AIAI Seminar-06 June-Talk by Mattia Cerrato (Institute of Computer Science)
Title: 10 Years of Fair Representations
Abstract: Research on algorithmic fairness has focused Fair Representation Learning (FRL) is a broad set of techniques, mostly based on neural networks, that seeks to learn new representations of data in which sensitive or undesired information has been removed. In this talk, I will offer a look back at the first ten years of FRL and its applications. Then, I will present a theoretical impossibility result for FRL with deterministic neural networks and the results of a massive experimentation we performed (around 300k model fits) supporting this result.
Jun 06 2024
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AIAI Seminar-06 June-Talk by Mattia Cerrato (Institute of Computer Science)
AIAI Seminar hosted by Mattia Cerrato (Institute of Computer Science)
Informatics Forum, G.03