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Call for Abstracts
The plenary session is looking for contributed abstracts that have a single author or two authors where the principal author is a student and a second author is their current PhD supervisor playing a supporting role.
The submissions will be reviewed with the author names available to the reviewer.
We accept abstracts on any area of algorithmic decision making and machine learning. Spreading from social impacts, policy implications, applications, new to technical contributions such as theory or new algorithms.
At submission stage we ask you not to make use of large language models or other generative AI for producing the abstract's text. We'd like to hear directly from you in your voice, expressing your ideas in the clearest way that you know how. Later if your abstract is accepted and you wish to improve presentation for final proof, then we can think about how best to do that.Abstracts must not exceed 500 words. Successful submissions will be selected to present at the plenary. Furthermore, those with successful submissions will be allowed to submit their work as a paper for publication to the Proceedings of Machine Learning Research (PMLR) after the meeting date.
Review Process
Successful submissions will be selected to give a talk at the plenary or to participate in a poster session depending on the number of submissions.
There will be multiple disciplines at the conference, so abstracts should be written in such a way that invites the interest of other disciplines. Naturally not all disciplinary boundaries can be crossed, but we encourage the relationship between different areas of interest to be highlighted. We hope the event will deepen understanding across domains.