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Fairness and Randomness in Machine Learning: Statistical Independence and Relativization

Publication: Journal Article

Derr, Rabanus, and Robert C Williamson. 2024. “Fairness and Randomness in Machine Learning: Statistical Independence and Relativization”. The New England Journal of Statistics in Data Science.

The Geometry and Calculus of Losses

Publication: Journal Article

Williamson, Robert C, and Zac Cranko. 2023. “The Geometry and Calculus of Losses”. Journal of Machine Learning Research 24 (342): 1-72.

Bob Williamson

Person:

Professor of Foundations of Machine Learning Systems

Contact

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Maria-von-Linden Strasse 6 Tübingen, 72076 Germany email

Information Processing Equalities

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machine learning processes information, but what do we mean by 'information"? One view comes from Information Theory, which was originally developed motivated by problems of communication. But learning problems are different, aren't they? This project explores the notion of information that makes...

Photography

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Armando Cabrera Pacheco

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I am a mathematician with research experience in differential geometry, geometric analysis, and mathematical relativity. The main goal of my current research is to better understand several key objects in machine learning from a rigorous mathematical point of view. I am convinced that analyzing...

Contacts and links

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Feel free to contact me at University of Tübingen Department of Computer Science Maria von Linden Str. 6 72076 Tübingen Germany laura [dot] iacovissi [at] uni-tuebingen [dot] de or check out my profiles: Google Scholar Github LinkedIn

Laura Iacovissi

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Welcome to my webpage! Since November 2021, I have been a PhD student at the Foundations of Machine Learning group. Previously, I worked as a research intern at the Max Planck Institute for Intelligent Systems with Dr. Caterina De Bacco, applying statistical physics to network science problems. I...