Scholar
Robert C. Williamson
Google Scholar ID: G4MBruQAAAAJ
University of Tübingen
machine learning
learning theory
imprecise probability
risk measures
Follow
Homepage
↗
Google Scholar
↗
Citations & Impact
All-time
Citations
12,202
H-index
31
i10-index
66
Publications
20
Co-authors
74
list available
Publications
8 items
Law of Large Numbers: Accuracy as Statistical Measure for AI Compliance and Competition
2026
Cited
0
Comparing Corrupted Constrained Learning Problems
2026
Cited
0
The Rhetoric of Machine Learning
2026
Cited
0
Three Types of Calibration with Properties and their Semantic and Formal Relationships
2025
Cited
0
Which distribution were you sampled from? Towards a more tangible conception of data
2024
Cited
1
Causal modelling without introducing counterfactuals or abstract distributions
2024
Cited
0
Geometry and Stability of Supervised Learning Problems
arXiv.org · 2024
Cited
0
Four Facets of Forecast Felicity: Calibration, Predictiveness, Randomness and Regret
arXiv.org · 2024
Cited
2
Co-authors
14 total
Alex Smola
Boson AI
Bernhard Schölkopf
Director, Max Planck Institute for Intelligent Systems & ELLIS Institute Tübingen; Professor at ETH
John Shawe-Taylor
UCL
Peter Bartlett
Professor, EECS and Statistics, UC Berkeley
John C. Platt
Google
Aditya Krishna Menon
Research Scientist, Google
Cheng Soon Ong
Data61, CSIRO, Canberra
Ralf Herbrich
Hasso Plattner Institute
