← Authors

Robert C. Williamson

30 papers · 2001–2025 · 3 conferences · across top CS/AI conferences

Achievements

🐝 Cross-Pollinator (9) πŸƒ Academic Marathon (24) 🌍 Conference Polyglot (3) 🐣 Hot Topic Early Bird πŸ—ΊοΈ Taxonomy Completionist (16) πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer 🌟 Keyword Trendsetter Combo (5) πŸ”¬ Deep Specialist (12) 🌱 Topic Pioneer πŸ† Keyword Champion (3) πŸ’Ž Century Club (30) πŸ”₯ Unstoppable (7) πŸ—ƒοΈ Keyword Collector (62) πŸ“ˆ Trend Setter πŸš€ Conference Pioneer

Conferences

JMLR (16) NIPS (8) COLT (6)

Top co-authors

Mark D. Reid (9) Zac Cranko (3) Brendan van Rooyen (2) Alexander J. Smola (2) Aditya Krishna Menon (2) Tim van Erven (2) Zakaria Mhammedi (2) Richard Nock (2) Elodie Vernet (2) Lizhen Qu (1)

Research topics

Statistics (1)

Keywords

proper loss (9) multiclass classification (5) online learning (4) loss function (4) bayes risk (4) stochastic mixability (3) binary classification (3) classification calibration (3) multiclass loss (3) generalization bound (2) bipartite ranking (2) support vector machine (2) regret bound (2) learning rate (2) learning theory (2) mirror descent (2) log loss (2) risk minimization (2) variational inference (2) supervised learning (2)

Papers

Geometry and Stability of Supervised Learning Problems JMLR 2025
Risk Measures and Upper Probabilities: Coherence and Stratification JMLR 2024
Information Processing Equalities and the Information–Risk Bridge JMLR 2024
The Geometry and Calculus of Losses JMLR 2023
PAC-Bayesian Bound for the Conditional Value at Risk NIPS 2020
A Primal-Dual link between GANs and Autoencoders NIPS 2019
Constant Regret, Generalized Mixability, and Mirror Descent NIPS 2018
A Theory of Learning with Corrupted Labels JMLR 2018
f-GANs in an Information Geometric Nutshell NIPS 2017
Composite Multiclass Losses JMLR 2016
Bipartite Ranking: a Risk-Theoretic Perspective JMLR 2016
Generalized Mixability via Entropic Duality COLT 2015
Fast Rates in Statistical and Online Learning JMLR 2015
Learning with Symmetric Label Noise: The Importance of Being Unhinged NIPS 2015
From Stochastic Mixability to Fast Rates NIPS 2014
Bayes-Optimal Scorers for Bipartite Ranking COLT 2014
On the Consistency of Output Code Based Learning Algorithms for Multiclass Learning Problems COLT 2014
The Geometry of Losses COLT 2014
Divergences and Risks for Multiclass Experiments COLT 2012
Mixability in Statistical Learning NIPS 2012
Mixability is Bayes Risk Curvature Relative to Log Loss JMLR 2012
Composite Multiclass Losses NIPS 2011
Mixability is Bayes Risk Curvature Relative to Log Loss COLT 2011
Information, Divergence and Risk for Binary Experiments JMLR 2011
Composite Binary Losses JMLR 2010
Learning the Kernel with Hyperkernels JMLR 2005
Algorithmic Luckiness JMLR 2002
Introduction to the Special Issue on Kernel Methods JMLR 2001
Prior Knowledge and Preferential Structures in Gradient Descent Learning Algorithms JMLR 2001
Regularized Principal Manifolds JMLR 2001