “The Organization of Challenges for the Benefit of More Diverse Communities”
Adrienne Mendrik · Isabelle Guyon · Wei-Wei Tu · Evelyne Viegas · Ming LI

Fri Dec 13 04:15 PM -- 06:00 PM (PST) @
in CiML 2019: Machine Learning Competitions for All »

“Open Space” is a technique for running meetings where the participants create and manage the agenda themselves. Participants can propose ideas that address the open space topic, these will be divided into various sessions that all other participants can join and brainstorm about. After the open space we will collect all the ideas and post them on the CiML website.

Author Information

Adrienne Mendrik (Netherlands eScience Center)
Isabelle Guyon (UPSud, INRIA, University Paris-saclay and ChaLearn)
Isabelle Guyon

Isabelle Guyon recently joined Google Brain as a research scientist. She is also professor of artificial intelligence at Université Paris-Saclay (Orsay). Her areas of expertise include computer vision, bioinformatics, and power systems. She is best known for being a co-inventor of Support Vector Machines. Her recent interests are in automated machine learning, meta-learning, and data-centric AI.  She has been a strong promoter of challenges and benchmarks, and is president of ChaLearn, a non-profit dedicated to organizing machine learning challenges. She is community lead of Codalab competitions, a challenge platform used both in academia and industry. She co-organized the “Challenges in Machine Learning Workshop” @ NeurIPS between 2014 and 2019, launched the "NeurIPS challenge track" in 2017 while she was general chair, and pushed the creation of the "NeurIPS datasets and benchmark track" in 2021, as a NeurIPS board member.

Wei-Wei Tu (4Paradigm Inc.)
Evelyne Viegas (Microsoft Research)
Ming LI (Nanjing University)

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