1.4k citations · 2.1k across the 21 of their papers we have counts for
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When can unlabeled data improve the learning rate?
Christina Göpfert, Shai Ben-David, Olivier Bousquet +3
In semi-supervised classification, one is given access both to labeled and unlabeled data. As unlabeled data is typically cheaper to acquire than labeled data, this setup becomes a…
Practical and Consistent Estimation of f-Divergences
Paul K. Rubenstein, Olivier Bousquet, Josip Djolonga +2
The estimation of an f-divergence between two probability distributions based on samples is a fundamental problem in statistics and machine learning. Most works study this problem…
GeNet: Deep Representations for Metagenomics
Mateo Rojas-Carulla, Ilya Tolstikhin, Guillermo Luque +3
We introduce GeNet, a method for shotgun metagenomic classification from raw DNA sequences that exploits the known hierarchical structure between labels for training. We provide a…