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In this paper, we demonstrate, both theoretically and by numerical examples, that adding a local prediction component to the update rule can significantly improve the convergence rate of distributed averaging algorithms. We focus on the…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-05-13 Boris N. Oreshkin , Mark J. Coates , Michael G. Rabbat

We present parton distribution functions which include a quantitative estimate of its uncertainties. The parton distribution functions are optimized with respect to deep inelastic proton data, expressing the uncertainties as a density…

High Energy Physics - Phenomenology · Physics 2007-05-23 Walter T. Giele , Stephane A. Keller , David A. Kosower

This work presents the first calculation in lattice QCD of three moments of spin-averaged and spin-polarized generalized parton distributions in the proton. It is shown that the slope of the associated generalized form factors decreases…

High Energy Physics - Lattice · Physics 2012-08-27 LHPC , SESAM Collaborations , : , Ph. Hagler , J. W. Negele , D. B. Renner , W. Schroers , Th. Lippert , K. Schilling

We derive expressions for the probability distribution of the ratio of two consecutive level spacings for the classical ensembles of random matrices. This ratio distribution was recently introduced to study spectral properties of many-body…

Mathematical Physics · Physics 2013-02-27 Y. Y. Atas , E. Bogomolny , O. Giraud , G. Roux

Consider a population of $N$ individuals, each having $d\geq 1$ different traits, and an additive measure, called dispersion, which rewards large pairwise separations between traits. The goal is to select $M\leq N$ individuals such that…

Statistical Mechanics · Physics 2026-05-01 Fabio Deelan Cunden , Noemi Cuppone , Giovanni Gramegna , Pierpaolo Vivo

Two new sum rules for the quark tensor charges of the nucleon are proposed, based on a relation connecting the quark transversity distributions to the quark helicity distributions and the quark model spin distributions, and on the sum rules…

High Energy Physics - Phenomenology · Physics 2009-10-30 Bo-Qiang Ma , Ivan Schmidt

Dual descent methods are commonly used to solve network optimization problems because their implementation can be distributed through the network. However, their convergence rates are typically very slow. This paper introduces a family of…

Optimization and Control · Mathematics 2011-04-07 M. Zargham , A. Ribeiro , A. Jadbabaie , A. Ozdaglar

Motivated by questions arising in the study of the spectral theory of models of aperiodic order, we investigate sums of functions of semibounded closed subsets of the real line. We show that under suitable thickness assumptions on the sets…

Classical Analysis and ODEs · Mathematics 2022-06-02 Jake Fillman , Sara H. Tidwell

The aim of the present work is to show that recent results of the authors on the approximation of distributions of sums of independent summands by the infinitely divisible laws on convex polyhedra can be shown via an alternative class of…

Probability · Mathematics 2022-08-04 Friedrich Götze , Andrei Yu. Zaitsev

We prove a limit theorem for the the maximal interpoint distance (also called the diameter) for a sample of n i.i.d. points in the unit ball of dimension 2 or more. The exact form of the limit distribution and the required normalisation are…

Probability · Mathematics 2007-05-23 Michael Mayer , Ilya Molchanov

This work studies nonconvex distributed constrained optimization over stochastic communication networks. We revisit the distributed dual averaging algorithm, which is known to converge for convex problems. We start from the centralized…

Optimization and Control · Mathematics 2022-11-15 Changxin Liu , Xuyang Wu , Xinlei Yi , Yang Shi , Karl H. Johansson

Motivated by a novel method for granular segregation, we analyze the one dimensional drift-diffusion between two absorbing boundaries. The time evolution of the probability distribution and the rate of absorption are given by explicit…

Statistical Mechanics · Physics 2009-10-31 Zeno Farkas , Tamas Fulop

We theoretically determine the probability distribution function of the net field of the random planar structure of dipoles which represent polarized particles. At small surface concentrations c of the point dipoles this distribution is…

Statistical Mechanics · Physics 2012-05-04 Andrey V. Panov

We show that, when the double bootstrap is used to improve performance of bootstrap methods for bias correction, techniques based on using a single double-bootstrap sample for each single-bootstrap sample can be particularly effective. In…

Statistics Theory · Mathematics 2015-11-12 Jinyuan Chang , Peter Hall

This talk brings attention to what is knowable from perturbative QCD theory on two-parton distribution functions in the light of CDF measuruments of the inclusive cross section for double parton scattering.

High Energy Physics - Phenomenology · Physics 2008-09-26 A. M. Snigirev

We clarify conflicting results in the literature on coefficient functions in front of higher twist operators contributing to the parton sum rules for deep inelastic scattering from polarized targets. The necessary corrections do not affect…

High Energy Physics - Phenomenology · Physics 2009-10-22 I. I. Balitsky , V. M. Braun , A. V. Kolesnichenko

In high-dimensional statistical inference, sparsity regularizations have shown advantages in consistency and convergence rates for coefficient estimation. We consider a generalized version of Sparse-Group Lasso which captures both…

Machine Learning · Statistics 2020-08-12 Xinyu Zhang

The improved calculation method of quark distributions in hadrons in the framework of QCD sum rules is presented. The imaginary part of the virtual photon scattering amplitude on some hadronic current is considered in the case, when initial…

High Energy Physics - Phenomenology · Physics 2007-05-23 B. L. Ioffe

Overparametrized models can exhibit an excellent generalization performance, although they should be prone to overfitting according to classical statistical theory. The discovery of the "double descent", indicating that the generalization…

Machine Learning · Computer Science 2026-05-22 Tino Werner

Various bias-correction methods such as EXTRA, gradient tracking methods, and exact diffusion have been proposed recently to solve distributed {\em deterministic} optimization problems. These methods employ constant step-sizes and converge…

Machine Learning · Computer Science 2023-07-19 Kun Yuan , Sulaiman A. Alghunaim , Bicheng Ying , Ali H. Sayed