English
Related papers

Related papers: Schur expansion of random-matrix reproducing kerne…

200 papers

Explicit expressions are proven for derivatives of the ratio of a determinant or Pfaffian determinant and a Vandermonde determinant. Such ratios appear for example in general group integrals of Harish-Chandra--Itzykson--Zuber type and in…

Mathematical Physics · Physics 2026-04-09 Gernot Akemann , Georg Angermann , Mario Kieburg , Adrian Padellaro

Using notions of composita and composition of generating functions we obtain explicit formulas for Chebyshev polynomials, Legendre polynomials, Gegenbauer polynomials, Associated Laguerre polynomials, Stirling polynomials, Abel polynomials,…

Number Theory · Mathematics 2012-11-02 Vladimir Kruchinin , Dmitry Kruchinin

We show that sequences of skew Schur polynomials obtained from stretched semi-standard Young tableaux satisfy a linear recurrence, which we give explicitly. Using this, we apply this to finding certain asymptotic behavior of these Schur…

Combinatorics · Mathematics 2015-12-14 Per Alexandersson

We propose efficient random features for approximating a new and rich class of kernel functions that we refer to as Generalized Zonal Kernels (GZK). Our proposed GZK family, generalizes the zonal kernels (i.e., dot-product kernels on the…

Machine Learning · Computer Science 2022-02-09 Insu Han , Amir Zandieh , Haim Avron

We tackle the regularisation of a differential system related to generalised Krawtchouk polynomials. We show a straightforward connection between certain auxiliary quantities involving the recurrence coefficients of these polynomials and…

Classical Analysis and ODEs · Mathematics 2026-03-31 Galina Filipuk , Juan F. Mañas-Mañas , Juan J. Moreno-Balcázar , Cristina Rodríguez-Perales

We propose a refinement of the random matrix model for a certain family of $L$-functions over $\mathbb F_q[u]$, using techniques that we hope will eventually apply to an arbitrary family of $L$-functions. This consists of a probability…

Number Theory · Mathematics 2024-09-05 Will Sawin

We study the approximation of a square-integrable function from a finite number of evaluations on a random set of nodes according to a well-chosen distribution. This is particularly relevant when the function is assumed to belong to a…

Machine Learning · Statistics 2024-11-13 Ayoub Belhadji , Rémi Bardenet , Pierre Chainais

We study Schur Q-polynomials evaluated on a geometric progression, or equivalently q-enumeration of marked shifted tableaux, seeking explicit formulas that remain regular at q=1. We obtain several such expressions as multiple basic…

Combinatorics · Mathematics 2008-04-08 Hjalmar Rosengren

In this article, we establish the mathematical foundations for modeling the randomness of shapes and conducting statistical inference on shapes using the smooth Euler characteristic transform. Based on these foundations, we propose two…

Methodology · Statistics 2024-05-27 Kun Meng , Jinyu Wang , Lorin Crawford , Ani Eloyan

We provide a multidimensional weighted Euler--MacLaurin summation formula on polytopes and a multidimensional generalization of a result due to L. J. Mordell on the series expansion in Bernoulli polynomials. These results are consequences…

Classical Analysis and ODEs · Mathematics 2022-03-15 Luca Brandolini , Leonardo Colzani , Bianca Gariboldi , Giacomo Gigante , Alessandro Monguzzi

We present a new formula of Cauchy type for the nonsymmetric Macdonald polynomials which are joint eigenfunctions of q-Dunkl operators. This gives the explicit formula for a reproducing kernel on the polynomial ring of n variables.

q-alg · Mathematics 2008-02-03 K. Mimachi , M. Noumi

We prove that for arbitrary partitions $\mathbf{\lambda} \subseteq \mathbf{\kappa},$ and integers $0\leq c<r\leq n,$ the sequence of Schur polynomials $S_{(\mathbf{\kappa} + k\cdot \mathbf{1}^c)/(\mathbf{\lambda} + k\cdot…

Combinatorics · Mathematics 2015-12-14 Per Alexandersson

In this note we analyze the Caffarelli-Silvestre extension function using tools from the theory of stochastic analysis applied to Dirichlet problems. We use a stochastic approach to give the explicit formulation of the kernel associated to…

Probability · Mathematics 2023-10-03 Michelangelo Cavina

We briefly review the solution of three ensembles of non-Hermitian random matrices generalizing the Wishart-Laguerre (also called chiral) ensembles. These generalizations are realized as Gaussian two-matrix models, where the complex…

Mathematical Physics · Physics 2011-06-01 Gernot Akemann

This paper derives exponential tail bounds and polynomial moment inequalities for the spectral norm deviation of a random matrix from its mean value. The argument depends on a matrix extension of Stein's method of exchangeable pairs for…

Probability · Mathematics 2013-05-06 Daniel Paulin , Lester Mackey , Joel A. Tropp

In this note we extend kernel function approximation results for neural networks with Gaussian-distributed weights to single-layer networks initialized using Haar-distributed random orthogonal matrices (with possible rescaling). This is…

Machine Learning · Computer Science 2021-04-14 James Martens

This article establishes a rigorous spectral framework for the mathematical analysis of SHAP values. We show that any predictive model defined on a discrete or multi-valued input space admits a generalized Fourier expansion with respect to…

Optimization and Control · Mathematics 2025-11-04 Roberto Morales

Umbral extensions of the stirling numbers of the second kind are considered and the resulting dobinski-like various formulas including new ones are presented. These extensions naturally encompass the two well known q-extensions. The further…

Combinatorics · Mathematics 2008-02-11 A. K. Kwasniewski

This paper deals with some special integral transforms of Bargmann-Fock type in the setting of quaternionic valued slice hyperholomorphic and Cauchy-Fueter regular functions. The construction is based on the well-known Fueter mapping…

Complex Variables · Mathematics 2019-10-02 Kamal Diki , Rolf Sören Krausshar , Irene Sabadini

Devoted to multi-task learning and structured output learning, operator-valued kernels provide a flexible tool to build vector-valued functions in the context of Reproducing Kernel Hilbert Spaces. To scale up these methods, we extend the…

Machine Learning · Computer Science 2018-05-25 Romain Brault , Florence d'Alché-Buc , Markus Heinonen