118 citations · 229 across the 23 of their papers we have counts for
3 papers · 2 filters
Pi-DUAL: Using Privileged Information to Distinguish Clean from Noisy Labels
Ke Wang, Guillermo Ortiz-Jimenez, Rodolphe Jenatton +3
Label noise is a pervasive problem in deep learning that often compromises the generalization performance of trained models. Recently, leveraging privileged information (PI) -- inf…
When does Privileged Information Explain Away Label Noise?
Guillermo Ortiz-Jimenez, Mark Collier, Anant Nawalgaria +4
Leveraging privileged information (PI), or features available during training but not at test time, has recently been shown to be an effective method for addressing label noise. Ho…
Massively Scaling Heteroscedastic Classifiers
Mark Collier, Rodolphe Jenatton, Basil Mustafa +3
Heteroscedastic classifiers, which learn a multivariate Gaussian distribution over prediction logits, have been shown to perform well on image classification problems with hundreds…