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We study the hole probability of Gaussian random entire functions. More specifically, we work with the flat model (the zero set of this function has a distribution which is invariant with respect to the plane isometries). A hole is the…

Complex Variables · Mathematics 2016-09-20 Alon Nishry

The estimation of a probability p from repeated Bernoulli trials is considered in this paper. A sequential approach is followed, using a simple stopping rule. A closed-form expression and an upper bound are obtained for the mean absolute…

Statistics Theory · Mathematics 2018-12-19 Luis Mendo

A Gaussian fluctuation formula is proved for linear statistics of complex random matrices in the case that the statistic is rotationally invariant. For a general linear statistic without this symmetry, Coulomb gas theory is used to predict…

Statistical Mechanics · Physics 2007-05-23 P. J. Forrester

Let N > n, and denote by K the convex hull of N independent standard gaussian random vectors in an n-dimensional Euclidean space. We prove that with high probability, the isotropic constant of K is bounded by a universal constant. Thus we…

Metric Geometry · Mathematics 2007-05-23 Bo'az Klartag , Gady Kozma

While deep learning offers powerful capabilities for scientific research, its application is often hindered by a lack of quantitative reliability. To address this, we introduce a probabilistic denoising framework that simultaneously…

Strongly Correlated Electrons · Physics 2026-05-11 Younsik Kim , Changyoung Kim

Polytope numbers for a polytope are a sequence of nonnegative integers that are defined by the facial information of a polytope. Every polygon is triangulable and a higher dimensional analogue of this fact states that every polytope is…

Combinatorics · Mathematics 2012-06-05 H. K. Kim , J. Y. Lee

We give an exact formula for the value of the derivative at zero of the gap probability in finite n x n Gaussian ensembles. As n goes to infinity our computation provides an asymptotic (with an explicit constant) of the order n^(1/2). As a…

Probability · Mathematics 2013-09-24 Antonio Lerario , Erik Lundberg

We study the hole probability of Gaussian random entire functions. More specifically, we work with entire functions in Taylor series form with i.i.d complex Gaussian coefficients. A hole is the event where the function has no zeros in a…

Complex Variables · Mathematics 2010-04-07 Alon Nishry

We establish central limit theorems for natural volumes of random inscribed polytopes in projective Riemannian or Finsler geometries. In addition, normal approximation of dual volumes and the mean width of random polyhedral sets are…

Metric Geometry · Mathematics 2020-05-22 Florian Besau , Daniel Rosen , Christoph Thäle

In classical random matrix theory the Gaussian and chiral Gaussian random matrix models with a source are realized as shifted mean Gaussian, and chiral Gaussian, random matrices with real $(\beta = 1)$, complex ($\beta = 2)$ and real…

Probability · Mathematics 2015-06-16 Peter J. Forrester

Explicit pointwise error bounds for the interpolation of a smooth function by piecewise exponential splines of order four are given. Estimates known for cubic splines are extended to a natural class of piecewise exponential splines which…

Numerical Analysis · Mathematics 2020-10-08 Ognyan Kounchev , Hermann Render

We study the geometry of centrally-symmetric random polytopes, generated by $N$ independent copies of a random vector $X$ taking values in $\mathbb{R}^n$. We show that under minimal assumptions on $X$, for $N \gtrsim n$ and with high…

Probability · Mathematics 2019-07-18 Olivier Guédon , Felix Krahmer , Christian Kümmerle , Shahar Mendelson , Holger Rauhut

Interpolation error estimates in terms of geometric quality measures are established for harmonic coordinates on polytopes in two and three dimensions. First we derive interpolation error estimates over convex polygons that depend on the…

Numerical Analysis · Mathematics 2015-10-06 Andrew Gillette , Alexander Rand

While Gaussian probability densities are omnipresent in applied mathematics, Gaussian cumulative probabilities are hard to calculate in any but the univariate case. We study the utility of Expectation Propagation (EP) as an approximate…

Machine Learning · Statistics 2013-12-02 John P. Cunningham , Philipp Hennig , Simon Lacoste-Julien

We study the expected volume of random polytopes generated by taking the convex hull of independent identically distributed points from a given distribution. We show that for log-concave distributions supported on convex bodies, we need at…

Metric Geometry · Mathematics 2021-11-16 Debsoumya Chakraborti , Tomasz Tkocz , Beatrice-Helen Vritsiou

The paper deals with the process of mathematical modeling representations of exponential and logarithmic functions hypercomplex number system of generalized quaternions via determining a linear differential equation with hypercomplex…

General Mathematics · Mathematics 2016-11-22 Yakiv O. Kalinovsky , Yuliya E. Boyarinova , Dmitry V. Lande , Alina S. Sukalo

Computation of the undetected error probability for error correcting codes over the Z-channel is an important issue, explored only in part in previous literature. In this paper we consider the case of Varshamov-Tenengol'ts codes, by…

Information Theory · Computer Science 2009-10-20 Marco Baldi , Franco Chiaraluce , Torleiv Kløve

We propose an open loop methodology based on sample statistics to solve chance constrained stochastic optimal control problems with probabilistic safety guarantees for linear systems where the additive Gaussian noise has unknown mean and…

Systems and Control · Electrical Eng. & Systems 2023-03-24 Shawn Priore , Meeko Oishi

Hardware distortions (HWD) render drastic effects on the performance of communication systems. They are recently proven to bear asymmetric signatures; and hence can be efficiently mitigated using improper Gaussian signaling (IGS), thanks to…

Signal Processing · Electrical Eng. & Systems 2020-09-14 Sidrah Javed , Ahmed Elzanaty , Osama Amin , Basem Shihada , Mohamed-Slim Alouini

Polyhedral estimate is a generic efficiently computable nonlinear in observations routine for recovering unknown signal belonging to a given convex compact set from noisy observation of signal's linear image. Risk analysis and optimal…

Statistics Theory · Mathematics 2022-12-26 Anatoli Juditsky , Arkadi Nemirovski
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