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In this paper, we examine the problem of approximating a general linear dimensionality reduction (LDR) operator, represented as a matrix $A \in \mathbb{R}^{m \times n}$ with $m < n$, by a partial circulant matrix with rows related by…

Machine Learning · Statistics 2015-02-26 Swayambhoo Jain , Jarvis Haupt

Derrida et al. and Sch\"{u}tz and Stinchcombe gave algebraic formulas for the correlation functions of the partially asymmetric simple exclusion process. Here we give a fairly general recipe of how to get these formulas and extend them to…

Statistical Mechanics · Physics 2007-05-23 Luca De Sanctis , Marco Isopi

Efficient recovery of a low-dimensional structure from high-dimensional data has been pursued in various settings including wavelet denoising, generalized linear models and low-rank matrix estimation. By thresholding some parameters to…

Methodology · Statistics 2017-08-14 Caroline Giacobino , Sylvain Sardy , Jairo Diaz-Rodriguez , Nick Hengartner

We report a numerical analysis of corrections to finite size scaling at the Anderson transition due to irrelevant scaling variables and non-linearities of the scaling variables. By taking proper account of these corrections, the…

Disordered Systems and Neural Networks · Physics 2009-10-31 Keith Slevin , Tomi Ohtsuki

We study the asymptotic behaviour of solutions of Forward Backward Stochastic Differential Equations in the coupled case, when the diffusion coefficient of the forward equation is multiplicatively perturbed by a small parameter that…

Probability · Mathematics 2013-02-27 Ana Bela Cruzeiro , André de Oliveira Gomes

We obtain error rates for large deviations of sums of i.i.d. random variables in, a particular case, of the domain of a non-symmetric infinite mean $\alpha=1$-stable law. The focus of this work is on the method of proof via analytic…

Probability · Mathematics 2025-06-17 Jonny Imbierski , Dalia Terhesiu

The difficulties arising in the investigation of finite-size scaling in $d$--dimensional O(n) systems with strong anisotropy and/or long-range interaction, decaying with the interparticle distance $r$ as $r^{-d-\sigma}$ ($0<\sigma\leq2$),…

Statistical Mechanics · Physics 2009-11-11 H. Chamati , N. S. Tonchev

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 consider the weakly asymmetric exclusion process on a bounded interval with particle reservoirs at the endpoints. The hydrodynamic limit for the empirical density, obtained in the diffusive scaling, is given by the viscous Burgers…

Probability · Mathematics 2009-12-14 Lorenzo Bertini , Claudio Landim , Mustapha Mourragui

The theory of stochastic approximations form the theoretical foundation for studying convergence properties of many popular recursive learning algorithms in statistics, machine learning and statistical physics. Large deviations for…

Probability · Mathematics 2025-02-05 Henrik Hult , Adam Lindhe , Pierre Nyquist , Guo-Jhen Wu

We establish the large deviation principle for solutions of one-dimensional SDEs with discontinuous coefficients. The main statement is formulated in a form similar to the classical Wentzel--Freidlin theorem, but under the considerably…

Probability · Mathematics 2016-07-14 Alexei Kulik , Daryna Sobolieva

The new ingredient of this paper is that we consider infinitely dimensional classes of functions and instead of the relative error setting, which was used in previous papers on norm discretization, we consider the absolute error setting. We…

Numerical Analysis · Mathematics 2018-12-20 Vladimir Temlyakov

Large deviation theory offers a powerful and general statistical framework to study the asymptotic dynamical properties of rare events. The application of the formalism to concrete experimental situations is, however, often restricted by…

Statistical Mechanics · Physics 2023-09-13 Maxime Debiossac , Nikolai Kiesel , Eric Lutz

Outliers widely occur in big-data applications and may severely affect statistical estimation and inference. In this paper, a framework of outlier-resistant estimation is introduced to robustify an arbitrarily given loss function. It has a…

Methodology · Statistics 2023-04-20 Yiyuan She , Zhifeng Wang , Jiahui Shen

We consider the one-dimensional partially asymmetric exclusion process with random hopping rates, in which a fraction of particles (or sites) have a preferential jumping direction against the global drift. In this case the accumulated…

Disordered Systems and Neural Networks · Physics 2009-11-10 R. Juhasz , L. Santen , F. Igloi

Filtering and parameter estimation under partial information for multiscale problems is studied in this paper. After proving mean square convergence of the nonlinear filter to a filter of reduced dimension, we establish that the conditional…

Probability · Mathematics 2014-09-09 Andrew Papanicolaou , Konstantinos Spiliopoulos

The totally asymmetric simple exclusion process along with particle adsorption and evaporation kinetics is a model of boundary-induced nonequilibrium phase transition. In the continuum limit, the average particle density across the system…

Statistical Mechanics · Physics 2018-04-25 Sutapa Mukherji , Somendra M. Bhattacharjee

Phenomenological scaling arguments suggest the existence of universal amplitudes in the finite-size scaling of certain correlation lengths in strongly anisotropic or dynamical phase transitions. For equilibrium systems, provided that…

Statistical Mechanics · Physics 2008-11-26 Malte Henkel , Ulrich Schollwöck

We establish the (level-1) large deviation principles for three kinds of means associated with the backward continued fraction expansion. We show that: for the harmonic and geometric means, the rate functions vanish exactly at one point;…

Dynamical Systems · Mathematics 2019-12-30 Hiroki Takahasi

We consider the two-point function of the totally asymmetric simple exclusion process with stationary initial conditions. The two-point function can be expressed as the discrete Laplacian of the variance of the associated height function.…

Mathematical Physics · Physics 2014-04-24 Jinho Baik , Patrik L. Ferrari , Sandrine Péché
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