Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Alexandros Eskenazis"'
Publikováno v:
Discrete Analysis (2023)
Low-degree learning and the metric entropy of polynomials, Discrete Analysis 2023:17, 23 pp. This paper is a follow-up to a paper by the first two authors on the general problem of designing algorithms that can efficiently learn functions defined on
Externí odkaz:
https://doaj.org/article/bb0396089e3a4a9cbbbee2fca36f2803
Autor:
Alexandros Eskenazis, Paata Ivanisvili
Publikováno v:
Israel Journal of Mathematics. 253:469-485
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::97b66edeb9f49a5295b219d01ea8d2ec
https://doi.org/10.1007/s11856-022-2373-8
https://doi.org/10.1007/s11856-022-2373-8
Publikováno v:
Bulletin of the London Mathematical Society.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d07ff8d45eb14aab205b62cb968b860d
https://doi.org/10.1112/blms.12786
https://doi.org/10.1112/blms.12786
Autor:
Alexandros Eskenazis
Publikováno v:
Canadian Mathematical Bulletin. 64:282-291
We prove an extension of Pisier’s inequality (1986) with a dimension-independent constant for vector-valued functions whose target spaces satisfy a relaxation of the UMD property.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::caeef118f91cacbe8311e418b317acd3
https://doi.org/10.4153/s0008439520000442
https://doi.org/10.4153/s0008439520000442
Autor:
Paata Ivanisvili, Alexandros Eskenazis
Publikováno v:
Probability Theory and Related Fields. 178:235-287
Let $$(X,\Vert \cdot \Vert _X)$$ be a Banach space. The purpose of this article is to systematically investigate dimension independent properties of vector valued functions $$f:\{-1,1\}^n\rightarrow X$$ on the Hamming cube whose spectrum is bounded a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3d682c51235b7d30176f645bb31d1b9a
https://doi.org/10.1007/s00440-020-00973-y
https://doi.org/10.1007/s00440-020-00973-y
Publikováno v:
Inventiones mathematicae. 217:833-886
We prove that not every metric space embeds coarsely into an Alexandrov space of nonpositive curvature. This answers a question of Gromov (1993) and is in contrast to the fact that any metric space embeds coarsely into an Alexandrov space of nonnegat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7912494f24dea0ae0bc2f0b9c9823591
https://doi.org/10.1007/s00222-019-00878-1
https://doi.org/10.1007/s00222-019-00878-1
Autor:
Alexandros Eskenazis, Evita Nestoridi
Publikováno v:
Ann. Inst. H. Poincaré Probab. Statist. 56, no. 4 (2020), 2621-2639
Nous etudions le temps de melange de l’urne de Bernoulli–Laplace de parametres $(n,k)$, ou $k\in\{0,1,\ldots,n\}$. On considere deux urnes, chacune contenant $n$ boules, telles que combinees elles ont exactement $n$ boules rouges et $n$ boules bl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::13eb524071c79e487557ea5894459eaf
https://doi.org/10.1214/20-aihp1052
https://doi.org/10.1214/20-aihp1052
Let $\mathscr{C}_n=\{-1,1\}^n$ be the discrete hypercube equipped with the uniform probability measure $\sigma_n$. Talagrand's influence inequality (1994) asserts that there exists $C\in(0,\infty)$ such that for every $n\in\mathbb{N}$, every function
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9bf7d2467a9774a048f0378dbbd7e752
Autor:
Alexandros Eskenazis, Paata Ivanisvili
Publikováno v:
Journal of Approximation Theory. 253:105377
We obtain the following dimension independent Bernstein–Markov inequality in Gauss space: for each 1 ≤ p ∞ there exists a constant C p > 0 such that for any k ≥ 1 and all polynomials P on R k we have ‖ ∇ P ‖ L p ( R k , d γ k ) ≤ C p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::39ef618ec829a84fc473df692ef38e13
https://doi.org/10.1016/j.jat.2020.105377
https://doi.org/10.1016/j.jat.2020.105377
Publikováno v:
Ann. Probab. 46, no. 5 (2018), 2908-2945
A symmetric random variable is called a Gaussian mixture if it has the same distribution as the product of two independent random variables, one being positive and the other a standard Gaussian random variable. Examples of Gaussian mixtures include r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::25f8c3e85a6547629552a38948b5165c
https://doi.org/10.1214/17-aop1242
https://doi.org/10.1214/17-aop1242