The field of ML has seen massive growth and it is becoming apparent it may be in need of self-reflection to ensure that efforts are directed towards real progress. To this end, we are organizing an workshop on "ML Evaluation Standards". ml-eval.github.io [1/N]
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We have a great list of invited speakers presenting a variety of perspectives on the topic of ML evaluation. [2/N]
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Acknowledging that there is no consensus on best
evaluation practices for ML, the workshop would also have 3 panel discussions. The 1st panel discussion would be about "Incentives for Better Evaluation", featuring researchers who have seen the field of ML explode. [3/N]
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The 3rd panel would be about the infamous "Slow vs Fast Science" question featuring researchers from ML (, ), Psychology (), Sociology () and Physics ().
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Call for Papers: You can submit your papers at cmt3.research.microsoft.com/SMILES2022 (Deadline: March 4). We invite two types of papers – opinion papers, and methodology papers about evaluation in ML on various topics, including:
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It's excited to organize this workshop alongside great people, who are cooler than these cats :)
See you at the virtual ICLR workshop in April!
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New workshop track with $15k in awards: "Improvement to the Conference and Publication Process". Details:
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Excitingly, the ML Evaluation Standards workshop @iclr_conf will be collaborating with @SchmidtFutures to grant $15k in awards for workshop submissions and reviewers!
ml-eval.github.io
More info below 
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