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Related papers: Inequalities for BMO on $\alpha$-trees

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We provide some new estimates for Bellman type functions for the dyadic maximal opeator on $R^n$ and of maximal operators on martingales related to weighted spaces. Using a type of symmetrization principle, introduced for the dyadic maximal…

Functional Analysis · Mathematics 2015-11-24 Antonios D. Melas , Eleftherios N. Nikolidakis , Dimitrios Cheliotis

We develop a Malliavin calculus on the horizontal path space of a totally geodesic Riemannian foliation. As a first application, under suitable assumptions, we prove a log-Sobolev inequality for a natural one-parameter family of…

Probability · Mathematics 2015-03-30 Fabrice Baudoin , Qi Feng

We find sharp conditions on the growth of a rooted regular metric tree such that the Neumann Laplacian on the tree satisfies a Hardy inequality. In particular, we consider homogeneous metric trees. Moreover, we show that a non-trivial…

Spectral Theory · Mathematics 2010-09-24 Tomas Ekholm , Rupert L. Frank , Hynek Kovarik

There is a strong interest in studying the correspondence between Euclidean quantum fields and neural networks. This correspondence takes different forms depending on the type of networks considered. In this work, we study this…

High Energy Physics - Theory · Physics 2023-10-30 W. A. Zúñiga-Galindo

We prove a bi-sublinear embedding for semigroups generated by non-smooth complex-coefficient elliptic operators in divergence form and for certain mutually dual pairs of Orlicz-space norms. This generalizes a result by Carbonaro and…

Functional Analysis · Mathematics 2023-02-24 Vjekoslav Kovač , Kristina Ana Škreb

Consider a non-doubling manifold with ends $M = \mathfrak{R}^{n}\sharp\, {\mathbb R}^{m}$ where $\mathfrak{R}^n=\mathbb{R}^n\times \mathbb{S}^{m-n}$ for $m> n \ge 3$. We say that an operator $L$ has a generalised Poisson kernel if $\sqrt{…

Analysis of PDEs · Mathematics 2019-08-27 Peng Chen , Xuan Thinh Duong , Ji Li , Liang Song , Lixin Yan

We study the Green function for the stationary Stokes system with bounded measurable coefficients in a bounded Lipschitz domain $\Omega\subset \mathbb{R}^n$, $n\ge 3$. We construct the Green function in $\Omega$ under the condition…

Analysis of PDEs · Mathematics 2017-07-14 Jongkeun Choi , Ki-Ahm Lee

In this paper, we consider a dilation type inequality on a weighted Riemannian manifold, which is classically known as Borell's lemma in high-dimensional convex geometry. We investigate the dilation type inequality as an isoperimetric type…

Differential Geometry · Mathematics 2021-04-13 Hiroshi Tsuji

We introduce a family of branch merging operations on continuum trees and show that Ford CRTs are distributionally invariant. This operation is new even in the special case of the Brownian CRT, which we explore in more detail. The…

Probability · Mathematics 2016-06-23 Franz Rembart

We consider an infinite homogeneous tree $\mathcal V$ endowed with the usual metric $d$ defined on graphs and a weighted measure $\mu$. The metric measure space $(\mathcal V,d,\mu)$ is nondoubling and of exponential growth, hence the…

Functional Analysis · Mathematics 2020-06-05 Laura Arditti , Anita Tabacco , Maria Vallarino

We prove a one-parameter family of sharp integral inequalities for functions on the $n$-dimensional unit ball. The inequalities are conformally invariant, and the sharp constants are attained for functions that are equivalent to a constant…

Functional Analysis · Mathematics 2012-01-31 Shibing Chen

We give an algorithm to enumerate the results on trees of monadic second-order (MSO) queries represented by nondeterministic tree automata. After linear time preprocessing (in the input tree), we can enumerate answers with linear delay (in…

Databases · Computer Science 2019-08-28 Antoine Amarilli , Pierre Bourhis , Stefan Mengel , Matthias Niewerth

In this paper our aim is to deduce some complete monotonicity properties and functional inequalities for the Bickley function. The key tools in our proofs are the classical integral inequalities, like Chebyshev, H\"older-Rogers,…

Classical Analysis and ODEs · Mathematics 2014-04-23 Árpád Baricz , Tibor K. Pogány

A loss function measures the discrepancy between the true values and their estimated fits, for a given instance of data. In classification problems, a loss function is said to be proper if a minimizer of the expected loss is the true…

Information Theory · Computer Science 2020-01-03 Amichai Painsky , Gregory W. Wornell

$W^{1, p}$ estimate for the solutions of elliptic equations whose coefficient matrix can have large jump along the boundary of subdomains is obtained. The principal coefficients are supposed to be in the John-Nirenberg space with small BMO…

Analysis of PDEs · Mathematics 2011-05-03 Ko Woon Um

The main focus of this contribution is on the harmonic Bergman spaces $\mathcal{B}_{\alpha}^{p}$ on the $q$-homogeneous tree $\mathfrak{X}_q$ endowed with a family of measures $\sigma_\alpha$ that are constant on the horocycles tangent to a…

Functional Analysis · Mathematics 2023-09-27 Filippo De Mari , Matteo Monti , Elena Rizzo

We study Bakry-Emery type estimates for the Laplace-Beltrami operator of a totally geodesic foliation. In particular, we are interested in situations for which the $\Gamma_2$ operator may not be bounded from below but the horizontal…

Differential Geometry · Mathematics 2014-12-12 Fabrice Baudoin , Michel Bonnefont

In this note we further investigate the procedure for computing tree-level amplitudes in Yang-Mills theory from connected instantons in the B-model on P^{3|4}, emphasizing that the problem of calculating Feynman diagrams is recast into the…

High Energy Physics - Theory · Physics 2011-05-05 Radu Roiban , Marcus Spradlin , Anastasia Volovich

This work proposes the Bregman-Tweedie classification model and analyzes the domain structure of the extended exponential function, an extension of the classic generalized exponential function with additional scaling parameter, and related…

Machine Learning · Computer Science 2019-07-17 Hyenkyun Woo

Nonnegative Boltzmann machines (NNBMs) are recurrent probabilistic neural network models that can describe multi-modal nonnegative data. NNBMs form rectified Gaussian distributions that appear in biological neural network models, positive…

Machine Learning · Statistics 2016-03-09 Muneki Yasuda
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