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Workshop

MLRetrospectives: A Venue for Self-Reflection in ML Research

Jessica Forde · Jesse Dodge · Mayoore Jaiswal · Rosanne Liu · Ryan Lowe · Rosanne Liu · Joelle Pineau · Yoshua Bengio

Keywords:  science of machine learning    community    critique  

The ICML Workshop on Retrospectives in Machine Learning will build upon the success of the 2019 NeurIPS Retrospectives workshop to further encourage the publication of retrospectives. A retrospective of a paper or a set of papers, by its author, takes the form of an informal paper. It provides a venue for authors to reflect on their previous publications, to talk about how their thoughts have changed following publication, to identify shortcomings in their analysis or results, and to discuss resulting extensions. The overarching goal of MLRetrospectives is to improve the science, openness, and accessibility of the machine learning field, by widening what is publishable and helping to identify opportunities for improvement. Retrospectives also give researchers and practitioners unable to attend conferences access to the author’s updated understanding of their work, which would otherwise only be accessible to their immediate circle. The machine learning community would benefit from retrospectives on much of the research which shapes our field, and this workshop will present an opportunity for a few retrospectives to be presented.

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Timezone: America/Los_Angeles

Schedule