Y. Baraud, S. Huet, and B. Et, Adaptive tests of linear hypothesis by model selection, pp.31-225251, 2003.

A. Barron, L. Birgé, and P. Et-massart, Risk bound for model selection via penalization, Probab. Theory and Relat. Fields, p.301413, 1999.

A. Barron, M. J. Schervish, and L. Et-wasserman, The consistency of posterior distribution in nonparametric problems, p.536561, 1999.

P. J. Bickel and Y. Et-ritov, Estimating integrated squared density derivatives : sharp best order of convergence estimates, pp.50-381393, 1988.

L. Birgé, Approximation dans les espaces métriques et théorie de l'estimation, Z. Wahrsch. Ver. Geb, vol.65, p.181237, 1983.

L. Birgé and P. Et-massart, Estimation of Integral Functionals of a Density, The Annals of Statistics, vol.23, issue.1, p.1129, 1995.
DOI : 10.1214/aos/1176324452

L. Birgé and P. Et-massart, From model selection to adaptive estimation, Festschrift for Lucien Le Cam : Research Papers in Probability and Statistics, 1997.

L. Cavalier and A. B. Et-tsybakov, Penalized blockwise Stein's method, monotone oracles and sharp adaptive estimation, Mathematical Methods of Statistics, vol.10, p.247282, 2001.

C. K. Chu and P. E. Et-cheng, Estimation of jump points and jump values of a density function, Statistica Sinica, vol.6, p.7995, 1996.

D. L. Donoho and I. M. Et-johnstone, Minimax risk for l q losses over l p -balls, Probability Theory and Related Fields, p.277303, 1994.

D. L. Donoho and I. M. Et-johnstone, Adpating to unknown smoothness via wavelet shrinkage, J. Amer. Statist. Assos, vol.90, p.12001224, 1995.

D. L. Donoho and I. M. Et-johnstone, Neo-Classical Minimax Problems, Thresholding and Adaptive Function Estimation, Bernoulli, vol.2, issue.1, p.3962, 1996.
DOI : 10.2307/3318568

D. L. Donoho, I. M. Johnstone, G. Kerkyacharian, and D. Et-picard, Wavelet Shrinkage : Asymptotia ?, J.R. Statist. Soc. B, vol.57, p.301369, 1995.

D. L. Donoho and M. Et-nussbaum, Minimax quadratic estimation of a quadratic functional, Journal of Complexity, vol.6, issue.3, p.290323, 1990.
DOI : 10.1016/0885-064X(90)90025-9

J. L. Doob, Application of the theory of martingales, Le Calcul des Probabilités et ses applications, Colloques Internationaux du C.N.R.S, p.2327, 1949.

S. Efromovich, . Yu, and M. S. Et-pinsker, A learning algorithm for nonparametric ltering, Autom. Telem, vol.11, 1984.

S. Efromovich, . Yu, and M. Low, On optimal adaptive estimation of a quadratic functional, The Annals of Statistics, vol.24, issue.3, p.11061125, 1996.
DOI : 10.1214/aos/1032526959

M. S. Ermakov, Minimax detection of a signal in a white Gaussian noise, Theory Probab, Appl, vol.35, p.667679, 1990.

M. I. Freidlin and A. P. Et-korostelev, Image processing for plane domains : change-point problems for the domain's area, Problems of Information Transmission, pp.31-2745, 1995.

M. Fromont and C. Et-lévy-leduc, Adaptive tests for periodic signal detection with applications to laser vibrometry, ESAIM: Probability and Statistics, vol.10, p.4675, 2003.
DOI : 10.1051/ps:2006002
URL : https://hal.archives-ouvertes.fr/hal-00457760

R. Farrel, On the lack of a uniformly consistent sequence of estimate of a density function in certain cases, Ann. Math. Statist, vol.38, p.471474, 1967.

D. A. Freedman, On the asymptotic behavior of Bayes estimates in the discrete case, Ann. Math. Statist, vol.34, p.13861403, 1963.

F. Gamboa and E. Et-gassiat, Blind Deconvolution of discrete linear systems, Ann. Statist, vol.24, 1996.

E. Gassiat and E. Et-gautherat, Identication of noisy linear systems with discrete random input, IEEE Transaction on Information Theory, vol.44, 1998.

E. Gassiat and E. Et-gautherat, Speed of convergence for the blind deconvolution of a linear systems with discrete random input, p.16841705, 1999.

E. Gautherat, Déconvolution aveugle des systèmes linéaires aléatoires discrets bruités ou non, Thèse, 1997.

E. Gautherat, Déconvolution aveugle bruitée : estimation de la distribution du processus source, 2002.

S. Ghosal, J. K. Ghosh, and R. V. Et-ramamoorthy, Consistency issues in Bayesian non-parametrics, Asymptotics Nonparametrics and Times Series : A tribute to Madan Lal Puri, p.639668, 1999.

S. Ghosal, J. K. Ghosh, and R. V. Et-ramamoorthy, Posterior consistency of Dirichlet mixtures in density estimation, Ann. Statist, vol.27, p.143158, 1999.

