12

Jun

Teaser image to Generalized Data Thinning Using Sufficient Statistics

Colloquium

Generalized Data Thinning Using Sufficient Statistics

Jacob Bien, University of Southern California, LA

   12.06.2023

   3:00 pm - 4:30 pm

   LMU 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.


Related

Link to tba

AI Keynote Series  •  20.03.2025  •  Online via Zoom

tba

Join the lecture with Alejandro Schuler from UC Berkeley.


Link to tba

AI Keynote Series  •  13.02.2025  •  Online via Zoom

tba

Join the lecture with Alex Luedtke from the University of Washington.


Link to TBA

Colloquium  •  05.02.2025  •  LMU Department of Statistics and via zoom

TBA

Colloquium at the LMU Department of Statistics with Isabel Valera (Saarland University in Saarbrücken).


Link to TBA

Colloquium  •  29.01.2025  •  LMU Department of Statistics and via zoom

TBA

Colloquium at the LMU Department of Statistics with Sophie Langer (University of Twente).


Link to TBA

Colloquium  •  15.01.2025  •  LMU Department of Statistics and via zoom

TBA

Colloquium at the LMU Department of Statistics with Sonja Greven (HU Berlin).