Spin Needlets for Cosmic Microwave Background Polarization Data Analysis (2008)
Geller, Daryl, Hansen, Frode K., Marinucci, Domenico, Kerkyacharian, Gerard, Picard, Dominique
Scalar wavelets have been used extensively in the analysis of Cosmic Microwave Background (CMB) temperature maps. Spin needlets are a new form of (spin) wavelets which were introduced in the...
Inversion of noisy Radon transform by SVD based needlet (2008)
Kerkyacharian, Gérard, Kyriazis, George, Le Pennec, Erwan, Petrushev, Pencho, Picard, Dominique
A linear method for inverting noisy observations of the Radon transform is developed based on decomposition systems (needlets) with rapidly decaying elements induced by the Radon transform SVD basis....
Inversion of noisy Radon transform by SVD based needlet (2008)
Kerkyacharian, Gérard, Kyriazis, George, Le Pennec, Erwan, Petrushev, Pencho, Picard, Dominique
A linear method for inverting noisy observations of the Radon transform is developed based on decomposition systems (needlets) with rapidly decaying elements induced by the Radon transform SVD basis....
Inversion of noisy Radon transform by SVD based needlet (2008)
Kerkyacharian, Gérard, Kyriazis, George, Pennec, Erwan Le, Petrushev, Pencho, Picard, Dominique
A linear method for inverting noisy observations of the Radon transform is developed based on decomposition systems (needlets) with rapidly decaying elements induced by the Radon transform SVD basis....
Subsampling Needlet Coefficients on the Sphere (2007)
Baldi, Paolo, Kerkyacharian, Gerard, Marinucci, Domenico, Picard, Dominique
In a recent paper, we analyzed the properties of a new kind of spherical wavelets (so-called needlets) for statistical inference procedures on spherical random fields; the results were mainly...
Needlet algorithms for estimation in inverse problems (2007)
Kerkyacharian, Gérard, Petrushev, Pencho, Picard, Dominique, Willer, Thomas
We provide a new algorithm for the treatment of inverse problems which combines the traditional SVD inversion with an appropriate thresholding technique in a well chosen new basis. Our goal is to...
NEED-VD: a second-generation wavelet algorithm for estimation in inverse problems (2006)
Kerkyacharian, Gérard, Petrushev, Pencho, Picard, Dominique, Willer, Thomas
We provide a new algorithm for the treatment of inverse problems which combines the traditional SVD inversion with an appropriate thresholding technique in a well chosen new basis. Our goal is to...
NEED-VD: a second-generation wavelet algorithm for estimation in inverse problems (2006)
Kerkyacharian, Gérard, Petrushev, Pencho, Picard, Dominique, Willer, Thomas
We provide a new algorithm for the treatment of inverse problems which combines the traditional SVD inversion with an appropriate thresholding technique in a well chosen new basis. Our goal is to...
NEED-VD: a second-generation wavelet algorithm for estimation in inverse problems (2006)
Kerkyacharian, Gérard, Petrushev, Pencho, Picard, Dominique, Willer, Thomas
We provide a new algorithm for the treatment of inverse problems which combines the traditional SVD inversion with an appropriate thresholding technique in a well chosen new basis. Our goal is to...
NEED-VD: a second-generation wavelet algorithm for estimation in inverse problems (2006)
Kerkyacharian, Gérard, Petrushev, Pencho, Picard, Dominique, Willer, Thomas
We provide a new algorithm for the treatment of inverse problems which combines the traditional SVD inversion with an appropriate thresholding technique in a well chosen new basis. Our goal is to...
High Frequency Asymptotics for Wavelet-Based Tests for Gaussianity and Isotropy on the Torus (2006)
Baldi, Paolo, Kerkyacharian, Gérard, Marinucci, Domenico, Picard, Dominique
We prove a CLT for skewness and kurtosis of the wavelets coefficients of a stationary field on the torus. The results are in the framework of the fixed-domain asymptotics, i.e. we refer to...
High Frequency Asymptotics for Wavelet-Based Tests for Gaussianity and Isotropy on the Torus (2006)
Baldi, Paolo, Kerkyacharian, Gérard, Marinucci, Domenico, Picard, Dominique
We prove a CLT for skewness and kurtosis of the wavelets coefficients of a stationary field on the torus. The results are in the framework of the fixed-domain asymptotics, i.e. we refer to...
Bodet, Catherine; Catherine Bodet , économiste, Est Analyste De La Responsabilité Sociale Et Environnementale Des Entreprises, Analyste Bilan Sociétal, Et Chargée De Projet « Bilan Sociétal », Picard, Dominique
Le Bilan Sociétal© est dans le même temps un instrument d'évaluation de la responsabilité des entreprises en terme social et environnemental et une démarche de progrès en ce sens. Une de ses...
