3 papers
stat.ML2024
Building Conformal Prediction Intervals with Approximate Message Passing
Lucas Clarté, Lenka Zdeborová
Conformal prediction has emerged as a powerful tool for building prediction intervals that are valid in a distribution-free way. However, its evaluation may be computationally cost…
stat.ML2024
Analysis of Bootstrap and Subsampling in High-dimensional Regularized Regression
Lucas Clarté, Adrien Vandenbroucque, Guillaume Dalle +3
We investigate popular resampling methods for estimating the uncertainty of statistical models, such as subsampling, bootstrap and the jackknife, and their performance in high-dime…
cs.LG2023
Expectation consistency for calibration of neural networks
Lucas Clarté, Bruno Loureiro, Florent Krzakala +1
Despite their incredible performance, it is well reported that deep neural networks tend to be overoptimistic about their prediction confidence. Finding effective and efficient cal…