5 papers
Metric space valued Fréchet regression
László Györfi, Pierre Humbert, Batiste Le Bars
We consider the problem of estimating the Fréchet and conditional Fréchet mean from data taking values in separable metric spaces. Unlike Euclidean spaces, where well-established m…
Online selective conformal inference: adaptive scores, convergence rates and optimality
Pierre Humbert, Ulysse Gazin, Ruth Heller +1
In a supervised online setting, quantifying uncertainty has been proposed in the seminal work of Gibbs and Candès (2021). For any given point-prediction algorithm, their method (AC…
On Volume Minimization in Conformal Regression
Batiste Le Bars, Pierre Humbert
We study the question of volume optimality in split conformal regression, a topic still poorly understood in comparison to coverage control. Using the fact that the calibration ste…
Transductive Conformal Inference for Full Ranking
Jean-Baptiste Fermanian, Pierre Humbert, Gilles Blanchard
We introduce a method based on Conformal Prediction (CP) to quantify the uncertainty of full ranking algorithms. We focus on a specific scenario where items are to be ranked…
Marginal and training-conditional guarantees in one-shot federated conformal prediction
Pierre Humbert, Batiste Le Bars, Aurélien Bellet +1
We study conformal prediction in the one-shot federated learning setting. The main goal is to compute marginally and training-conditionally valid prediction sets, at the server-lev…