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Some variant of the Frank-Wolfe method for convex optimization problems with adaptive selection of the step parameter corresponding to information about the smoothness of the objective function (the Lipschitz constant of the gradient).…

Optimization and Control · Mathematics 2023-08-01 G. V. Aivazian , F. S. Stonyakin , D. A. Pasechnyuk , M. S. Alkousa , A. M. Raigorodskii

A Ginsparg-Wilson based calibration of the topological charge is used to calculate the renormalization constants which appear in the field-theoretical determination of the topological susceptibility on the lattice. A systematic comparison…

High Energy Physics - Lattice · Physics 2008-11-26 B. Alles , M. D'Elia , A. Di Giacomo , C. Pica

We investigate a local reparameterizaton technique for greatly reducing the variance of stochastic gradients for variational Bayesian inference (SGVB) of a posterior over model parameters, while retaining parallelizability. This local…

Machine Learning · Statistics 2015-12-22 Diederik P. Kingma , Tim Salimans , Max Welling

As a typical application, the Lenstra-Lenstra-Lovasz lattice basis reduction algorithm (LLL) is used to compute a reduced basis of the orthogonal lattice for a given integer matrix, via reducing a special kind of lattice bases. With such…

Symbolic Computation · Computer Science 2018-05-10 Jingwei Chen , Damien Stehlé , Gilles Villard

Suppressing monopoles and vortices by introducing large chemical potentials for them in the Wilson action for the SU(2) lattice gauge theory, we study the nature of the deconfinement phase transition on N_\sigma^3 \times N_\tau lattices for…

High Energy Physics - Lattice · Physics 2009-10-31 Rajiv V. Gavai

Many inequality relations between real vector quantities can be succinctly expressed as "weak (sub)majorization" relations. We explain these ideas and apply them in several areas: angles between subspaces, Ritz values, and graph Laplacian…

Numerical Analysis · Mathematics 2013-03-26 A. V. Knyazev , M. E. Argentati

There has been substantial progress in understanding confinement in a class of four-dimensional SU(N) gauge theories using semiclassical methods. These models have one or more compact directions, and much of the analysis is based on the…

High Energy Physics - Theory · Physics 2014-10-08 Michael C. Ogilvie

Applications of normalizing flows to the sampling of field configurations in lattice gauge theory have so far been explored almost exclusively in two space-time dimensions. We report new algorithmic developments of gauge-equivariant flow…

We propose a shrinkage procedure for simultaneous variable selection and estimation in generalized linear models (GLMs) with an explicit predictive motivation. The procedure estimates the coefficients by minimizing the Kullback-Leibler…

Methodology · Statistics 2010-09-14 Minh-Ngoc Tran , David Nott , Chenlei Leng

Symmetry provides powerful non-perturbative constraints in quantum many-body systems. A prominent example is the Lieb-Schultz-Mattis (LSM) anomaly -- a mixed 't Hooft anomaly between internal and translational symmetries that forbids a…

Strongly Correlated Electrons · Physics 2026-05-26 Tsubasa Oishi , Takuma Saito , Hiromi Ebisu

Liquid drops slide more slowly over soft, deformable substrates than over rigid solids. This phenomenon can be attributed to the viscoelastic dissipation induced by the moving wetting ridge, which inhibits a rapid motion, and is called…

Topological freezing is a well known problem in lattice simulations: with shrinking lattice spacing a transition between topological sectors becomes increasingly improbable, leading to a problematic increase of the autocorrelation time…

High Energy Physics - Lattice · Physics 2022-12-23 Christian Hoelbling , Timo Eichhorn , Philip Rouenhoff , Lukas Varnhorst

Real-life applications of deep neural networks are hindered by their unsteady predictions when faced with noisy inputs and adversarial attacks. The certified radius in this context is a crucial indicator of the robustness of models. However…

Machine Learning · Computer Science 2024-03-19 Blaise Delattre , Alexandre Araujo , Quentin Barthélemy , Alexandre Allauzen

General-purpose Markov Chain Monte Carlo sampling algorithms suffer from a dramatic reduction in efficiency as the system being studied is driven towards a critical point. Recently, a series of seminal studies suggested that normalizing…

High Energy Physics - Lattice · Physics 2021-11-24 Luigi Del Debbio , Joe Marsh Rossney , Michael Wilson

We implement the Wang-Landau algorithm in the context of SU(N) lattice gauge theories. We study the quenched, reduced version of the lattice theory and calculate its density of states for N=20,30,40,50. We introduce a variant of the…

High Energy Physics - Lattice · Physics 2008-11-26 Barak Bringoltz , Stephen R. Sharpe

Fluid-structure interaction models involve parameters that describe the solid and the fluid behavior. In simulations, there often is a need to vary these parameters to examine the behavior of a fluid-structure interaction model for…

Numerical Analysis · Mathematics 2020-04-24 Roman Weinhandl , Peter Benner , Thomas Richter

We introduce a novel model order reduction method for large-scale linear switched systems (LSS) where the coefficient matrices are affected by a low-rank switching. The key idea is to replace the LSS by a non-switched system with extended…

Systems and Control · Computer Science 2018-12-21 Philipp Schulze , Benjamin Unger

We study the approximability of multiway partitioning problems, examples of which include Multiway Cut, Node-weighted Multiway Cut, and Hypergraph Multiway Cut. We investigate these problems from the point of view of two possible…

Data Structures and Algorithms · Computer Science 2015-03-16 Alina Ene , Jan Vondrak , Yi Wu

The shear-transformation-zone (STZ) theory has been remarkably successful in accounting for broadly peaked, frequency-dependent, viscoelastic responses of amorphous systems near their glass temperatures $T_g$. This success is based on the…

Statistical Mechanics · Physics 2012-02-02 J. S. Langer

We consider smooth convex minimization over compact convex sets, i.e., $\min_{x \in C} f(x)$ with the (vanilla) Frank-Wolfe algorithm. Well-known lower bounds establish a worst-case $\Omega(1/t)$ primal-gap barrier in the general smooth…

Optimization and Control · Mathematics 2026-05-05 Sebastian Pokutta