Home | Events

27

Nov

Teaser image to The power of prediction

 

The power of prediction

Moritz Hardt, Max Planck Institute for Intelligent Systems, Tübingen

   27.11.2023

   4:15 pm - 5:45 pm

   LMU Department of Statistics and via zoom

Moritz Hardt explores performative prediction’s impact on human populations. Distinguishing between discovering patterns and steering populations, he introduces a power notion for digital platforms, examining their influence in markets. The talk concludes with collective algorithmic strategies against platform power.

Related

Link to Privacy, Data Privacy, and Differential Privacy

 

Colloquium  •  16.07.2024  •  LMU Department of Statistics and via zoom

Privacy, Data Privacy, and Differential Privacy

Colloquium at the LMU Department of Statistics with James Bailie from Harvard University.

Link to Variational Learning for Large Deep Networks

 

Colloquium  •  10.07.2024  •  LMU Department of Statistics and via zoom

Variational Learning for Large Deep Networks

Colloquium at the LMU Department of Statistics with Thomas Möllenhoff from RIKEN, Tokyo.

Link to Can today’s intention to treat have a causal effect on tomorrow’s hazard function?

 

Colloquium  •  03.07.2024  •  LMU Department of Statistics and via zoom

Can today’s intention to treat have a causal effect on tomorrow’s hazard function?

Colloquium at the LMU Department of Statistics with Jan Beyersmann, University of Ulm.

Link to The Complexities of Differential Privacy for Survey Data

 

Colloquium  •  26.06.2024  •  LMU Department of Statistics and via zoom

The Complexities of Differential Privacy for Survey Data

Link to Resampling-based inference for the average treatment effect in observational studies with competing risks

 

Colloquium  •  19.06.2024  •  LMU Department of Statistics and via zoom

Resampling-based inference for the average treatment effect in observational studies with competing risks

This talk explores three resampling methods to construct valid confidence intervals and bands for treatment effect estimation in competing risks studies.