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This paper deals with the multi-term generalisation of the time-fractional diffusion-wave equation for general operators with discrete spectrum, as well as for positive hypoelliptic operators, with homogeneous multi-point time-nonlocal…

Analysis of PDEs · Mathematics 2020-05-05 Michael Ruzhansky , Niyaz Tokmagambetov , Berikbol T. Torebek

We study the learning properties of nonparametric ridge-less least squares. In particular, we consider the common case of estimators defined by scale dependent kernels, and focus on the role of the scale. These estimators interpolate the…

Machine Learning · Statistics 2021-11-11 Nicolò Pagliana , Alessandro Rudi , Ernesto De Vito , Lorenzo Rosasco

This is a partly expository article for the volume "Algebraic and Analytic Microlocal Analysis" on pointwise Weyl laws for spectral projections kernels in the Kaehler setting. We prove a 2-term pointwise Weyl law for projections onto sums…

Complex Variables · Mathematics 2019-09-02 Steve Zelditch , Peng Zhou

We consider the EBT algorithm (a particle method) for the non-local equation with a discontinuous interaction kernel. The main difficulty lies in the low regularity of the kernel which is not Lipschitz continuous, thus preventing the…

Numerical Analysis · Mathematics 2021-06-23 Piotr Gwiazda , Błażej Miasojedow , Jakub Skrzeczkowski , Zuzanna Szymańska

We consider the large deviations associated with the empirical mean of independent and identically distributed random variables under a subexponential moment condition. We show that non-trivial deviations are observable at a subexponential…

Probability · Mathematics 2025-07-22 Grégoire Ferré

We use exponential asymptotics to match the late time temperature evolution of an expanding, conformally invariant fluid to its early time behaviour. We show that the rich divergent transseries asymptotics at late times can be used to…

High Energy Physics - Theory · Physics 2023-05-03 Inês Aniceto , Daniel Hasenbichler , Adri Olde Daalhuis

Kernel approximation methods create explicit, low-dimensional kernel feature maps to deal with the high computational and memory complexity of standard techniques. This work studies a supervised kernel learning methodology to optimize such…

Machine Learning · Computer Science 2020-02-17 Mert Al , Zejiang Hou , Sun-Yuan Kung

We derive the local and central limit theorems for the Stirling numbers of the second kind by elementary means, obtaining as corollaries effective asymptotic estimates for the Bell numbers and for the moments of the distribution. We also…

Combinatorics · Mathematics 2026-05-29 Hsien-Kuei Hwang , Chong-Yi Li , Vytas Zacharovas

We investigate the large-time behavior of the solutions of the two-dimensional Keller-Segel system in self-similar variables, when the total mass is subcritical, that is less than 8\pi after a proper adimensionalization. It was known from…

Analysis of PDEs · Mathematics 2013-10-11 Juan Campos Serrano , Jean Dolbeault

We give an elementary proof of the existence of an asymptotic expansion in powers of $k$ of the Bergman kernel associated to $L^k$, where $L$ is a positive line bundle. We also give an algorithm for computing the coefficients in the…

Complex Variables · Mathematics 2007-11-12 Robert Berman , Bo Berndtsson , Johannes Sjoestrand

An asymptotic expansion for inverse moments of positive binomial and Poisson distributions is derived. The expansion coefficients of the asymptotic series are given by the positive central moments of the distribution. Compared to previous…

Statistics Theory · Mathematics 2009-01-16 Marko Znidaric

We study the large-time behavior of the continuous-time heat kernel and of solutions to the heat equation on homogeneous trees. First, we derive sharp asymptotic formulas for the heat kernel as $t\to\infty$. Second, using them, we show that…

Analysis of PDEs · Mathematics 2026-03-13 Effie Papageorgiou

We consider an extension of the conventional quantum Heisenberg algebra, assuming that coordinates as well as momenta fulfil nontrivial commutation relations. As a consequence, a minimal length and a minimal mass scale are implemented. Our…

High Energy Physics - Theory · Physics 2011-02-22 Martin Kober , Piero Nicolini

We consider the limiting behavior of fluctuations of small noise diffusions with multiple scales around their homogenized deterministic limit. We allow full dependence of the coefficients on the slow and fast motion. These processes arise…

Probability · Mathematics 2015-02-20 Konstantinos Spiliopoulos

This paper develops a general asymptotic theory for nonparametric kernel regression in the presence of cluster dependence. We examine nonparametric density estimation, Nadaraya-Watson kernel regression, and local linear estimation. Our…

Econometrics · Economics 2024-12-31 Yuya Shimizu

We prove weak convergence in a separable Hilbert space for estimators of high-dimensional regression coefficients, which yields asymptotic normality and enables direct use of standard asymptotic tools such as the continuous mapping theorem.…

Statistics Theory · Mathematics 2026-05-05 Kou Fujimori , Koji Tsukuda

Recently proposed nonlocal and nonperturbative late time behavior of the heat kernel is generalized to curved spacetimes. Heat kernel trace asymptotics is dominated by two terms one of which represents a trivial covariantization of the…

High Energy Physics - Theory · Physics 2009-11-10 A. O. Barvinsky , Yu. V. Gusev , V. F. Mukhanov , D. V. Nesterov

We consider a metric measure space with a local regular Dirichlet form. We establish necessary and sufficient conditions for upper heat kernel bounds with sub-diffusive space-time exponent to hold. This characterization is stable under…

Probability · Mathematics 2015-03-17 Sebastian Andres , Martin T. Barlow

We consider the kernel partial least squares algorithm for non-parametric regression with stationary dependent data. Probabilistic convergence rates of the kernel partial least squares estimator to the true regression function are…

Statistics Theory · Mathematics 2017-06-13 Marco Singer , Tatyana Krivobokova , Axel Munk

Current Lagrangian (particle-tracking) algorithms used to simulate diffusion-reaction equations must employ a certain number of particles to properly emulate the system dynamics---particularly for imperfectly-mixed systems. The number of…

Numerical Analysis · Mathematics 2017-03-08 Michael Schmidt , Stephen Pankavich , David Benson