High Frequency Asymptotics for Wavelet-Based Tests for Gaussianity and Isotropy on the Torus (2006)
Baldi, Paolo, Kerkyacharian, Gérard, Marinucci, Domenico, Picard, Dominique
We prove a CLT for skewness and kurtosis of the wavelets coefficients of a stationary field on the torus. The results are in the framework of the fixed-domain asymptotics, i.e. we refer to...
High Frequency Asymptotics for Wavelet-Based Tests for Gaussianity and Isotropy on the Torus (2006)
Baldi, Paolo, Kerkyacharian, Gérard, Marinucci, Domenico, Picard, Dominique
We prove a CLT for skewness and kurtosis of the wavelets coefficients of a stationary field on the torus. The results are in the framework of the fixed-domain asymptotics, i.e. we refer to...
Thresholding in Learning Theory (2005)
Kerkyacharian, Gerard, Picard, Dominique
In this paper we investigate the problem of learning an unknown bounded function. We be emphasize special cases where it is possible to provide very simple (in terms of computation) estimates...
Thresholding in Learning Theory (2005)
Kerkyacharian, Gerard, Picard, Dominique
In this paper we investigate the problem of learning an unknown bounded function. We be emphasize special cases where it is possible to provide very simple (in terms of computation) estimates...
Thresholding in Learning Theory (2005)
Kerkyacharian, Gerard, Picard, Dominique
In this paper we investigate the problem of learning an unknown bounded function. We be emphasize special cases where it is possible to provide very simple (in terms of computation) estimates...
Thresholding in Learning Theory (2005)
Kerkyacharian, Gerard, Picard, Dominique
In this paper we investigate the problem of learning an unknown bounded function. We be emphasize special cases where it is possible to provide very simple (in terms of computation) estimates...
Thresholding in Learning Theory (2005)
Kerkyacharian, Gerard, Picard, Dominique
In this paper we investigate the problem of learning an unknown bounded function. We be emphasize special cases where it is possible to provide very simple (in terms of computation) estimates...
Regression in random design and warped wavelets (2004)
Kerkyacharian, Gérard, Picard, Dominique
We consider the problem of estimating an unknown function f in a regression setting with random design. Instead of expanding the function on a regular wavelet basis, we expand it on the basis...
Adaptive boxcar deconvolution on full Lebesgue measure sets (2004)
Kerkyacharian, Gérard, Picard, Dominique, Raimondo, Marc
We consider the nonparametric estimation of a function that is observed in white noise after convolution with a boxcar, the indicator of an interval $(-a,a)$. In a recent paper \citet{jkpr04} have...
Autin, Florent, Picard, Dominique, Rivoirard, Vincent
In this paper our aim is to provide tools for easily calculating the maxisets of several procedures. Then we apply these results to perform a comparison between several Bayesian estimators in a non...
Adaptive boxcar deconvolution on full Lebesgue measure sets (2004)
Kerkyacharian, Gérard, Picard, Dominique, Raimondo, Marc
We consider the nonparametric estimation of a function that is observed in white noise after convolution with a boxcar, the indicator of an interval $(-a,a)$. In a recent paper \citet{jkpr04} have...
Autin, Florent, Picard, Dominique, Rivoirard, Vincent
In this paper our aim is to provide tools for easily calculating the maxisets of several procedures. Then we apply these results to perform a comparison between several Bayesian estimators in a non...
Adaptive boxcar deconvolution on full Lebesgue measure sets (2004)
Kerkyacharian, Gérard, Picard, Dominique, Raimondo, Marc
We consider the nonparametric estimation of a function that is observed in white noise after convolution with a boxcar, the indicator of an interval $(-a,a)$. In a recent paper \citet{jkpr04} have...
Autin, Florent, Picard, Dominique, Rivoirard, Vincent
In this paper our aim is to provide tools for easily calculating the maxisets of several procedures. Then we apply these results to perform a comparison between several Bayesian estimators in a non...
Adaptive boxcar deconvolution on full Lebesgue measure sets (2004)
Kerkyacharian, Gérard, Picard, Dominique, Raimondo, Marc
We consider the nonparametric estimation of a function that is observed in white noise after convolution with a boxcar, the indicator of an interval $(-a,a)$. In a recent paper \citet{jkpr04} have...
Autin, Florent, Picard, Dominique, Rivoirard, Vincent
In this paper our aim is to provide tools for easily calculating the maxisets of several procedures. Then we apply these results to perform a comparison between several Bayesian estimators in a non...
