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Calibration weighting is a fundamental technique in survey sampling and data integration for incorporating auxiliary information and improving efficiency of estimators. Classical calibration methods are typically formulated through distance…

Methodology · Statistics 2026-03-24 Jae Kwang Kim , Yonghyun Kwon , Yumou Qiu

We consider a countably generated and uniformly closed algebra of bounded functions. We assume that there is a lower semicontinuous, with respect to the supremum norm, quadratic form and that normal contractions operate in a certain sense.…

Functional Analysis · Mathematics 2018-06-29 Michael Hinz , Alexander Teplyaev

The random XORSAT problem deals with large random linear systems of Boolean variables. The difficulty of such problems is controlled by the ratio of number of equations to number of variables. It is known that in some range of values of…

Disordered Systems and Neural Networks · Physics 2016-08-16 Thierry Mora , Marc Mézard

We formulate em algorithm in the framework of Bregman divergence, which is a general problem setting of information geometry. That is, we address the minimization problem of the Bregman divergence between an exponential subfamily and a…

Information Theory · Computer Science 2024-09-10 Masahito Hayashi

Clustering categorical distributions in the finite-dimensional probability simplex is a fundamental task met in many applications dealing with normalized histograms. Traditionally, the differential-geometric structures of the probability…

Machine Learning · Computer Science 2021-11-22 Frank Nielsen , Ke Sun

In this paper, we generalize the simple Euclidean 1-center approximation algorithm of Badoiu and Clarkson (2003) to Riemannian geometries and study accordingly the convergence rate. We then show how to instantiate this generic algorithm to…

Computational Geometry · Computer Science 2021-04-29 Marc Arnaudon , Frank Nielsen

In this paper, we study the strong consistency of the sparse K-means clustering for high dimensional data. We prove the consistency in both risk and clustering for the Euclidean distance. We discuss the characterization of the limit of the…

Statistics Theory · Mathematics 2025-04-15 Jeungju Kim , Johan Lim

Associated to any finite metric space are a large number of objects and quantities which provide some degree of structural or geometric information about the space. In this paper we show that in the setting of subsets of weighted Hamming…

Functional Analysis · Mathematics 2024-09-19 Ian Doust , Anthony Weston

This paper introduces a new quantization scheme for real and complex Grassmannian sources. The proposed approach relies on a structured codebook based on a geometric construction of a collection of bent grids defined from an initial mesh on…

Information Theory · Computer Science 2016-10-27 Alexis Decurninge , Maxime Guillaud

Many data analysis problems can be cast as distance geometry problems in \emph{space forms} -- Euclidean, spherical, or hyperbolic spaces. Often, absolute distance measurements are often unreliable or simply unavailable and only proxies to…

Machine Learning · Computer Science 2021-07-30 Puoya Tabaghi , Jianhao Peng , Olgica Milenkovic , Ivan Dokmanić

We describe how to approximate the Riemann curvature tensor as well as sectional curvatures on possibly infinite-dimensional shape spaces that can be thought of as Riemannian manifolds. To this end, we extend the variational time…

Numerical Analysis · Mathematics 2019-12-17 Alexander Effland , Behrend Heeren , Martin Rumpf , Benedikt Wirth

Upon a consistent topological statistical theory the application of structural statistics requires a quantification of the proximity structure of model spaces. An important tool to study these structures are Pseudo-Riemannian metrices,…

Statistics Theory · Mathematics 2020-06-23 Patrick Michl

We classify (up to quasi-isomorphism) the free differential modules whose homology is equal to a given module $M$ by developing a theory for deforming an arbitrary free complex into a differential module. We use an iterative approach to…

Commutative Algebra · Mathematics 2023-08-07 Maya Banks , Keller VandeBogert

Every isometry of a finite dimensional euclidean space is a product of reflections and the minimum length of a reflection factorization defines a metric on its full isometry group. In this article we identify the structure of intervals in…

Group Theory · Mathematics 2013-12-31 Noel Brady , Jon McCammond

We propose a novel approach to the problem of multilevel clustering, which aims to simultaneously partition data in each group and discover grouping patterns among groups in a potentially large hierarchically structured corpus of data. Our…

Machine Learning · Statistics 2021-05-26 Viet Huynh , Nhat Ho , Nhan Dam , XuanLong Nguyen , Mikhail Yurochkin , Hung Bui , and Dinh Phung

We provide quantitative and abstract strong convergence results for sequences from a compact metric space satisfying a certain form of \emph{generalized Fej\'er monotonicity} where (1) the metric can be replaced by a much more general type…

Functional Analysis · Mathematics 2025-07-15 Nicholas Pischke

A codeword is associated to a linearized polynomial. The weight distribution of the codewords is determined as the linearized polynomial varies in a family of fixed degree. There is a corresponding result on Wenger graphs from linearized…

Information Theory · Computer Science 2015-02-17 Haode Yan , Chunlei Liu

On a smooth connected manifold, we consider all possible locally elliptic and locally bounded measurable coefficient Riemannian metrics called rough Riemannian metrics. We equip this set with an extended metric which is connected if and…

Differential Geometry · Mathematics 2025-07-15 Lashi Bandara , Anisa Hassan

A discretisation of differential geometry using the Whitney forms of algebraic topology is consistently extended via the introduction of a pairing on the space of chains. This pairing of chains enables us to give a definition of the…

High Energy Physics - Theory · Physics 2007-05-23 Vivien de Beauce , Siddhartha Sen

The proof of the theorem, which states that the Euclidean metric on the set of random points in an $n$-dimensional Euclidean space with the distribution of a special class, converges in probability in the limit $n\rightarrow\infty$ to the…

Mathematical Physics · Physics 2014-04-22 Alexander P. Zubarev