Search | Foundations of Machine Learning Systems

Search results

67 results found

Slow Science

News: April 16, 2024

Machine learning research is notoriously fast paced. Can one get off the treadmill and embrace a notion of slow science ? I am pleased to be able to argue yes by example! Recently I have had two works published with a very long gestation. The first Geometry and Calculus of Losses reports work that...

Rabanus Derr

Page

Hello, I'm Rabanus. Since October 2021 I am pursuing my PhD under supervision of Bob Williamson in the group "Foundations of Machine Learning Systems". I am working on the implication of probability theoretical assumptions on ethical considerations in machine learning. As part of this endeavour I'm...

Corruptions of Supervised Learning Problems: Typology and Mitigations

Publication: Journal Article

Iacovissi, Laura, Nan Lu, and Robert C. Williamson. 2024. “Corruptions of Supervised Learning Problems: Typology and Mitigations”. ArXiv.

Risk Measures and Upper Probabilities: Coherence and Stratification

Publication: Journal Article

Fröhlich, Christian, and Robert C Williamson. Forthcoming. “Risk Measures and Upper Probabilities: Coherence and Stratification”. Journal of Machine Learning Research, Forthcoming.

Insights From Insurance for Fair Machine Learning: Responsibility, Performativity and Aggregates

Publication: Journal Article

Fröhlich, Christian, and Robert C. Williamson. 2023. “Insights From Insurance for Fair Machine Learning: Responsibility, Performativity and Aggregates”. ArXiv.

Four Facets of Forecast Felicity: Calibration, Predictiveness, Randomness and Regret

Publication: Manuscript

Derr, Rabanus, and Robert C. Williamson. 2024. “Four Facets of Forecast Felicity: Calibration, Predictiveness, Randomness and Regret.”

About

Page

We are based in Tübingen, near the Schönbuch forest (all the photographs on the site are of the environs of Tübingen).

Team

Page

Research (old)

Page

News

Page