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Related papers: On group averaging for non-compact groups

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The relationship between mappings of sets and renormalization group transformations is established, and renormalization group invariants of such mappings are found. These results are valid both for continuous and discrete mappings and for…

Mathematical Physics · Physics 2007-05-23 Gennady N. Nikolaev

This paper is devoted to provide a theoretical underpinning for ensemble forecasting with rapid fluctuations in body forcing and in boundary conditions. Ensemble averaging principles are proved under suitable `mixing' conditions on random…

Probability · Mathematics 2012-07-26 Wei Wang , Jian Ren , Jinqiao Duan , Guowei He

Group imbalance has been a known problem in empirical risk minimization (ERM), where the achieved high average accuracy is accompanied by low accuracy in a minority group. Despite algorithmic efforts to improve the minority group accuracy,…

Machine Learning · Statistics 2024-03-20 Hongkang Li , Shuai Zhang , Yihua Zhang , Meng Wang , Sijia Liu , Pin-Yu Chen

We consider the averaging principle for deterministic or stochastic systems with a fast stochastic component (family of continuous-time Markov chains depending on the state of the system as a parameter). We show that, due to bifurcations in…

Probability · Mathematics 2020-02-25 Mark Freidlin , Leonid Koralov

Disaggregated evaluation is a central task in AI fairness assessment, where the goal is to measure an AI system's performance across different subgroups defined by combinations of demographic or other sensitive attributes. The standard…

Machine Learning · Computer Science 2024-05-15 Christine Herlihy , Kimberly Truong , Alexandra Chouldechova , Miroslav Dudik

We ask when a finite set of t-structures in a triangulated category can be `averaged' into one t-structure or, equivalently, when the extension closure of a finite set of aisles is again an aisle. There is a straightforward, positive answer…

Representation Theory · Mathematics 2012-09-25 Nathan Broomhead , David Pauksztello , David Ploog

Various uses of the renormalization group are examined.

High Energy Physics - Theory · Physics 2011-12-20 D. G. C. McKeon

Grouping structures arise naturally in many statistical modeling problems. Several methods have been proposed for variable selection that respect grouping structure in variables. Examples include the group LASSO and several concave group…

Statistics Theory · Mathematics 2013-01-07 Jian Huang , Patrick Breheny , Shuangge Ma

Non-adaptive group testing refers to the problem of inferring a sparse set of defectives from a larger population using the minimum number of simultaneous pooled tests. Recent positive results for noiseless group testing have motivated the…

Information Theory · Computer Science 2021-07-16 Gabriel Arpino , Nicolò Grometto , Afonso S. Bandeira

Group testing, a problem with diverse applications across multiple disciplines, traditionally assumes independence across nodes' states. Recent research, however, focuses on real-world scenarios that often involve correlations among nodes,…

Information Theory · Computer Science 2025-04-02 Hesam Nikpey , Saswati Sarkar , Shirin Saeedi Bidokhti

Using the damped pendulum system we introduce the averaging method to study the periodic solutions of a dynamical system with small perturbation. We provide sufficient conditions for the existence of periodic solutions with small amplitude…

Dynamical Systems · Mathematics 2014-05-20 Douglas Duarte Novaes

The renormalization group is not only a powerful method for describing universal properties of phase transitions but it is also useful for evaluating non- universal properties beyond mean-field theory. In this contribution we concentrate on…

Condensed Matter · Physics 2009-11-07 Gernot Alber , Georgios Metikas

We present an averaging process for sections of a torsor under a unipotent group. This process allows one to integrate local sections of such a torsor into a global simplicial section. The results of this paper have applications to…

Representation Theory · Mathematics 2007-05-23 Amnon Yekutieli

Estimating the generalization error (GE) of machine learning models is fundamental, with resampling methods being the most common approach. However, in non-standard settings, particularly those where observations are not independently and…

A method is described to probe high-scale physics in lower-energy experiments by employing sum rules in terms of renormalisation group invariants. The method is worked out in detail for the study of supersymmetry-breaking mechanisms in the…

High Energy Physics - Phenomenology · Physics 2012-11-06 Jamil Hetzel , Wim Beenakker

When averages of different experimental determinations of the same quantity are computed, each with statistical and systematic error components, then frequently the statistical and systematic components of the combined error are quoted…

Data Analysis, Statistics and Probability · Physics 2015-10-28 Jens Erler

The review presents general methods for treating complicated problems that cannot be solved exactly and whose solution encounters two major difficulties. First, there are no small parameters allowing for the safe use of perturbation theory…

High Energy Physics - Theory · Physics 2021-05-27 V. I. Yukalov

This talk is an overview of selected topics related to renormalization group flows and the phases of gauge theories.

High Energy Physics - Phenomenology · Physics 2007-05-23 Kenneth Intriligator

We give an introduction to renormalisation, focusing first on a pedagogical description of fundamental concepts of the procedure and its features, then we introduce the renormalisation group and its equations. We discuss then the case of…

High Energy Physics - Phenomenology · Physics 2026-05-21 Leonardo Di Giustino

Over the last several years, there has been a resurgence of interest in using non-perturbative approximation methods based on Wilson's continuous renormalization group. In this lecture, I review progress particularly in the past year,…

High Energy Physics - Theory · Physics 2007-05-23 Tim R. Morris