S. Ghosal and A. Van-der-vaart, Convergence rates of posterior distributions for noniid observations, The Annals of Statistics, vol.35, issue.1, 2007.
DOI : 10.1214/009053606000001172

S. Ghosal and A. Van-der-vaart, Posterior convergence rates of Dirichlet mixtures at smooth densities, The Annals of Statistics, vol.35, issue.2, p.697723, 2007.
DOI : 10.1214/009053606000001271

A. Goldenshluger, A. B. Tsybakov, and A. Et-zeevi, Optimal change-point estimation from indirect observations, The Annals of Statistics, vol.34, issue.1, p.350372, 2006.
DOI : 10.1214/009053605000000750
URL : https://hal.archives-ouvertes.fr/hal-00080124

G. K. Golubev, Adaptive asymptotically minimax estimates for smooth signals . Problems of Information Transmission, p.5767, 1987.

G. K. Golubev, Nonparametric estimation of smooth densities of a distribution in L 2 , Problems Information Transmission, p.4454, 1992.

G. K. Golubev and M. Et-nussbaum, Adaptive spline estimates in a nonparametric regression model, Theory Probab, Appl, vol.37, p.521529, 1992.

E. Guerre and P. Et-lavergne, Optimal minimax rates for nonparametric specication testing in regression models, Econom. Theory, vol.18, p.11391171, 2002.

J. A. Hartigan, Estimation of a Convex Density Contour in Two Dimensions, Journal of the American Statistical Association, vol.38, issue.397, p.267270, 1987.
DOI : 10.1080/01621459.1987.10478428

J. Heikkinen, Curve and Surface Estimation Using Dynamic Step Functions, Practical Nonparametric and semiparametric Bayesian statistics, p.255272, 1998.
DOI : 10.1007/978-1-4612-1732-9_14

J. L. Horowitz and V. G. Et-spokoiny, An Adaptive, Rate-Optimal Test of a Parametric Mean-Regression Model Against a Nonparametric Alternative, Econometrica, vol.69, issue.3, pp.69-599631, 2001.
DOI : 10.1111/1468-0262.00207

Y. I. Ingster, On minimax nonparametric detection of a signal in Gaussian white noise, Probl. Inf. Trans, vol.18, pp.6173-6222, 1982.

Y. I. Ingster, Minimax testing of nonparametric hypotheses on a distribution density in L p -metrics, Theory Probab, Appl, pp.31-333337, 1986.

Y. I. Ingster, Minimax detection of a signal in ?p metrics, Journal of Mathematical Sciences, vol.30, issue.2, p.152168, 1990.
DOI : 10.1007/BF01254275

Y. I. Ingster, Asymptotically minimax hypothesis testing for nonparametric alternatives, Methods Stat, vol.2, pp.85114-171189, 1993.

Y. Ingster and I. A. Et-suslina, Nonparametric Goodness-of-Fit Testing Under Gaussian Models, Lecture Note in Statistics, vol.169, 2002.
DOI : 10.1007/978-0-387-21580-8

G. Kerkyacharian and D. Et-picard, Thresholding algorithms, maxisets and wellconcentrated bases, Test, issue.9, p.283344, 2000.
DOI : 10.1007/bf02595738

G. Kerkyacharian and D. Et-picard, Minimax or maxisets ?, Bernoulli, vol.8, issue.219, p.253, 2002.

R. Z. Khas-'minskii and V. S. Et-lebedev, On the properties of parametric estimators for areas of a discontinuous image, Problems of Control and Information Theory, vol.19, p.375385, 1990.

A. P. Korostelev, On minimax estimation of a discontinuous signal, Theory Probab, Appl, vol.32, p.727730, 1987.

A. P. Korostelev and A. B. Et-tsybakov, Minimax theory of image reconstruction, Lecture Notes in Statistics, vol.82, 1993.
DOI : 10.1007/978-1-4612-2712-0

B. Laurent, Ecient estimation of integral functionals of a density, Ann. Statist, vol.24, p.659681, 1996.

B. Laurent, Adaptive estimation of a quadratic functional of a density by model selection, ESAIM: Probability and Statistics, vol.9, p.118, 2005.
DOI : 10.1051/ps:2005001

B. Laurent and P. Et-massart, Adaptive estimation of a quadratic functional of a density by model selection, ESAIM: Probability and Statistics, vol.9, p.13021338, 2000.
DOI : 10.1051/ps:2005001

O. V. Lepskii, On a problem of adaptive estimation in Gaussian white noise, Theory Probab, Appl, vol.35, p.454466, 1990.

O. V. Lepskii, Asymptotically minimax adaptive estimation. I. Upper bounds, Theory Probab, Appl, vol.36, p.682697, 1991.
DOI : 10.1137/1136085

O. V. Lepskii, On asymptotically exact testing of nonparametric hypotheses, Discussion paper, 1993.

O. V. Lepskii, A. Nemirovski, and V. G. Et-spokoiny, On estimation of the L r norm of a regression function, Probability Theory and Related Fields, vol.113, issue.2, pp.221253-50, 1999.
DOI : 10.1007/s004409970006

O. V. Lepskii and A. B. Et-tsybakov, Asymptotically exact nonparametric hypothesis testing in sup-norm and at a xed point, p.1748, 2000.

