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Some eigenvalue matrix models possess an interesting property: one can manifestly define the basis where all averages can be explicitly calculated. For example, in the Gaussian Hermitian and rectangular complex models, averages of the Schur…

High Energy Physics - Theory · Physics 2025-07-04 A. Mironov , A. Morozov , Z. Zakirova

The time-evolving precision matrix of a piecewise-constant Gaussian graphical model encodes the dynamic conditional dependency structure of a multivariate time-series. Traditionally, graphical models are estimated under the assumption that…

Methodology · Statistics 2017-11-01 Alexander J. Gibberd , James D. B. Nelson

This paper focuses on the problem of separately modulating and jointly estimating two independent continuous-valued parameters sent over a Gaussian multiple-access channel (MAC) under the mean square error (MSE) criterion. To this end, we…

Information Theory · Computer Science 2016-09-28 Ayse Unsal , Raymond Knopp , Neri Merhav

Bayesian inference requires specification of a single, precise prior distribution, whereas frequentist inference only accommodates a vacuous prior. Since virtually every real-world application falls somewhere in between these two extremes,…

Methodology · Statistics 2023-09-26 Ryan Martin

We propose a rectangular rotational invariant estimator to recover a real matrix from noisy matrix observations coming from an arbitrary additive rotational invariant perturbation, in the large dimension limit. Using the Bayes-optimality of…

Information Theory · Computer Science 2023-04-25 Farzad Pourkamali , Nicolas Macris

Through refined asymptotic analysis based on the normal approximation, we study how higher-order coding performance depends on the mean power as well as on finer statistics of the input power. We introduce a multifaceted power model in…

Information Theory · Computer Science 2026-05-13 Adeel Mahmood , Aaron B. Wagner

This paper considers the quantification of the prediction performance in Gaussian process regression. The standard approach is to base the prediction error bars on the theoretical predictive variance, which is a lower bound on the mean…

Machine Learning · Statistics 2017-03-16 Johan Wågberg , Dave Zachariah , Thomas B. Schön , Petre Stoica

In this paper we consider the classical capacity problem for Gaussian measurement channels without imposing any kind of threshold condition. We prove Gaussianity of the average state of the optimal ensemble in general and discuss the…

Quantum Physics · Physics 2022-04-04 A. S. Holevo

We calculate Gaussian averages of arbitrary exponentials of the matrix variable $X$ with the help of superintegrability, which provides explicit expressions for Schur averages. As in the simpler cases the answer is expressed in terms of…

High Energy Physics - Theory · Physics 2026-03-31 A. Morozov

Gravitational-wave astronomers often wish to characterize the expected parameter-estimation accuracy of future observations. The Fisher matrix provides a lower bound on the spread of the maximum-likelihood estimator across noise…

General Relativity and Quantum Cosmology · Physics 2011-11-08 Michele Vallisneri

An integral over the interval $(0,\pi)$ is given for the cumulative distribution function of a sum of independent gamma random variables with different scale and shape parameters. The cumulative distribution function of a positive definite…

Probability · Mathematics 2024-12-18 Thomas Royen

In this work we focus on the general relay channel. We investigate the application of estimate-and-forward (EAF) to different scenarios. Specifically, we consider assignments of the auxiliary random variables that always satisfy the…

Information Theory · Computer Science 2007-07-13 R. Dabora , S. D. Servetto

This paper focuses on the analysis of average Gaussian error probabilities in certain fading channels, i.e. we are interested in E[Q((p {\gamma})^(1/2))] where Q(.) is the Gaussian Q-function, p is a positive real number and {\gamma} is a…

Information Theory · Computer Science 2011-03-03 Jose F. Paris

A statistical mechanical framework for analyzing random linear vector channels is presented in a large system limit. The framework is based on the assumptions that the left and right singular value bases of the rectangular channel matrix…

Information Theory · Computer Science 2008-02-21 Yoshiyuki Kabashima

This paper seeks an efficient algorithm for stochastic precoding to maximize the long-term average weighted sum rates throughout a multiple-input multiple-output (MIMO) network. Unlike many existing works that assume a particular…

Information Theory · Computer Science 2026-03-10 Wenyu Wang , Kaiming Shen

A distributional route to Gaussianity, associated with the concept of Conservative Mixing Transformations in ensembles of random vector-valued variables, is proposed. This route is completely different from the additive mechanism…

Statistical Mechanics · Physics 2023-01-11 Massimiliano Giona , Chiara Pezzotti , Giuseppe Procopio

We consider distributed estimation of the inverse covariance matrix, also called the concentration or precision matrix, in Gaussian graphical models. Traditional centralized estimation often requires global inference of the covariance…

Machine Learning · Statistics 2015-06-15 Zhaoshi Meng , Dennis Wei , Ami Wiesel , Alfred O. Hero

Holographic MIMO (hMIMO) systems with a massive number of individually controlled antennas N make minimum mean square error (MMSE) channel estimation particularly challenging, due to its computational complexity that scales as $N^3$ . This…

Information Theory · Computer Science 2023-12-19 Antonio Alberto D'Amico , Giacomo Bacci , Luca Sanguinetti

We give a hyperpfaffian formulation of partition functions and ensemble averages for Hermitian and circular ensembles when L is an arbitrary integer and \beta=L^2 and when L is an odd integer and \beta=L^2 +1.

Mathematical Physics · Physics 2010-08-27 Christopher D. Sinclair

The goal of this paper is to show that a single robust estimator of the mean of a multivariate Gaussian distribution can enjoy five desirable properties. First, it is computationally tractable in the sense that it can be computed in a time…

Statistics Theory · Mathematics 2022-10-28 Arnak S. Dalalyan , Arshak Minasyan
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