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This is a brief review, in relatively non-technical terms, of recent advances in the theory of random field geometry. These advances have provided a collection of explicit new formulae describing mean values of a variety of geometric…

Probability · Mathematics 2008-05-08 Robert J Adler

Randomized algorithms provide solutions to two ubiquitous problems: (1) the distributed calculation of a principal component analysis or singular value decomposition of a highly rectangular matrix, and (2) the distributed calculation of a…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-04-09 Huamin Li , Yuval Kluger , Mark Tygert

The purpose of this article is to propose a new method to define and calculate path integrals over metrics on a K\"ahler manifold. The main idea is to use finite dimensional spaces of Bergman metrics, as an approximation to the full space…

High Energy Physics - Theory · Physics 2013-01-15 Frank Ferrari , Semyon Klevtsov , Steve Zelditch

Outlier detection is a major topic in robust statistics due to the high practical significance of anomalous observations. Many existing methods are, however, either parametric or cease to perform well when the data is far from linearly…

Methodology · Statistics 2018-11-14 Matias Heikkilä

The RooUnfold package provides a common framework to evaluate and use different unfolding algorithms, side-by-side. It currently provides implementations or interfaces for the Iterative Bayes, Singular Value Decomposition, and TUnfold…

Data Analysis, Statistics and Probability · Physics 2011-12-09 Tim Adye

Topological measurements are increasingly being accepted as an important tool for quantifying complex structures. In many applications, these structures can be expressed as nodal domains of real-valued functions and are obtained only…

Probability · Mathematics 2020-05-29 Konstantin Mischaikow , Thomas Wanner

We describe a numerical framework that uses random sampling to efficiently capture low-rank local solution spaces of multiscale PDE problems arising in domain decomposition. In contrast to existing techniques, our method does not rely on…

Numerical Analysis · Mathematics 2020-02-06 Ke Chen , Qin Li , Jianfeng Lu , Stephen J. Wright

We present a symbolic-numeric approach for the analysis of a given set of noisy data, represented as a finite set $\X$ of limited precision points. Starting from $\X$ and a permitted tolerance $\varepsilon$ on its coordinates, our method…

Commutative Algebra · Mathematics 2012-02-20 Claudia Fassino , Maria-Laura Torrente

We consider the efficiency of multiplexing spatially encoded information across random configurations of a metasurface-programmable chaotic cavity in the microwave domain. The distribution of the effective rank of the channel matrix is…

Applied Physics · Physics 2020-08-05 Philipp del Hougne , Dmitry V. Savin , Olivier Legrand , Ulrich Kuhl

In this article we show how to compute a matrix representation and the implicit equation by means of the method developed in [Botbol: arXiv:1007.3437], using the computer algebra system Macaulay2 \cite{M2}. As it is probably the most…

Algebraic Geometry · Mathematics 2010-07-22 Nicolas Botbol

A number of numeric approaches to simulate Poisson point processes with arbitrary event rates are presented and implemented for R. They include the simulation of the number of points and their location as well as the determination of…

Probability · Mathematics 2019-05-21 Niklas Hohmann

In this paper, we give an elementary new method for determining the rational points on algebraic curves using torsion packets. We also provide examples of curves for which all rational points can be completely determined by our method.

Number Theory · Mathematics 2026-03-23 Ryo Ichikawa

A reliable and user-friendly characterisation of nano-objects in a target material is presented here in the form of a software data analysis package for interpreting small-angle X-ray scattering (SAXS) patterns. When provided with data on…

Data Analysis, Statistics and Probability · Physics 2014-12-08 Ingo Breßler , Brian R. Pauw , Andreas Thünemann

The spectra of random feature matrices provide essential information on the conditioning of the linear system used in random feature regression problems and are thus connected to the consistency and generalization of random feature models.…

Machine Learning · Statistics 2022-12-13 Zhijun Chen , Hayden Schaeffer , Rachel Ward

Randomized dimensionality reduction is a widely-used algorithmic technique for speeding up large-scale Euclidean optimization problems. In this paper, we study dimension reduction for a variety of maximization problems, including…

Data Structures and Algorithms · Computer Science 2025-06-03 Jie Gao , Rajesh Jayaram , Benedikt Kolbe , Shay Sapir , Chris Schwiegelshohn , Sandeep Silwal , Erik Waingarten

We introduce numerical algebraic geometry methods for computing lower bounds on the reach, local feature size, and the weak feature size of the real part of an equidimensional and smooth algebraic variety using the variety's defining…

Algebraic Geometry · Mathematics 2022-09-07 Sandra Di Rocco , Parker B. Edwards , David Eklund , Oliver Gäfvert , Jonathan D. Hauenstein

We develop algorithms for sampling from a probability distribution on a submanifold embedded in Rn. Applications are given to the evaluation of algorithms in 'Topological Statistics'; to goodness of fit tests in exponential families and to…

Statistics Theory · Mathematics 2012-07-06 Persi Diaconis , Susan Holmes , Mehrdad Shahshahani

The automation of the traditional Painleve test in Mathematica is discussed. The package PainleveTest.m allows for the testing of polynomial systems of ordinary and partial differential equations which may be parameterized by arbitrary…

Exactly Solvable and Integrable Systems · Physics 2013-01-08 Douglas Baldwin , Willy Hereman

Ensemble-based modifications of the well-known SHapley Additive exPlanations (SHAP) method for the local explanation of a black-box model are proposed. The modifications aim to simplify SHAP which is computationally expensive when there is…

Machine Learning · Computer Science 2021-03-08 Lev V. Utkin , Andrei V. Konstantinov

The $M_2$ variables are devised to extend $M_{T2}$ by promoting transverse masses to Lorentz-invariant ones and making explicit use of on-shell mass relations. Unlike simple kinematic variables such as the invariant mass of visible…

High Energy Physics - Phenomenology · Physics 2021-04-09 Chan Beom Park