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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 basic estimators $r_1,...
We introduce the notion of anisotropic long memory for random fields on $\mathbb{Z}^2$ whose partial sums on incommensurate rectangles with sides growing at different rates O(n) and $O(n^{H_1/H_2})$, ...
Considernindividuals who, by popular vote, choose among q≥2 alternatives, one of which is “better” than the others. Assume that each individual votes independently at random, and that the probability ...
This note constitutes a corrigendum to the article of Azomahou, JSPI, 139:2581-2597.
We consider a binary unsupervised classi cation problem where each observation is associated with an unobserved label that we want to retrieve. More precisely, we assume that there are two groups of...
We consider the problem of regression learning for deterministic design and independent random errors.We start by proving a sharp PAC-Bayesian type bound for the exponentially weighted aggregate (EWA)...
We want to recover the regression function in the single-index model. Using an aggregation algorithm with local polynomial estimators, we answer in particular to the second part of Question 2 from Sto...
The stochastic growth model Internal Diffusion Limited Aggregation was defined in 1991 by Diaconis and Fulton. Several shape results are known when the underlying state space is the d-dimensional latt...
Aggregation functions are generally defined and used to combine several numerical values into a single one, so that the final result of the aggregation takes into account all the individual values i...
We develop minimax optimal risk bounds for the general learning task consisting in predicting as well as the best function in a reference set G up to the smallest possible additive term, called the ...
We want to recover the regression function in the single-index model. Using an aggregation algorithm with local polynomial estimators, we answer in particular to the second part of Question 2 from S...
The paper studies the aggregation/disaggregation problem of random parameter AR(1) processes and its relation to the long memory phenomenon. We give a characterization of a subclass of aggregated p...
An aggregated method of nonparametric estimators based on time-domain and statedomain estimators is proposed and studied. To attenuate the curse of dimensionality, we propose a factor modeling strat...

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