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We present a distributed (non-Bayesian) learning algorithm for the problem of parameter estimation with Gaussian noise. The algorithm is expressed as explicit updates on the parameters of the Gaussian beliefs (i.e. means and precision). We…

Optimization and Control · Mathematics 2016-12-08 Angelia Nedić , Alex Olshevsky , César A. Uribe

We consider the scattering by a one-dimensional random potential and derive the probability distribution of the corresponding Wigner time delay. It is shown that the limiting distribution is the same for two different models and coincides…

Disordered Systems and Neural Networks · Physics 2009-10-30 Alain Comtet , Christophe Texier

In this paper we examine a control variate estimator for a quantity that can be expressed as the expectation of a functional of a random process, that is itself the solution of a differential equation driven by fast mean-reverting ergodic…

Probability · Mathematics 2020-08-10 Josselin Garnier , Laurent Mertz

We consider transport properties of the chaotic (strange) attractor along unfolded trajectories of the dissipative standard map. It is shown that the diffusion process is normal except of the cases when a control parameter is close to some…

Chaotic Dynamics · Physics 2009-11-13 G. M. Zaslavsky , M. Edelman

Although time-dependent random media with short range correlations lead to (possibly biased) normal tracer diffusion, anomalous fluctuations occur away from the most probable direction. This was pointed out recently in 1D lattice random…

Disordered Systems and Neural Networks · Physics 2017-07-19 Pierre Le Doussal , Thimothée Thiery

We study a reaction-diffusion-convection problem with nonlinear drift posed in a domain with periodically arranged obstacles. The non-linearity in the drift is linked to the hydrodynamic limit of a totally asymmetric simple exclusion…

Analysis of PDEs · Mathematics 2022-04-05 Vishnu Raveendran , Emilio N. M. Cirillo , Adrian Muntean

Distributional regression aims at estimating the conditional distribution of a targetvariable given explanatory co-variates. It is a crucial tool for forecasting whena precise uncertainty quantification is required. A popular methodology…

Statistics Theory · Mathematics 2024-11-22 Clément Dombry , Ahmed Zaoui

Variance reduction is a family of powerful mechanisms for stochastic optimization that appears to be helpful in many machine learning tasks. It is based on estimating the exact gradient with some recursive sequences. Previously, many papers…

Optimization and Control · Mathematics 2025-11-07 Aleksandr Shestakov , Valery Parfenov , Aleksandr Beznosikov

The generalised extreme value (GEV) distribution is a three parameter family that describes the asymptotic behaviour of properly renormalised maxima of a sequence of independent and identically distributed random variables. If the shape…

Applications · Statistics 2022-05-10 Daniela Castro-Camilo , Raphaël Huser , Håvard Rue

What happens when a continuously evolving stochastic process is interrupted with large changes at random intervals $\tau$ distributed as a power-law $\sim \tau^{-(1+\alpha)};\alpha>0$? Modeling the stochastic process by diffusion and the…

Statistical Mechanics · Physics 2016-06-22 Apoorva Nagar , Shamik Gupta

The classical Birkhoff ergodic theorem in its most popular version says that the time average along a single typical trajectory of a dynamical system is equal to the space average with respect to the ergodic invariant distribution. This…

Dynamical Systems · Mathematics 2017-12-06 Michael Blank

The Generalized Central Limit Theorem is a remarkable generalization of the Central Limit Theorem, showing that the sum of a large number of independent, identically-distributed (i.i.d) random variables with infinite variance may converge…

Statistical Mechanics · Physics 2020-02-19 Ariel Amir

Logistic regression involving high-dimensional covariates is a practically important problem. Often the goal is variable selection, i.e., determining which few of the many covariates are associated with the binary response. Unfortunately,…

Computation · Statistics 2025-02-18 Yiqi Tang , Ryan Martin

This short note shows a limiting behavior of integrals of some centered antipersistent stationary infinitely divisible moving averages as the compact integration domain in $d\ge 1$ dimensions extends to the whole positive quadrant…

Probability · Mathematics 2024-07-10 Evgeny Spodarev

Generative AutoEncoders require a chosen probability distribution in latent space, usually multivariate Gaussian. The original Variational AutoEncoder (VAE) uses randomness in encoder - causing problematic distortion, and overlaps in latent…

Machine Learning · Computer Science 2019-01-15 Jarek Duda

It has been conjectured that transport in integrable one-dimensional (1D) systems is necessarily ballistic. The large diffusive response seen experimentally in nearly ideal realizations of the S=1/2 1D Heisenberg model is therefore puzzling…

Strongly Correlated Electrons · Physics 2010-12-01 J. Sirker , R. G. Pereira , I. Affleck

In an indirect Gaussian sequence space model lower and upper bounds are derived for the concentration rate of the posterior distribution of the parameter of interest shrinking to the parameter value $\theta^\circ$ that generates the data.…

Statistics Theory · Mathematics 2015-02-03 Jan Johannes , Anna Simoni , Rudolf Schenk

In this paper we investigate deterministic diffusion in systems which are spatially extended in certain directions but are restricted in size and open in other directions, consequently particles can escape. We introduce besides the…

chao-dyn · Physics 2016-08-31 Z. Kaufmann , H. Lustfeld , A. Nemeth , P. Szepfalusy

The complex spatiotemporal patterns of atmospheric flows resulting from the cooperative existence of fluctuations ranging in size from millimeters to thousands of kilometers are found to exhibit long-range spatial and temporal correlations…

General Physics · Physics 2016-11-17 A. Mary Selvam

The Barab\'asi's priority queuing model [A.-L. Barab\'asi, Nature \textbf{435}, 207 (2005)] and its variants have been extensively studied to understand heavy-tailed distributions of the inter-event times and the response times observed in…

Physics and Society · Physics 2021-11-16 Hang-Hyun Jo
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