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The aim of the paper is to show that the solutions to variational problems with non-standard growth conditions satisfy a corresponding variational inequality without any smallness assumptions on the gap between growth and coercitivity…

Analysis of PDEs · Mathematics 2020-10-09 Michela Eleuteri , Antonia Passarelli di Napoli

We have derived the coefficients of the highest three 1/x-enhanced small-x logarithms of all timelike splitting functions and the coefficient functions for the transverse fragmentation function in one-particle inclusive e^+e^- annihilation…

High Energy Physics - Phenomenology · Physics 2015-05-30 A. Vogt

We study singular limits of stochastic evolution equations in the interplay of disappearing strength of the noise and insufficient regularity, where the equation in the limit with noise would not be defined due to lack of regularity. We…

Probability · Mathematics 2023-11-07 Dirk Blömker , Jonas M. Tölle

We introduce an expressive subclass of non-negative almost submodular set functions, called strongly 2-coverage functions which include coverage and (sums of) matroid rank functions, and prove that the homogenization of the generating…

Combinatorics · Mathematics 2023-03-08 Dorna Abdolazimi , Shayan Oveis Gharan

We present numerical solutions of the $Q^2$ evolution equations at next-to-leading order (NLO) for unpolarized and polarized parton distributions, in both the flavor non-singlet and singlet channels. The numerical method is based on a…

High Energy Physics - Phenomenology · Physics 2009-10-28 T. Weigl , W. Melnitchouk

This work deals with the homogenization of functionals with linear growth in the context of $\mathcal{A}$-quasiconvexity. A representation theorem is proved, where the new integrand function is obtained by solving a cell problem where the…

Analysis of PDEs · Mathematics 2014-10-03 José Matias , Marco Morandotti , Pedro M. Santos

In this paper, we investigate the stochastic evolution equations (SEEs) driven by $\log$-Whittle-Mat$\acute{{\mathrm{e}}}$rn (W-M) random diffusion coefficient field and $Q$-Wiener multiplicative force noise. First, the well-posedness of…

Numerical Analysis · Mathematics 2022-07-05 X. Qi , M. Azaiez , C. Huang , C. Xu

In this paper we establish a framework for normal approximation for white noise functionals by Stein's method and Hida calculus. Our work is inspired by that of Nourdin and Peccati (Probab. Theory Relat. Fields 145, 75-118, 2009), who…

Probability · Mathematics 2017-09-20 Louis H. Y. Chen , Yuh-Jia Lee , Hsin-Hung Shih

We introduce the notion of logarithmically concave (or log-concave) sequences in Coding Theory. A sequence $a_0, a_1, \dots, a_n$ of real numbers is called log-concave if $a_i^2 \ge a_{i-1}a_{i+1}$ for all $1 \le i \le n-1$. A natural…

Information Theory · Computer Science 2024-10-08 Minjia Shi , Xuan Wang , Junmin An , Jon-Lark Kim

The sharp growth and distortion theorems are established for slice monogenic extensions of univalent functions on the unit disc $\mathbb D\subset \mathbb C$ in the setting of Clifford algebras, based on a new convex combination identity.…

Complex Variables · Mathematics 2017-01-17 Guangbin Ren , Xieping Wang

Linear second-order ordinary differential equations of the form $d^{2}w/dz^{2}=\{u^{2}f(a,z)$ $+g(z)\}w$ are studied for large values of the real parameter $u$, where $z$ ranges over a bounded or unbounded complex domain $Z$, and $a_{0} \le…

Classical Analysis and ODEs · Mathematics 2025-11-04 T. M. Dunster

We study the problem of approximating and learning coverage functions. A function $c: 2^{[n]} \rightarrow \mathbf{R}^{+}$ is a coverage function, if there exists a universe $U$ with non-negative weights $w(u)$ for each $u \in U$ and subsets…

Machine Learning · Computer Science 2014-05-29 Vitaly Feldman , Pravesh Kothari

We present two linear relations between an arbitrary (real tempered second order) generalized stochastic process over $\mathbb{R}^{d}$ and White Noise processes over $\mathbb{R}^{d}$. The first is that any generalized stochastic process can…

Probability · Mathematics 2021-11-04 R. Carrizo Vergara

Dyson-Schwinger equations determine the Green functions $G^r(\alpha,L)$ in quantum field theory. Their solutions are triangular series in a coupling constant $\alpha$ and an external scale parameter $L$ for a chosen amplitude $r$, with the…

High Energy Physics - Theory · Physics 2015-02-12 Olaf Krueger , Dirk Kreimer

We aim to explain whether a stress memory task has a significant impact on tonal coarticulation. We contribute a novel approach to analyse tonal coarticulation in phonetics, where several f0 contours are compared with respect to their…

Applications · Statistics 2024-09-10 Valentina Masarotto , Yiya Chen

Learning unnormalized statistical models (e.g., energy-based models) is computationally challenging due to the complexity of handling the partition function. To eschew this complexity, noise-contrastive estimation~(NCE) has been proposed by…

Machine Learning · Computer Science 2023-06-14 Wei Jiang , Jiayu Qin , Lingyu Wu , Changyou Chen , Tianbao Yang , Lijun Zhang

This article investigates the role of the regularity of the test function when considering the weak error for standard discretizations of SPDEs of the form $dX(t)=AX(t)dt+F(X(t))dt+dW(t)$, driven by space-time white noise. In previous…

Probability · Mathematics 2017-09-28 Charles-Edouard Bréhier

The governed equations for the order parameter, one-time and two-time correlators are obtained on the basis of the Langevin equation with the white multiplicative noise which amplitude $x^{a}$ is determined by an exponent $0<a<1$ ($x$ being…

Statistical Mechanics · Physics 2016-08-31 Alexander I. Olemskoi , Dmitrii O. Kharchenko

Consider a random process s solution of the stochastic partial differential equation Ls = w with L a homogeneous operator and w a multidimensional L\'evy white noise. In this paper, we study the asymptotic effect of zooming in or zooming…

Probability · Mathematics 2018-01-11 Julien Fageot , Michael Unser

We consider training decision trees using noisily labeled data, focusing on loss functions that can lead to robust learning algorithms. Our contributions are threefold. First, we offer novel theoretical insights on the robustness of many…

Machine Learning · Computer Science 2024-01-24 Jonathan Wilton , Nan Ye
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