Robert C. Williamson
30 papers · 2001–2025 · 3 conferences · across top CS/AI conferences
Achievements
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π£ Hot Topic Early Bird π Interdisciplinary Bridge π§ Keyword Pioneer πΊοΈ Taxonomy Completionist (16) π Conference Polyglot (3)
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Interdisciplinary Bridge
π§
Keyword Pioneer
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Keyword Trendsetter Combo
(5)
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Deep Specialist
(12)
π±
Topic Pioneer
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Keyword Champion
(3)
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Century Club
(30)
π₯
Unstoppable
(7)
ποΈ
Keyword Collector
(62)
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Trend Setter
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Conference Pioneer
Conferences
JMLR (16)
NIPS (8)
COLT (6)
Top co-authors
Research topics
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 InformationβRisk 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