Wavelet Deconvolution in a Periodic Setting (2003)
Iain M. Johnstone, Gerard Kerkyacharian, Dominique Picard, Marc Raimondo
In this paper, we present an inverse estimation procedure which combines Fourier analysis with wavelet expansion. In the periodic setting, our method can recover a blurred function observed in white...
Regression in Random Design and Warped Wavelets. (2003)
G Erard Kerkyacharian, Dominique Picard
We consider the problem of estimating an unknown function f in a regression setting with random design. Instead of expanding the function on a regular wavelet basis, we expand it on the basis jk (G),...
Convergence Properties Of Wavelet Estimators (2002)
Peter Hall, Gerard Kerkyacharian, Dominique Picard
Adaptive sampling schemes with multiple sampling rates have the potential to significantly improve the e#ciency and e#ectiveness of methods for signal analysis. For example, in the case of equipment...
Kerkyacharian, Gérard, Picard, Dominique
We discuss a new way of evaluating the performance of a statistical estimation procedure. This consists of investigating the maximal set where a given procedure has a given rate of convergence....
Adaptive confidence interval for pointwise curve estimation (2000)
Picard, Dominique, Tribouley, Karine
We present a procedure associated with nonlinear wavelet methods that provides adaptive confidence intervals around $f (x_0)$, in either a white noise model or a regression setting. A suitable...
Thresholding algorithms, maxisets and well-concentrated bases (2000)
Kerkyacharian, Gérard, Picard, Dominique
The aim of this paper la to synthetically analyse the performances of thresholding and wavelet estimation methods. In this connection, it la useful to describe the maxlmal sets where these methods...
Thresholding algorithms, maxisets and well-concentrated bases (2000)
Kerkyacharian, Gérard, Picard, Dominique
The aim of this paper la to synthetically analyse the performances of thresholding and wavelet estimation methods. In this connection, it la useful to describe the maxlmal sets where these methods...
Wavelet Shrinkage: Asymptopia? (1999)
David L. Donoho, Iain M. Johnstone, Dominique Picard
Considerable effort has been directed recently to develop asymptotically minimax methods in problems of recovering infinite-dimensional objects (curves, densities, spectral densities, images) from...
Maximal Spaces with given rate of convergence for thresholding algorithms (1999)
Albert Cohen, Ronald Devore, Gerard Kerkyacharian, Dominique Picard
this paper is to discuss the existence and the nature of maximal spaces in the context of nonlinear methods based on thresholding (or shrinkage) procedures. Before going further, some remarks should...
Maximal Spaces with given rate of convergence for thresholding algorithms (1999)
Albert Cohen, Ronald Devore, Gerard Kerkyacharian, Dominique Picard
this paper is to discuss the existence and the nature of maximal spaces in the context of nonlinear methods based on thresholding (or shrinkage) procedures. Before going further, some remarks should...
Maximal Spaces with given rate of convergence for thresholding algorithms (1999)
Albert Cohen, Ronald Devore, Gerard Kerkyacharian, Dominique Picard
this paper is to discuss the existence and the nature of maximal spaces in the context of nonlinear methods based on thresholding (or shrinkage) procedures. Before going further, some remarks should...
Wavelet Shrinkage: Asymptopia? (1998)
David L. Donoho, Iain M. Johnstone, Dominique Picard
Considerable effort has been directed recently to develop asymptotically minimax methods in problems of recovering infinite-dimensional objects (curves, densities, spectral densities, images) from...
Density Estimation By Wavelet Thresholding (1998)
David L. Donoho, Iain M. Johnstone, Dominique Picard
Density estimation is a commonly used test case for non-parametric estimation methods. We explore the asymptotic properties of estimators based on thresholding of empirical wavelet coefficients....
Block threshold rules for curve estimation using kernel and wavelet methods (1998)
Hall, Peter, Kerkyacharian, Gérard, Picard, Dominique
Motivated by recently developed threshold rules for wavelet estimators, we suggest threshold methods for general kernel density estimators, including those of classical Rosenblatt–Parzen type....
Politesse, savoir-vivre et relations sociales / Dominique Picard (1998)
Incluye bibliografía e índice
Wavelet Shrinkage: Asymptopia? (1997)
David L. Donoho, Iain M. Johnstone, Dominique Picard
Considerable effort has been directed recently to develop asymptotically minimax methods in problems of recovering infinite-dimensional objects (curves, densities, spectral densities, images) from...
Estimating nonquadratic functionals of a density using Haar wavelets (1996)
Kerkyacharian, Gérard, Picard, Dominique
Z.Consider the problem of estimating $\int \Phi(f)$, where $\Phi$ is a smooth function and f is a density with given order of regularity s. Special attention is paid to the case $\Phi(t) = t^3$. It...
