Codabench is a platform allowing you to flexibly specify a benchmark. First you define tasks, e.g. datasets and metrics of success, then you specify the API for submissions of code (algorithms), add some documentation pages, and [CLICK] your benchmark is created, ready to accept submissions of new algorithms. Participant results get appended to an ever-growing leaderboard.
You may also create inverted benchmarks in which the role of datasets and algorithms are swapped. You specify reference algorithms and your participants submit datasets.
CodaLab Competitions is a powerful open source framework for running competitions that
result or code submission. You can either participate in an existing competition or host
Most competitions hosted on Codalab are machine learning (data science)
competitions, but Codalab is NOT limited to this application domain. It can accommodate
problem for which a solution can be provided in the form of a zip archive containing a
files to be evaluated quantitatively by a scoring program (provided by the organizers).
scoring program must return a numeric score, which is displayed on a leaderboard where
performances of participants are compared.
Codalab was created in 2013 as a joint venture between Microsoft and Stanford University.
Originally the vision was to create an ecosystem for conducting computational research
in a more
efficient, reproducible, and collaborative manner, combining worksheets and
Worksheets capture complex research pipelines in a reproducible way and create
papers". Currently, we are developing the V2 of Codalab, which will be able to organize benchmarks.
Some competitions have been organized using worksheets, but the competition platform
and the worksheet platform have both a large user base and can be used independently. In
ChaLearn joined to co-develop
2015, University Paris-Saclay is
community lead of Codalab competitions, under the direction of Isabelle Guyon, professor
data. Codalab is administered by CKCollab and the LRI
Codalab is used actively in research. In
2019/2020, 400 new challenges were launched. Recent
popular challenges organized with Codalab include the
retweet prediction challenge, the ECCV
2020 ChaLearn LAP Fair face recognition challenge,
the 2020 DriveML
Huawei Autonomous Vehicle Challenge, and high
profile challenges include the 2
million Euro prize of the EU, organized by the See.4C
consortium, the CIKM
AnalytiCup 2017, which attracted 493 participants,
(633 participants) and the ChaLearn
AutoML challenge 2017 (687 participants).
Since 2016, Codalab offers the possibility of organizing machine learning challenges with
submission. The simplest machine learning challenges require only the submission of
which are compared to a solution (or key) by a scoring program. Result submission
less computationally expensive than code submission challenges. However, they offer less
possibilities. In particular, code submission allows conducting fair benchmarks by
submitted code in the same condition for all participants.
Codalab has been providing free resources for challenge organizers who want to run high
events, within a pre-approved agreed upon budget. New since version 1.5: organizers can
their own compute workers to the backend of Codalab to redirect the code submissions,
growth to big data competitions running at the expense of the organizers. For very
dedicated projects, Codalab can be customized since it is an open source project.
The LAL and CERN are organizing a challenge to reconstruct
particle trajectories in high energy physics detectors. After the success of the
first phase with result submission only, a second phase with code submission will be
run on Codalab. TrackML is an officially selected
challenge of the NIPS 2018 conference.
February 2018: 2 million Euro Big Data EU prize powered by Codalab.
February 2018: Isabelle Guyon presents Codalab at the newly formed Institute of
January 2018: Paris-Saclay master students create challenges for L2 students.
January 2018: Paris-Saclay instructors create reinforcement learning homework.
December 2017: Codalab exceeds 10000 users with 480 competitions (145 public)
December 2017: Codalab presented at the Challenges in Machine Learning workshop [slides].
Version 1.5 is out!
November 2017: Explore the new features: scale up your code submission
your own compute workers (full privacy, dockers); organize RL challenges and hook up
providing data on demand (with your own "ingestion program"); use the ChaLab wizard to
competitions in minutes.