Concept

Uncorrelatedness (probability theory)

Publications associées (12)

RANDOMIZED JOINT DIAGONALIZATION OF SYMMETRIC

Given a family of nearly commuting symmetric matrices, we consider the task of computing an orthogonal matrix that nearly diagonalizes every matrix in the family. In this paper, we propose and analyze randomized joint diagonalization (RJD) for performing t ...

Philadelphia2024

Information Spectrum Converse for Minimum Entropy Couplings and Functional Representations

Given two jointly distributed random variables (X,Y), a functional representation of X is a random variable Z independent of Y, and a deterministic function g(⋅,⋅) such that X=g(Y,Z). The problem of finding a minimum entropy functional representation is kn ...

2023

Positive Definite Completions and Continuous Graphical Models

Kartik Waghmare

This thesis concerns the theory of positive-definite completions and its mutually beneficial connections to the statistics of function-valued or continuously-indexed random processes, better known as functional data analysis. In particular, it dwells upon ...

EPFL2023

Small-scale dynamo with finite correlation times

Fluctuation dynamos occur in most turbulent plasmas in astrophysics and are the prime candidates for amplifying and maintaining cosmic magnetic fields. A few analytical models exist to describe their behavior, but they are based on simplifying assumptions. ...

AMER PHYSICAL SOC2023

Discrete Optimal Transport with Independent Marginals is #P-Hard

Daniel Kuhn, Soroosh Shafieezadeh Abadeh, Bahar Taskesen

We study the computational complexity of the optimal transport problem that evaluates the Wasser- stein distance between the distributions of two K-dimensional discrete random vectors. The best known algorithms for this problem run in polynomial time in th ...

2022

On Vacuous and Non-Vacuous Generalization Bounds for Deep Neural Networks.

Konstantinos Pitas

Deep neural networks have been empirically successful in a variety of tasks, however their theoretical understanding is still poor. In particular, modern deep neural networks have many more parameters than training data. Thus, in principle they should over ...

EPFL2020

On Polynomial Lieb–Robinson Bounds for the XY Chain in a Decaying Random Field

Marius Christopher Lemm

We consider the isotropic XY quantum spin chain in a random external field in the z direction, with single site distributions given by i.i.d. random variables times the critical decaying envelope j−1/2. Our motivation is the study of many-body localization ...

2016

Inhomogeneity of charge-density-wave order and quenched disorder in a high-T-c superconductor

Janusz Andrzej Karpinski, Davide Innocenti

It has recently been established that the high-transition-temperature (high-T-c) superconducting state coexists with short-range charge-density-wave order(1-11) and quenched disorder(12,13) arising from dopants and strain(14-17). This complex, multiscale p ...

Nature Publishing Group2015

A New Entropy Power Inequality for Integer-Valued Random Variables

Emmanuel Abbé, Saeid Haghighatshoar

The entropy power inequality (EPI) yields lower bounds on the differential entropy of the sum of two independent real-valued random variables in terms of the individual entropies. Versions of the EPI for discrete random variables have been obtained for spe ...

Institute of Electrical and Electronics Engineers2014

Lyapunov Exponents of Random Walks in Small Random Potential: The Lower Bound

Thomas Mountford, Jean-Christophe Mourrat

We consider the simple random walk on , d > 3, evolving in a potential of the form beta V, where are i.i.d. random variables taking values in [0, + a), and beta > 0. When the potential is integrable, the asymptotic behaviours as beta tends to 0 of the asso ...

Springer Berlin Heidelberg2013

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