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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 apply a probabilistic approach to study the computational complexity of analog computers which solve linear programming problems. We analyze numerically various ensembles of linear programming problems and obtain, for each of these…

Other Condensed Matter · Physics 2009-11-11 Yaniv Avizrats , Joshua Feinberg , Shmuel Fishman

We study unitary random matrix ensembles in the critical regime where a new cut arises away from the original spectrum. We perform a double scaling limit where the size of the matrices tends to infinity, but in such a way that only a…

Mathematical Physics · Physics 2007-11-19 Tom Claeys

The unitary group with the Haar probability measure is called Circular Unitary Ensemble. All the eigenvalues lie on the unit circle in the complex plane and they can be regarded as a determinantal point process on $\mathbb{S}^1$. It is also…

Probability · Mathematics 2022-03-16 Makoto Katori , Tomoyuki Shirai

We address the question of how the celebrated universality of local correlations for the real eigenvalues of Hermitian random matrices of size NxN can be extended to complex eigenvalues in the case of random matrices without symmetry.…

Mathematical Physics · Physics 2015-04-20 G. Akemann , M. J. Phillips

Simulation models of complex dynamics in the natural and social sciences commonly lack a tractable likelihood function, rendering traditional likelihood-based statistical inference impossible. Recent advances in machine learning have…

Machine Learning · Statistics 2022-02-24 Joel Dyer , Patrick Cannon , Sebastian M Schmon

We consider collections of $N$ chordal random curves obtained from a critical lattice model on a planar graph, in the limit when a fine-mesh graph approximates a simply-connected domain. We define and study candidates for such limits in…

Mathematical Physics · Physics 2019-03-26 Alex Karrila

The signature transform, defined by the formal tensor series of global iterated path integrals, is a homomorphism between the path space and the tensor algebra that has been studied in geometry, control theory, number theory as well as…

Classical Analysis and ODEs · Mathematics 2022-11-09 Horatio Boedihardjo , Xi Geng

Tensor algebras give rise to one of the most powerful measures of similarity for sequences of arbitrary length called the signature kernel accompanied with attractive theoretical guarantees from stochastic analysis. Previous algorithms to…

Machine Learning · Statistics 2024-11-25 Csaba Toth , Harald Oberhauser , Zoltan Szabo

We establish a universal approximation theorem for signatures of rough paths that are not necessarily weakly geometric. By extending the path with time and its rough path bracket terms, we prove that linear functionals of the signature of…

Probability · Mathematics 2026-02-06 Mihriban Ceylan , Anna P. Kwossek , David J. Prömel

The signature kernel is a recent state-of-the-art tool for analyzing high-dimensional sequential data, valued for its theoretical guarantees and strong empirical performance. In this paper, we present a novel method for efficiently…

Numerical Analysis · Mathematics 2025-11-12 Matthew Tamayo-Rios , Alexander Schell , Rima Alaifari

The paper studies scaling limits of random skew plane partitions confined to a box when the inner shapes converge uniformly to a piecewise linear function V of arbitrary slopes in [-1,1]. It is shown that the correlation kernels in the bulk…

Mathematical Physics · Physics 2011-10-21 Sevak Mkrtchyan

We consider learning on graphs, guided by kernels that encode similarity between vertices. Our focus is on random walk kernels, the analogues of squared exponential kernels in Euclidean spaces. We show that on large, locally treelike,…

Machine Learning · Statistics 2013-10-01 Matthew Urry , Peter Sollich

We show that kernel-based quadrature rules for computing integrals can be seen as a special case of random feature expansions for positive definite kernels, for a particular decomposition that always exists for such kernels. We provide a…

Machine Learning · Computer Science 2015-11-10 Francis Bach

A meandric system of size $n$ is the set of loops formed from two arc diagrams (non-crossing perfect matchings) on $\{1,\dots,2n\}$, one drawn above the real line and the other below the real line. A uniform random meandric system can be…

Probability · Mathematics 2023-09-28 Jacopo Borga , Ewain Gwynne , Minjae Park

We consider line ensembles of non-intersecting random walks constrained by a hard wall, each tilted by the area underneath it with geometrically growing pre-factors $\mathfrak{b}^i$ where $\mathfrak{b}>1$. This is a model for the level…

Probability · Mathematics 2023-10-31 Christian Serio

We investigate the spectral properties of the product of $M$ complex non-Hermitian random matrices that are obtained by removing $L$ rows and columns of larger unitary random matrices uniformly distributed on the group ${\rm U}(N+L)$. Such…

Mathematical Physics · Physics 2014-06-10 Gernot Akemann , Zdzislaw Burda , Mario Kieburg , Taro Nagao

A combination of direct and inverse Fourier transforms on the unitary group $U(N)$ identifies normalized characters with probability measures on $N$-tuples of integers. We develop the $N\to\infty$ version of this correspondence by matching…

Probability · Mathematics 2019-12-19 Alexey Bufetov , Vadim Gorin

We propose new estimates for the frontier of a set of points. They are defined as kernel estimates covering all the points and whose associated support is of smallest surface. The estimates are written as linear combinatio- ns of kernel…

Methodology · Statistics 2011-03-31 Guillaume Bouchard , Stéphane Girard , Anatoli Iouditski , Alexander Nazin

A random geometric graph (RGG) with kernel $K$ is constructed by first sampling latent points $x_1,\ldots,x_n$ independently and uniformly from the $d$-dimensional unit sphere, then connecting each pair $(i,j)$ with probability $K(\langle…

Probability · Mathematics 2026-02-17 Cheng Mao , Yihong Wu , Jiaming Xu