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A new method to represent and approximate rotation matrices is introduced. The method represents approximations of a rotation matrix $Q$ with linearithmic complexity, i.e. with $\frac{1}{2}n\lg(n)$ rotations over pairs of coordinates,…

Machine Learning · Computer Science 2014-04-30 Michael Mathieu , Yann LeCun

We study elastic systems such as interfaces or lattices, pinned by quenched disorder. To escape triviality as a result of ``dimensional reduction'', we use the functional renormalization group. Difficulties arise in the calculation of the…

Condensed Matter · Physics 2009-07-10 Pierre Le Doussal , Kay Joerg Wiese , Pascal Chauve

Quasi-Newton (QN) methods provide an efficient alternative to second-order methods for minimizing smooth unconstrained problems. While QN methods generally compose a Hessian estimate based on one secant interpolation per iteration,…

Optimization and Control · Mathematics 2025-04-11 Mokhwa Lee , Yifan Sun

Since the advent of mesh-free methods as a tool for the numerical analysis of systems of Partial Differential Equations (PDEs), many variants of differential operator approximation have been proposed. In this work, we propose a local…

Numerical Analysis · Mathematics 2022-03-07 Mitja Jančič , Gregor Kosec

In Part I of this work, we have proposed a general framework of decentralized stochastic quasi-Newton methods, which converge linearly to the optimal solution under the assumption that the local Hessian inverse approximations have bounded…

Optimization and Control · Mathematics 2022-01-20 Jiaojiao Zhang , Huikang Liu , Anthony Man-Cho So , Qing Ling

In the second paper of this series we extend our Bayesian reanalysis of the evidence for a cosmic variation of the fine structure constant to the semi-parametric modelling regime. By adopting a mixture of Dirichlet processes prior for the…

Instrumentation and Methods for Astrophysics · Physics 2013-09-12 Ewan Cameron , Tony Pettitt

An alternative representation of the quasistatic nonradiative rates of Gersten and Nitzan [J. Chem. Phys. 1981, 75, 1139] and Ford and Weber [Phys. Rep. 1984, 113, 195] is derived for the respective parallel and perpendicular dipole…

Chemical Physics · Physics 2011-10-17 Alexander Moroz

Inflationary predictions for the power spectrum of the curvature perturbation have been verified to an excellent degree, leaving many models compatible with observations. In this thesis we studied third-order correlations, that might allow…

Cosmology and Nongalactic Astrophysics · Physics 2013-12-03 Eleftheria Tzavara

We show that the forward-jet measurements performed at HERA allow for a detailed study of corrections due to next-to-leading logarithms (NLL) in the Balitsky-Fadin-Kuraev-Lipatov (BFKL) approach. While the description of the d\sigma/dx data…

High Energy Physics - Phenomenology · Physics 2010-03-25 O. Kepka , C. Marquet , R. Peschanski , C. Royon

In this work, we numerically study the higher-ordered/extended Boussinesq system describing the propagation of water-waves over flat topography. A reformulation of the same order of precision that avoids the calculation of high order…

Analysis of PDEs · Mathematics 2022-07-04 Ralph Lteif , Stéphane Gerbi

We show that the perturbative expansion of the two-level correlation function, $R(\omega)$, in disordered conductors can be understood semiclassically in terms of self-intersecting particle trajectories. This requires the extension of the…

Mesoscale and Nanoscale Physics · Physics 2009-10-31 Robert A. Smith , Igor V. Lerner , Boris L. Altshuler

The accuracy of the electric field integral equation (EFIE) can be substantially improved using high-order discretizations. However, this equation suffers from ill-conditioning and deleterious numerical effects in the low-frequency regime,…

Numerical Analysis · Mathematics 2023-08-30 Johann Bourhis , Adrien Merlini , Francesco P. Andriulli

Point-mass filters solve Bayesian recursive relations by approximating probability density functions of a system state over grids of discrete points. The approach suffers from the curse of dimensionality. The exponential increase of the…

Signal Processing · Electrical Eng. & Systems 2025-06-09 Jiří Ajgl , Ondřej Straka

This paper shows how to obtain non-rigorous mathematical control over models of loosely coupled disordered grains; it provides new information about saddle point structure and perturbative corrections. Both the Wegner model and a variant…

Disordered Systems and Neural Networks · Physics 2009-06-02 Vincent E. Sacksteder

Large scale optimization problems are ubiquitous in machine learning and data analysis and there is a plethora of algorithms for solving such problems. Many of these algorithms employ sub-sampling, as a way to either speed up the…

Optimization and Control · Mathematics 2016-02-29 Farbod Roosta-Khorasani , Michael W. Mahoney

In this paper, we propose a novel data augmentation method for training neural networks for Direction of Arrival (DOA) estimation. This method focuses on expanding the representation of the DOA subspace of a dataset. Given some input data,…

Audio and Speech Processing · Electrical Eng. & Systems 2019-10-11 Luca Mazzon , Yuma Koizumi , Masahiro Yasuda , Noboru Harada

The phase spaces of the two- and three-frequency sine-Gordon models are examined in the framework of truncated conformal space approach. The focus is mainly on a tricritical point in the phase space of the three-frequency model. We give…

High Energy Physics - Theory · Physics 2009-11-10 Gabor Zsolt Toth

We use the semiclassical approach combined with the scaling results for the diffusion coefficient to consider the two-level correlation function $R(\varepsilon)$ for a disordered electron system in the crossover region, characterized by the…

Condensed Matter · Physics 2016-08-31 Arkady G. Aronov , Vladimir E. Kravtsov , Igor V. Lerner

We study Anderson localization in disordered helical conductors that are obtained from one-dimensional conductors with spin-orbit interaction and a magnetic field, or from equivalent systems. We call such conductors "quasi-helical" because…

Mesoscale and Nanoscale Physics · Physics 2013-03-05 Bernd Braunecker , Anders Ström , G. I. Japaridze

Second-order information is valuable for many applications but challenging to compute. Several works focus on computing or approximating Hessian diagonals, but even this simplification introduces significant additional costs compared to…

Machine Learning · Computer Science 2024-07-08 Mohamed Elsayed , Homayoon Farrahi , Felix Dangel , A. Rupam Mahmood
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