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Workshop
Sat Dec 08 05:00 AM -- 03:30 PM (PST) @ Room 511 ABDE
CiML 2018 - Machine Learning competitions "in the wild": Playing in the real world or in real time
Isabelle Guyon · Evelyne Viegas · Sergio Escalera · Jacob D Abernethy





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Challenges in machine learning and data science are competitions running over several weeks or months to resolve problems using provided datasets or simulated environments. The playful nature of challenges naturally attracts students, making challenge a great teaching resource. For this fifth edition of the CiML workshop at NIPS we want to go beyond simple data science challenges using canned data. We will explore the possibilities offered by challenges in which code submitted by participants are evaluated "in the wild", directly interacting in real time with users or with real or simulated systems. Organizing challenges "in the wild" is not new. One of the most impactful such challenge organized relatively recently is the DARPA grant challenge 2005 on autonomous navigation, which accelerated research on autonomous vehicles, leading to self-driving cars. Other high profile challenge series with live competitions include RoboCup, which has been running from the past 22 years. Recently, the machine learning community has started being interested in such interactive challenges, with last year at NIPS the learning to run challenge, an reinforcement learning challenge in which a human avatar had to be controlled with simulated muscular contractions, and the ChatBot challenge in which humans and robots had to engage into an intelligent conversation. Applications are countless for machine learning and artificial intelligence programs to solve problems in real time in the real world, by interacting with the environment. But organizing such challenges is far from trivial
The workshop will give a large part to discussions around two principal axes: (1) Design principles and implementation issues; (2) Opportunities to organize new impactful challenges.
Our objectives include bringing together potential partner to organize new such challenges and stimulating "machine learning for good", i.e. the organization of challenges for the benefit of society.
CiML 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 propose to reconvene and discuss new opportunities for challenges "in the wild", one of the hottest topics in challenge organization. We have invited prominent speakers having experience in this domain.
The audience of this workshop is targeted to workshop organizers, participants, and anyone with scientific problem involving machine learning, which may be formulated as a challenge. The emphasis of the workshop is on challenge design. Hence it complements nicely the workshop on the NIPS 2018 competition track and will help paving the way toward next year's competition program.
Submit abstract (up to 2 pages) before October 10 by sending email to nips2018@chalearn.org. See http://ciml.chalearn.org/ciml2018#CALL.

Morning Welcome - - Isabelle Guyon and Evelyne Viegas (Announcement)
Evelyne Viegas
Esteban Arcaute and Umut Ozertem - Facebook project on developing benchmarks of algorithms in realistic settings (Invited talk)
Esteban Arcaute
Laura Seaman - Project Alloy – Machine Learning Challenges for Researching Human-Machine Teaming (Invited talk)
Laura Seaman
Live competiton 1: Pommerman (Competition)
Corpus for AutoML Pipelines, Richard Lippmann, Swoop Vattam, Pooya Khorrami, and Cagri Dagli (Poster)
Richard Lippmann, Pooya Khorrami
How to fail hosting data science contests with images, Evgeny Nizhibitsky, Artur Kuzin (Poster)
n01z3 Kuzin, Evgeny Nizhibitskiy
ML Benchmark Tools Package, Ryan Turner, Uber AI Labs (Poster)
Ryan Turner
Break, poster viewing 1 (Poster)
Grand-Challenge.org, James A. Meakin Bram van Ginneken (Poster)
James Meakin
Beyond the Leaderboard, Adrienne M. Mendrik, Stephen R. Aylward (Poster)
Adrienne Mendrik, Stephen R Aylward
Julien Hay, Bich-Liên Doan, Fabrice Popineau - Renewal news recommendation platform (Invited talk)
Julien Hay, Bich-Liên DOAN
Panel discussion. Design principles and implementation issues. (Discussion)
Sergio Escalera
Lunch Break, poster viewing 2 (Poster)
Afternoon Welcome - Isabelle Guyon and Evelyne Viegas (Announcement)
Isabelle Guyon
Mikhail Burtsev and Varvara Logacheva - Wild evaluation of chat-bots (Invited talk)
Mikhail Burtsev, Varvara Logacheva
Larry Jackel - Measuring Progress in Robotics (Invited talk)
Lawrence Jackel
Daniel Polani - Competitions to Challenge Artificial Intelligence: from the L-Game to RoboCup (Invited talk)
Daniel Polani
Antoine Marot - Learning to run a power network (Invited talk)
Antoine Marot
Multi-Agent RL in MalmO (MARLO) Competition, Diego Perez-Liebana Katja Hofmann Sharada Prasanna Mohanty Noburu Kuno Andre Kramer Sam Devlin Raluca D. Gaina Daniel Ionita (Poster)
Sharada Mohanty
Break, poster viewing 3 (Poster)
NASA Frontier Development Lab 2018, A. Bella, A. Chopra, W. Fawcett, R. Talebi, D. Angerhausen, A. Berea, N.A. Cabrol, C. Kempes, M. Mascaro (Poster)
Aaron C Bell
AutoDL challenge design and beta tests, Zhengying Liu, Olivier Bousquet, Andre Elisseeff, Isabelle Guyon, Adrien Pavao, Lisheng Sun-Hosoya, and Sebastien Treguer (Poster)
Zhengying Liu, Sébastien Treguer
TrackML, a Particle Physics Tracking Machine Learning Challenge, Jean-Roch Vlimant (Caltech), Vincenzo Innocente, Andreas Salzburger (CERN), Isabelle Guyon (ChaLearn), Sabrina Amrouche, Tobias Golling, Moritz Kiehn (Geneva University),David Rousseau∗, Yet (Poster)
Andrey Ustyuzhanin, jean-roch vlimant
L2RPN: Learning To Run a Power Network Competition, Antoine Marot, Balthazar Donon, Isabelle Guyon, Benjamin Donnot. (Poster)
Benjamin Donnot
Live competition 2: The driving AI Olympics (Competition)
Panel discussion: Opportunities to organize new impactful challenges. (Discussion)
Jacob Abernethy