T. H. Li, Blind Deconvolution of Linear Systems with Multilevel Nonstationary Inputs, The Annals of Statistics, vol.23, issue.2, p.690704, 1995.
DOI : 10.1214/aos/1176324542

J. Loubes and S. A. Et-van-de-geer, Adaptive estimation in regression, using soft thresholding type penalties, Statistica Neerlandica, vol.56, p.453478, 2002.

M. H. Neumann, Optimal change-point in inverse problems, Scand, J. Statist, vol.24, p.503521, 1997.

D. Nolan, The excess-mass ellipsoid, Journal of Multivariate Analysis, vol.39, issue.2, p.348371, 1991.
DOI : 10.1016/0047-259X(91)90106-C

M. Nussbaum, Spline smoothing in regression Models and Asymptotic Eciency in L 2, Ann. Statist, vol.13, p.984997, 1985.

D. Picard and K. Et-tribouley, Adaptive condence interval for pointwise curve estimation, Ann. Statist, vol.28, p.298335, 2000.

M. S. Pinsker, Optimal ltering of square integrable signals in Gaussian white noise, Problems of Information Transmission, p.120133, 1980.

W. Polonik, Measuring mass concentrations and estimating density contours clustersan excess mass approach, Ann. Statist, vol.23, issue.3, p.855881, 1995.
DOI : 10.1214/aos/1176324626
URL : http://projecteuclid.org/download/pdf_1/euclid.aos/1176324626

M. Raimondo, Minimax estimation of sharp change points, The Annals of Statistics, vol.26, issue.4, p.13791397, 1998.
DOI : 10.1214/aos/1024691247

P. Rigollet and R. Et-vert, Fast rates for plug-in estimators of density level sets, Preprint, 2007.

X. Shen and L. Et-wasserman, Rates of convergence of posterior distributions, Ann. Statist, vol.29, p.687714, 2001.

V. G. Spokoiny, Adaptive hypothesis testing using wavelets, The Annals of Statistics, vol.24, issue.6, p.24772498, 1996.
DOI : 10.1214/aos/1032181163
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.323.8383

V. G. Spokoiny, Adaptive and spatially adaptive testing of a nonparametric hypothesis, Math. Methods Stat, 1998.

C. Stone, The use of polynomial splines and their tensor products in multivariate function estimation, Ann. Statist, vol.22, p.118184, 1994.

I. A. Suslina, Minimax detection of a signal for l p ball, Zap. Nauchn. Semin. POMI, vol.207, p.127137, 1993.

A. B. Tsybakov, Multidimensional change-point problems and boundary esti mation, IMS Lecture Notes Monograph Series, 1994.
DOI : 10.1214/lnms/1215463133

A. B. Tsybakov, On nonparametric estimation of density level sets, The Annals of Statistics, vol.25, issue.3, p.948969, 1997.
DOI : 10.1214/aos/1069362732

A. B. Tsybakov, Introduction à l'estimation non-paramétrique, 2004.

G. Walther, Granulometric smoothing, The Annals of Statistics, vol.25, issue.6, pp.22732299-52, 1997.
DOI : 10.1214/aos/1030741072
URL : http://projecteuclid.org/download/pdf_1/euclid.aos/1030741072

. Bibliographie1 and G. Gayraud, Estimation of functionals of density support, Mathematical Methods of Statistics, vol.6, issue.1, pp.26-47, 1997.

G. Gayraud and K. Tribouley, Adaptive Estimation and Condence Interval for a Quadratic Functional by Wavelet, Statistics and probability letters, p.109122, 1999.

G. Gayraud and C. Pouet, Minimax Testing composite null hypotheses in the discrete regression scheme, Math. Methods Stat, vol.4, p.375394, 2001.

G. Gayraud, Minimax Estimation of a Discontinuity for the Density, Journal of Nonparametric Statistics, vol.44, issue.1-2, pp.12-5966, 2002.
DOI : 10.1214/aos/1176345206

G. Gayraud and A. B. Tsybakov, Testing Hypotheses About Contours in Images, Journal of Nonparametric Statistics, vol.23, issue.1-2, pp.12-6785, 2002.
DOI : 10.2307/1390737

G. Gayraud and C. Pouet, Adaptive minimax testing in the discrete regression scheme, Probability Theory and Related Fields, pp.4-531558, 2005.

G. Gayraud and J. Rousseau, Rates of Convergence for a Bayesian Level Set Estimation, Scandinavian Journal of Statistics, vol.22, issue.4, pp.639-660, 2005.
DOI : 10.1214/aos/1069362379

G. Gayraud and J. Rousseau, Consistency results on nonparametric Bayesian estimation of level sets using spatial priors, TEST, vol.25, issue.1, pp.90-108, 2007.
DOI : 10.1007/s11749-006-0003-0

E. Gautherat and G. Gayraud, Parametric Estimation in Noisy Blind Deconvolution Model : a New Estimation Procedure
URL : https://hal.archives-ouvertes.fr/hal-00367759