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Given an $n$-sample of random vectors $(X_i,Y_i)_{1 \leq i \leq n}$ whose joint law is unknown, the long-standing problem of supervised classification aims to \textit{optimally} predict the label $Y$… (More)

The aim of this paper is to establish non-asymptotic minimax rates of testing for goodness-of-fit hypotheses in a heteroscedastic setting. More precisely, we deal with sequences $(Y_j)_{j\in J}$ of… (More)

- Cl'ement Marteau
- 2007

In this paper, we study statistical inverse problems. We are interested in the case where the operator is not exactly known. Using the penalized blockwise Stein’s rule, we construct an estimator that… (More)

This paper considers the problem of adaptive estimation of a non-homogeneous intensity function from the observation of n independent Poisson processes having a common intensity that is randomly… (More)

This paper is devoted to multidimensional inverse problems. In this setting, we address the goodness-of-fit testing problem. We investigate the separation rates associated with different kinds of… (More)

The effect of measurement errors in discriminant analysis is investigated. Given observations $Z=X+\epsilon$, where $\epsilon$ denotes a random noise, the goal is to predict the density of $X$ among… (More)

We tackle the problem of estimating a regression function observed in an instrumental regression framework. This model is an inverse problem with unknown operator. We provide a spectral cut-off… (More)

In this paper, we consider a parametric density contamination model. We work with a sample of i.i.d. data with a common density, f? = (1− λ?)φ+ λ?φ(.− μ?), where the shape φ is assumed to be known.… (More)

This paper extends the successful maxiset paradigm from function estimation to signal detection in inverse problems. In this context, the maxisets do not have the same shape compared to the classical… (More)

This paper considers the problem of adaptive estimation of a template in a randomly shifted curve model. Using the Fourier transform of the data, we show that this problem can be transformed into a… (More)