Generalized Data Thinning Using Sufficient Statistics

Jacob Bien, University of Southern California, LA

12.06.2023

3:00 pm - 4:30 pm

LMU Munich, Department of Statistics and via zoom

Sample splitting, a common tool in data science, faces limitations. A recent method, convolution-closed data thinning, offers an alternative when sample splitting isn’t feasible. This talk explores sufficiency as a key principle, leading to a unified framework called generalized data thinning.

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Generalized Data Thinning Using Sufficient Statistics

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