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Kernel methods are an extremely popular set of techniques used for many important machine learning and data analysis applications. In addition to having good practical performances, these methods are supported by a well-developed theory.…

Machine Learning · Statistics 2015-04-23 Shiva Prasad Kasiviswanathan , Mark Rudelson

Analyzing the structure of sampled features from an input data distribution is challenging when constrained by limited measurements in both the number of inputs and features. Traditional approaches often rely on the eigenvalue spectrum of…

Machine Learning · Computer Science 2025-02-11 Chanwoo Chun , SueYeon Chung , Daniel D. Lee

The spectral fluctuations of complex quantum systems, in appropriate limit, are known to be consistent with that obtained from random matrices. However, this relation between the spectral fluctuations of physical systems and random matrices…

Quantum Physics · Physics 2020-09-16 S. Harshini Tekur , M. S. Santhanam

This paper is concerned with the spectral properties of matrices associated with linear filters for the estimation of the underlying trend of a time series. The interest lies in the fact that the eigenvectors can be interpreted as the…

Statistics Theory · Mathematics 2008-12-18 Alessandra Luati , Tommaso Proietti

This study explores the relationship between hypergraph automorphisms and the spectral properties of matrices associated with hypergraphs. For an automorphism $f$, an \( f \)-compatible matrices capture aspects of the symmetry, represented…

Combinatorics · Mathematics 2024-05-03 Anirban Banerjee , Samiron Parui

In this review we summarise recent results for the complex eigenvalues and singular values of finite products of finite size random matrices, their correlation functions and asymptotic limits. The matrices in the product are taken from…

Mathematical Physics · Physics 2015-10-28 Gernot Akemann , Jesper R. Ipsen

Distance matrices are matrices whose elements are the relative distances between points located on a certain manifold. In all cases considered here all their eigenvalues except one are non-positive. When the points are uncorrelated and…

Chaotic Dynamics · Physics 2009-11-10 E. Bogomolny , O. Bohigas , C. Schmit

Off-diagonal upper bounds are established away from the diagonal for the Bergman kernels associated to high powers of holomorphic line bundles over compact complex manifolds, asymptotically as the power tends to infinity. The line bundle is…

Complex Variables · Mathematics 2013-08-02 Michael Christ

In this paper we consider strata of flat metrics coming from quadratic differentials (semi-translation structures) on surfaces of finite type. We provide a necessary and sufficient condition for a set of simple closed curves to be…

Geometric Topology · Mathematics 2013-11-28 Ser-Wei Fu

The existing research on spectral algorithms, applied within a Reproducing Kernel Hilbert Space (RKHS), has primarily focused on general kernel functions, often neglecting the inherent structure of the input feature space. Our paper…

Machine Learning · Statistics 2024-03-08 Weichun Xia , Lei Shi

Spectral properties of Toeplitz operators and their finite truncations have long been central in operator theory. In the finite dimensional, non-normal setting, the spectrum is notoriously unstable under perturbations. Random perturbations…

Probability · Mathematics 2025-09-17 Anirban Basak

We examine scattering properties of singular vertex of degree $n=2$ and $n=3$, taking advantage of a new form of representing the vertex boundary condition, which has been devised to approximate a singular vertex with finite potentials. We…

Quantum Physics · Physics 2009-12-25 Taksu Cheon , Pavel Exner , Ondrej Turek

We consider a non-relativistic quantum particle interacting with a singular potential supported by two parallel straight lines in the plane. We locate the essential spectrum under the hypothesis that the interaction asymptotically…

Spectral Theory · Mathematics 2014-06-12 Sylwia Kondej , David Krejcirik

Spectral singularities are spectral points that spoil the completeness of the eigenfunctions of certain non-Hermitian Hamiltonian operators. We identify spectral singularities of complex scattering potentials with the real energies at which…

Mathematical Physics · Physics 2010-11-24 Ali Mostafazadeh

We consider the hermitian random matrix model with external source and general polynomial potential, when the source has two distinct eigenvalues but is otherwise arbitrary. All such models studied so far have a common feature: an…

Mathematical Physics · Physics 2020-12-11 Andrei Martínez-Finkelshtein , Guilherme L. F. Silva

Computing eigenvalues of very large matrices is a critical task in many machine learning applications, including the evaluation of log-determinants, the trace of matrix functions, and other important metrics. As datasets continue to grow in…

Machine Learning · Statistics 2025-06-16 Siavash Ameli , Chris van der Heide , Liam Hodgkinson , Michael W. Mahoney

We study a class of integral functionals known as nonlocal perimeters, which, intuitively, express a weighted interaction between a set and its complement. The weight is provided by a positive kernel K, which might be singular. In the first…

Analysis of PDEs · Mathematics 2020-04-07 Judith Berendsen , Valerio Pagliari

We study the spectrum of unbounded J-self-adjoint block operator matrices. In particular, we prove enclosures for the spectrum, provide a sufficient condition for the spectrum being real and derive variational principles for certain real…

Spectral Theory · Mathematics 2017-03-27 Matthias Langer , Michael Strauss

We consider various asymptotic scaling limits $N\to\infty$ for the $2N$ complex eigenvalues of non-Hermitian random matrices in the symmetry class of the symplectic Ginibre ensemble. These are known to be integrable, forming Pfaffian point…

Probability · Mathematics 2022-01-26 Gernot Akemann , Sung-Soo Byun , Nam-Gyu Kang

We study spectral and scattering properties of a spinless quantum particle confined to an infinite planar layer with hard walls containing a finite number of point perturbations. A solvable character of the model follows from the explicit…

Mathematical Physics · Physics 2020-01-23 Pavel Exner , Katerina Nemcova