40 citations · 88 across the 7 of their papers we have counts for
8 papers
Estimation via length-constrained generalized empirical principal curves under small noise
Sylvain Delattre, Aurélie Fischer
In this paper, we propose a method to build a sequence of generalized empirical principal curves, with selected length, so that, in Hausdor distance, the images of the estimating p…
Robust Bregman Clustering
Aurélie Fischer, Clément Levrard, Claire Brécheteau
Using a trimming approach, we investigate a k-means type method based on Bregman divergences for clustering data possibly corrupted with clutter noise. The main interest of Bregman…
Aggregation using input-output trade-off
Aurélie Fischer, Mathilde Mougeot
In this paper, we introduce a new learning strategy based on a seminal idea of Mojirsheibani (1999, 2000, 2002a, 2002b), who proposed a smart method for combining several classifie…
Convergence rates for smooth k-means change-point detection
Aurélie Fischer, Dominique Picard
In this paper, we consider the estimation of a change-point for possibly high-dimensional data in a Gaussian model, using a k-means method. We prove that, up to a logarithmic term,…
On principal curves with a length constraint
Sylvain Delattre, Aurélie Fischer
Principal curves are defined as parametric curves passing through the "middle" of a probability distribution in R^d. In addition to the original definition based on self-consistenc…
Statistical learning for wind power : a modeling and stability study towards forecasting
Aurélie Fischer, Lucie Montuelle, Mathilde Mougeot +1
We focus on wind power modeling using machine learning techniques. We show on real data provided by the wind energy company Ma{ï}a Eolis, that parametric models, even following clo…
Improved rates for Wasserstein deconvolution with ordinary smooth error in dimension one
Jérôme Dedecker, Aurélie Fischer, Bertrand Michel
This paper deals with the estimation of a probability measure on the real line from data observed with an additive noise. We are interested in rates of convergence for the Wasserst…
COBRA: A Combined Regression Strategy
Gérard Biau, Aurélie Fischer, Benjamin Guedj +1
A new method for combining several initial estimators of the regression function is introduced. Instead of building a linear or convex optimized combination over a collection of ba…