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We study the following fundamental hypothesis testing problem, which we term Gaussian mean testing. Given i.i.d. samples from a distribution $p$ on $\mathbb{R}^d$, the task is to distinguish, with high probability, between the following…

Statistics Theory · Mathematics 2022-10-26 Ilias Diakonikolas , Daniel M. Kane , Ankit Pensia

We study Bayesian estimation of finite mixture models in a general setup where the number of components is unknown and allowed to grow with the sample size. An assumption on growing number of components is a natural one as the degree of…

Statistics Theory · Mathematics 2022-03-18 Ilsang Ohn , Lizhen Lin

We study all five-, six-, and one eight-vertex type two-state solutions of the Yang-Baxter equations in the form $A_{12} B_{13} C_{23} = C_{23} B_{13} A_{12}$, and analyze the interplay of the `gauge' and `inversion' symmetries of these…

q-alg · Mathematics 2023-06-22 J. Hietarinta , C. Viallet

We study the problem of estimability of means in undirected graphical Gaussian models with symmetry restrictions represented by a colored graph. Following on from previous studies, we partition the variables into sets of vertices whose…

Statistics Theory · Mathematics 2012-07-24 Helene Gehrmann , Steffen L. Lauritzen

Praeger-Xu graphs are connected, symmetric, 4-regular graphs that are unusual both in that their automorphism groups are large, and in that vertex stabilizer subgroups are also large. Determining number and distinguishing number are…

Combinatorics · Mathematics 2023-09-21 Sally Cockburn , Max Klivans

We solve a class of isoperimetric problems on $\mathbb{R}^2_+ :=\left\{ (x,y)\in \mathbb{R} ^2 : y>0 \right\}$ with respect to monomial weights. Let $\alpha $ and $\beta $ be real numbers such that $0\le \alpha <\beta+1$, $\beta\le 2…

Analysis of PDEs · Mathematics 2019-07-09 Angelo Alvino , Friedemann Brock , Francesco Chiacchio , Anna Mercaldo , Maria Rosaria Posteraro

Gaussian mixture models (GMMs) are ubiquitous in statistical learning, particularly for unsupervised problems. While full GMMs suffer from the overparameterization of their covariance matrices in high-dimensional spaces, spherical GMMs…

Machine Learning · Statistics 2025-11-10 Tom Szwagier , Pierre-Alexandre Mattei , Charles Bouveyron , Xavier Pennec

A mixture of variance-gamma distributions is introduced and developed for model-based clustering and classification. The latest in a growing line of non-Gaussian mixture approaches to clustering and classification, the proposed mixture of…

Methodology · Statistics 2014-12-30 Sharon M. McNicholas , Paul D. McNicholas , Ryan P. Browne

We formulate gauge invariance for the equilibrium statistical mechanics of classical multi-component systems. Species-resolved phase space shifting constitutes a gauge transformation which we analyze using Noether's theorem and shifting…

Estimating the number of components is a fundamental challenge in unsupervised learning, particularly when dealing with high-dimensional data with many components or severely imbalanced component sizes. This paper addresses this challenge…

Machine Learning · Statistics 2026-04-22 Huan Qing

We consider multivariate centered Gaussian models for the random vector $(Z^1,\ldots, Z^p)$, whose conditional structure is described by a homogeneous graph and which is invariant under the action of a permutation subgroup. The following…

Statistics Theory · Mathematics 2022-09-22 Piotr Graczyk , Hideyuki Ishi , Bartosz Kołodziejek

We study the Hilbert-Schmidt measure on the manifold of mixed Gaussian states in multi mode continuous variable quantum systems. An analytical expression for the Hilbert-Schmidt volume element is derived. Its corresponding probability…

Quantum Physics · Physics 2015-03-10 Valentin Link , Walter T. Strunz

Given a finite Borel measure $\mu$ on R n and basic semi-algebraic sets $\Omega$\_i $\subset$ R n , i = 1,. .. , p, we provide a systematic numerical scheme to approximate as closely as desired $\mu$(\cup\_i $\Omega$\_i), when all moments…

Optimization and Control · Mathematics 2017-06-27 Jean Lasserre , Youssouf Emin

Gaussian mixture models are universal approximators in the sense that any smooth density can be approximated arbitrarily well with a Gaussian mixture model with enough components. Due to their broad expressive power, Gaussian mixture models…

Computation · Statistics 2025-02-12 Haley Colgate Kottler , Julia Lindberg , Jose Israel Rodriguez

Given data drawn from a mixture of multivariate Gaussians, a basic problem is to accurately estimate the mixture parameters. We give an algorithm for this problem that has a running time, and data requirement polynomial in the dimension and…

Machine Learning · Computer Science 2010-04-27 Ankur Moitra , Gregory Valiant

We point out necessary and sufficient conditions of uniform consistency of nonparametric sets of alternatives for widespread nonparametric tests. Nonparametric sets of alternatives can be defined both in terms of distribution function and…

Statistics Theory · Mathematics 2020-09-01 Mikhail Ermakov

We study the sparse high-dimensional Gaussian mixture model when the number of clusters is allowed to grow with the sample size. A minimax lower bound for parameter estimation is established, and we show that a constrained maximum…

Statistics Theory · Mathematics 2024-02-26 Dapeng Yao , Fangzheng Xie , Yanxun Xu

We consider the problem of approximating a general Gaussian location mixture by finite mixtures. The minimum order of finite mixtures that achieve a prescribed accuracy (measured by various $f$-divergences) is determined within constant…

Statistics Theory · Mathematics 2025-04-08 Yun Ma , Yihong Wu , Pengkun Yang

In this paper, we present sharp stability results for various reverse isoperimetric problems in $\mathbb R^2$. Specifically, we prove the stability of the reverse isoperimetric inequality for $\lambda$-convex bodies -- convex bodies with…

Differential Geometry · Mathematics 2026-01-07 Kostiantyn Drach , Kateryna Tatarko

The set of common numerical and analytical problems is introduced in the form of the generalized multidimensional discrete Poisson equation. It is shown that its solutions with square-summable discrete derivatives are unique up to a…

Mathematical Physics · Physics 2011-09-27 Roman Werpachowski
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