Brendan Van Rooyen — accepted AI-conference papers

2015

Learning from Corrupted Binary Labels via Class-Probability Estimation

Aditya Menon, Brendan Van Rooyen, Cheng Soon Ong, Bob Williamson

ICML 2015poster

Many supervised learning problems involve learning from samples whose labels are corrupted in some way. For example, each sample may have some constant probability of being incorrectly labelled (learning with label noise), or one may have a pool of unlabelled samples in lieu of negative samples (lea…

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2015

Learning with Symmetric Label Noise: The Importance of Being Unhinged

Brendan van Rooyen, Aditya Menon, Robert C. Williamson

NeurIPS 2015spotlight

Convex potential minimisation is the de facto approach to binary classification. However, Long and Servedio [2008] proved that under symmetric label noise (SLN), minimisation of any convex potential over a linear function class can result in classification performance equivalent to random guessing.…

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