Zobrazeno 1 - 10
of 53
pro vyhledávání: '"Gerard Kerkyacharian"'
Autor:
Pencho Petrushev, Athanasios G. Georgiadis, Dominique Picard, Gerard Kerkyacharian, Galatia Cleanthous
Publikováno v:
Cleanthous, G, Georgiadis, A, Kerkyacharian, G, Petrushev, P & Picard, D 2018 ' Kernel and wavelet density estimators on manifolds and more general metric spaces ' arXiv . < https://arxiv.org/abs/1805.04682 >
Bernoulli 26, no. 3 (2020), 1832-1862
Bernoulli 26, no. 3 (2020), 1832-1862
We consider the problem of estimating the density of observations taking values in classical or nonclassical spaces such as manifolds and more general metric spaces. Our setting is quite general but also sufficiently rich in allowing the development
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bfb636af3f428e6be9e283df71df30a0
https://vbn.aau.dk/da/publications/68c2ac95-a895-4946-a76e-68a2cf5dcd36
https://vbn.aau.dk/da/publications/68c2ac95-a895-4946-a76e-68a2cf5dcd36
The aim of this article is to establish two-sided Gaussian bounds for the heat kernels on the unit ball and simplex in $${{\mathbb {R}}}^n$$, and in particular on the interval, generated by classical differential operators whose eigenfunctions are al
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b041f5896f3e6b9350c58595f235480b
Publikováno v:
Constructive Approximation. 35:225-243
Constructing a good approximation to a function of many variables suffers from the “curse of dimensionality”. Namely, functions on ℝN with smoothness of order s can in general be captured with accuracy at most O(n−s/N) using linear spaces or
Publikováno v:
Teoriya Veroyatnostei i ee Primeneniya. 52:150-171
Publikováno v:
Constructive Approximation
Constructive Approximation, 2018, Constructive Approximation, 47 (2), pp.277-320. ⟨10.1007/s00365-018-9416-8⟩
Constructive Approximation, 2018, Constructive Approximation, 47 (2), pp.277-320. ⟨10.1007/s00365-018-9416-8⟩
We study the regularity of centered Gaussian processes $$(Z_x( \omega ))_{x\in M}$$ , indexed by compact metric spaces $$(M, \rho )$$ . It is shown that the almost everywhere Besov regularity of such a process is (almost) equivalent to the Besov regu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fdefe6472e051fb91575addb349254b1
Autor:
Dominique Picard, Gerard Kerkyacharian
Publikováno v:
Constructive Approximation. 24:123-156
In the general atomic setting of an unconditional basis in a (quasi-) Banach space, we show that representing the spaces of m-terms approximation as Lorentz spaces is equivalent to the verification of two inequalities (Jackson and Bernstein), and tha
Autor:
Eero Saksman, Dominique Picard, S Meng, F Ruymgaart, David J. Evans, Manfred Opper, G Wahba, Robert G. Aykroyd, L Cavalier, Manuel Davy, Heikki Haario, Ad Stoffelen, Sofia C. Olhede, Daniela De Canditiis, Simon J. Godsill, Felix Abramovich, Christophe Andrieu, Guy P. Nason, Patrick J. Wolfe, Markku Lehtinen, Lehel Csató, Dan Cornford, C Butucea, Eric Moulines, D Paul, Gerard Kerkyacharian, E Khabie-Zeitoune, Marko Laine, Marianna Pensky, Alexandre B. Tsybakov, Johanna Tamminen, Marc Raimondo, Robert West, Ross N. Hoffman, W Ng, U Golubev, Noel A Cressie, Iain M. Johnstone, Christian P. Robert, Axel Munk
Publikováno v:
Journal of the Royal Statistical Society Series B: Statistical Methodology. 66:627-652
Johnstone, Kerkyacharian, Picard and Raimondo Johnstone, Kerkyacharian, Picard and Raimondo are interested in the inverse problem of estimating f where f has been convolved with g and then contaminated with white noise. This popular problem has been
Autor:
Dominique Picard, Gerard Kerkyacharian
Publikováno v:
ESAIM: Probability and Statistics. 7:239-250
We present here a new proof of the theorem of Birman and Solomyak on the metric entropy of the unit ball of a Besov space on a regular domain of The result is: if s - d(1/π - 1/p) + > 0, then the Kolmogorov metric entropy satisfies H(e) ~ e -d/s . T
Publikováno v:
Probability Theory and Related Fields
Probability Theory and Related Fields, Springer Verlag, 2014, 158 (3-4), pp.665-710
Probability Theory and Related Fields, 2014, 158 (3-4), pp.665-710. ⟨10.1007/s00440-013-0493-0⟩
Probability Theory and Related Fields, Springer Verlag, 2014, 158 (3-4), pp.665-710
Probability Theory and Related Fields, 2014, 158 (3-4), pp.665-710. ⟨10.1007/s00440-013-0493-0⟩
International audience; Convergence of the Bayes posterior measure is considered in canonical statistical settings where observations sit on a geometrical object such as a compact manifold, or more generally on a compact metric space verifying some c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7a9f43441bf16399a3faff316e6631e7
https://hal.archives-ouvertes.fr/hal-00976006
https://hal.archives-ouvertes.fr/hal-00976006
Autor:
Gerard Kerkyacharian, Vladimir Koltchinskii, Alexandre B. Tsybakov, Dominique Picard, Vladimir Temlyakov
Publikováno v:
Constructive Approximation
Constructive Approximation, Springer Verlag, 2014, 39 (3), pp.421-444
Constructive Approximation, 2014, 39 (3), pp.421-444. ⟨10.1007/s00365-014-9229-3⟩
Constructive Approximation, Springer Verlag, 2014, 39 (3), pp.421-444
Constructive Approximation, 2014, 39 (3), pp.421-444. ⟨10.1007/s00365-014-9229-3⟩
Consider a standard binary classification problem, in which $$(X,Y)$$ is a random couple in $$\mathcal{X}\times \{0,1\}$$ , and the training data consist of $$n$$ i.i.d. copies of $$(X,Y).$$ Given a binary classifier $$f:\mathcal{X}\mapsto \{0,1\},$$
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::da474d4f443d0127a53fc6f599bd7487
https://hal.archives-ouvertes.fr/hal-01019308
https://hal.archives-ouvertes.fr/hal-01019308