Williamson, Robert

8 publications

TMLR 2025 Aggregating Algorithm and Axiomatic Loss Aggregation Armando J Cabrera Pacheco, Rabanus Derr, Robert Williamson

ICML 2023 Random Classification Noise Does Not Defeat All Convex Potential Boosters Irrespective of Model Choice Yishay Mansour, Richard Nock, Robert Williamson

TMLR 2023 Tailoring to the Tails: Risk Measures for Fine-Grained Tail Sensitivity Christian Fröhlich, Robert Williamson

TMLR 2023 The Geometry of Mixability Armando J Cabrera Pacheco, Robert Williamson

ICML 2019 Fairness Risk Measures Robert Williamson, Aditya Menon

ICML 2019 Lossless or Quantized Boosting with Integer Arithmetic Richard Nock, Robert Williamson

AISTATS 2010 Convexity of Proper Composite Binary Losses Mark Reid, Robert Williamson

JMLR 2007 The Need for Open Source Software in Machine Learning Sören Sonnenburg, Mikio L. Braun, Cheng Soon Ong, Samy Bengio, Leon Bottou, Geoffrey Holmes, Yann LeCun, Klaus-Robert Müller, Fernando Pereira, Carl Edward Rasmussen, Gunnar Rätsch, Bernhard Schölkopf, Alexander Smola, Pascal Vincent, Jason Weston, Robert Williamson