Density estimation by wavelet thresholding (1996)
Donoho, David L., Johnstone, Iain M., Kerkyacharian, Gérard, Picard, Dominique
Density estimation is a commonly used test case for nonparametric estimation methods. We explore the asymptotic properties of estimators based on thresholding of empirical wavelet coefficients....
Wavelet Shrinkage: Asymptopia? (1994)
David L. Donoho, Iain M. Johnstone, Dominique Picard
Considerable effort has been directed recently to develop asymptotically minimax methods in problems of recovering infinite-dimensional objects (curves, densities, spectral densities, images) from...
Density Estimation By Wavelet Thresholding (1994)
David L. Donoho, Iain M. Johnstone, Dominique Picard
Density estimation is a commonly used test case for non-parametric estimation methods. We explore the asymptotic properties of estimators based on thresholding of empirical wavelet coefficients....
Wavelet Shrinkage: Asymptopia? (1994)
David L. Donoho, Iain M. Johnstone, Dominique Picard
Considerable effort has been directed recently to develop asymptotically minimax methods in problems of recovering infinite-dimensional objects (curves, densities, spectral densities, images) from...
Wavelet Shrinkage: Asymptopia? (1994)
David L. Donoho, Iain M. Johnstone, Dominique Picard
Considerable effort has been directed recently to develop asymptotically minimax methods in problems of recovering infinite-dimensional objects (curves, densities, spectral densities, images) from...
Density Estimation By Wavelet Thresholding (1994)
David L. Donoho, Iain M. Johnstone, Dominique Picard
Density estimation is a commonly used test case for non-parametric estimation methods. We explore the asymptotic properties of estimators based on thresholding of empirical wavelet coefficients....
Density Estimation By Wavelet Thresholding (1994)
David L. Donoho, Iain M. Johnstone, Dominique Picard
Density estimation is a commonly used test case for non-parametric estimation methods. We explore the asymptotic properties of estimators based on thresholding of empirical wavelet coefficients....
Wavelet Shrinkage: Asymptopia? (1994)
David L. Donoho, Iain M. Johnstone, Dominique Picard
Considerable effort has been directed recently to develop asymptotically minimax methods in problems of recovering infinite-dimensional objects (curves, densities, spectral densities, images) from...
Density Estimation By Wavelet Thresholding (1994)
David L. Donoho, Iain M. Johnstone, Dominique Picard
Density estimation is a commonly used test case for non-parametric estimation methods. We explore the asymptotic properties of estimators based on thresholding of empirical wavelet coefficients....
La interacción social: cultura, instituciones y comunicaciòn (1992)
Marc, Edmond, Picard, Dominique
Traducción de: La Interaction Sociale
La interacción social: cultura, instituciones y comunicaciòn (1992)
Marc, Edmond, Picard, Dominique
84-7509-748-0
La interacción social : cultura, instituciones y comunicación / Edmond Marc, Dominíque Picard (1992)
Marc, Edmond, Picard, Dominique
Traducción de: L'interaction sociale
Del código al deseo : el cuerpo en la relación social (1986)
Picard, Dominique, Maisonneuve, Jean (pref.)
Traducción de: Du code au désir. Le corps dans la relation sociale
Del código al deseo : el cuerpo en la relación social (1986)
Picard, Dominique, Maisonneuve, Jean (pref.)
950-12-4423-7
Ruptures de modèles en statistique / (1983)
Thesis (doctoral)--Université de Paris-Sud, 1983.
Density Estimation By Wavelet Thresholding (1970)
David L. Donoho, Iain M. Johnstone, Dominique Picard
Density estimation is a commonly used test case for non-parametric estimation methods. We explore the asymptotic properties of estimators based on thresholding of empirical wavelet coefficients....
Wavelet deconvolution in a periodic setting
Iain M. Johnstone, Gérard Kerkyacharian, Dominique Picard, Marc Raimondo
Deconvolution problems are naturally represented in the Fourier domain, whereas thresholding in wavelet bases is known to have broad adaptivity properties. We study a method which combines both fast...
Thresholding algorithms, maxisets and well-concentrated bases
Gérard Kerkyacharian, Dominique Picard, Lucien Birgé, Peter Hall, Oleg Lepski, Enno Mammen, ...
Approximation methods, Besov spaces, denoising, minimax rate of convergence, non parametric estimation, oracle inequalities, saturation spaces, wavelet thresholding, 62G05, 62G07, 62G20,
Statistical morphisms and related invariance properties
Statistical manifold, Amari connections, comparison of experiments, likelihood expansions, asymptotic properties of tests.,