30 citations · 87 across the 5 of their papers we have counts for
4 papers · 1 filter
Noisy Adaptive Group Testing using Bayesian Sequential Experimental Design
Marco Cuturi, Olivier Teboul, Quentin Berthet +2
When the infection prevalence of a disease is low, Dorfman showed 80 years ago that testing groups of people can prove more efficient than testing people individually. Our goal in…
Fast Differentiable Sorting and Ranking
Mathieu Blondel, Olivier Teboul, Quentin Berthet +1
The sorting operation is one of the most commonly used building blocks in computer programming. In machine learning, it is often used for robust statistics. However, seen as a func…
Learning with Differentiable Perturbed Optimizers
Quentin Berthet, Mathieu Blondel, Olivier Teboul +3
Machine learning pipelines often rely on optimization procedures to make discrete decisions (e.g., sorting, picking closest neighbors, or shortest paths). Although these discrete d…
Supervised Quantile Normalization for Low-rank Matrix Approximation
Marco Cuturi, Olivier Teboul, Jonathan Niles-Weed +1
Low rank matrix factorization is a fundamental building block in machine learning, used for instance to summarize gene expression profile data or word-document counts. To be robust…