Time: 11.00 to 12.00
Location: Garda room, Via Sommarive 5 - Polo Ferrari 1 (Povo, TN)
Prof. Ya’acov Ritov, University of Michigan
We identify conditional parity as a general notion of nondiscrimination in machine learning. In fact, several recently proposed notions of non-discrimination, including a few counterfactual notions, are instances of conditional parity. We show that conditional parity is amenable to statistical analysis by studying randomization as a general mechanism for achieving conditional parity and a kernel-based test of conditional parity.
About the Speaker
Ya'acov Ritov has B.Sc. and M.Sc in Electrical Engineering from the Technion and PhD in statistics from the Hebrew University, where he was in the department of statistics until 2015. He is currently a professor of statistics at the University of Michigan
Contact Person Regarding this Talk: andrea.passerini [at] unitn.it (Andrea Passerini )