Vision & Mission
ICBINB’s vision is to create and foster a community that goes beyond benchmark climbing and new algorithms
with bold numbers. In the long-term, we want to influence and be an example for other venues on the promotion of
good science in machine learning; science that is collaborative and advances the understanding, the elegance,
and the diversity of the field rather than just rewarding science that proves to be better
than previous work on a given benchmark.
The desired outcome is to create a ML sub-community with a much more diverse set of values, highlighting
the importance of unexpected negative results, questioning well-established default practices, re-evaluating
and understanding existing methods; defining entirely new problems, or challenging formulations of existing
problems; rewarding simplicity over unnecessary complexity.
How to get there?
ICBINB organizes activities that provide a space for beautiful ideas that advance the understanding of the ML
field even when those ideas did not result in a new leaderboard on the latest benchmark. Furthermore,
ICBINB takes actions to create a supportive community that can help junior scientists, or simply help ideas that
are stuck, to emerge and flourish.
ICBINB organizes workshops to allow researchers to showcase their works whose characteristics fit under the values expressed
by the initiative, as they would likely be undervalued in existing venues. ICBINB also organizes seminar series, where speakers
will normally discuss projects that fit into the description of undervalued works, as per ICBINB’s values.
In the future, ICBINB will expand and diversify its activities, to cover more aspects of the long-term vision and
further spread values to the broader ML community. This includes: local events at the organizers’ host institutions;
mentoring activities, such as an “adopt a paper” initiative; a special issue in an existing journal;
an entirely brand-new journal, focused on works currently undervalued as per ICBINB’s values; a repository
for dissemination and tracking of valuable negative results in machine learning, a podcast and/or blog,
for researchers and ICBINB’s organizers to share their stories of works which do not fit the “bold numbers” paradigm.
In the longer-term…
Here a list of events/activities that we would like to promote moving forward. If any of these resonate with you and you would like to help us make it a reality, please reach out!
- A monthly seminar series for sharing stories from or about research
- A journal special issue for
“beautiful ideas without bold numbers” - A matchmaking platform: supportive reviewing process to help papers reach the final line
- A blog for sharing stories from or about research, unexpected negative results that would otherwise be forgotten
- ... and much more! Stay tuned 🙂