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In this paper, we study the probability that some weighted partial sums of a random multiplicative function $f$ are positive. Applying the characteristic decomposition, we obtain that if $S$ is a non-empty subset of the multiplicative…

Number Theory · Mathematics 2025-09-15 Shuming Liu , Bing He

The paper outlines an exact combinatorial approach to finite coagulating systems. In this approach, cluster sizes and time are discrete, and the binary aggregation alone governs the time evolution of the systems. By considering the growth…

Statistical Mechanics · Physics 2018-02-21 Agata Fronczak , Anna Chmiel , Piotr Fronczak

We study the scenario of graph-based clustering algorithms such as spectral clustering. Given a set of data points, one first has to construct a graph on the data points and then apply a graph clustering algorithm to find a suitable…

Machine Learning · Statistics 2011-02-11 Markus Maier , Ulrike von Luxburg , Matthias Hein

Let ${\cal G}=(G,w) $ be a positive-weighted graph, that is a graph $G$ endowed with a function $w$ from the edge set of $G$ to the set of positive real numbers; for any distinct vertices $i,j $, we define $D_{i,j}({\cal G})$ to be the…

Combinatorics · Mathematics 2016-05-04 Agnese Baldisserri , Elena Rubei

We generalize finite-sample bounds for convex clustering to the setting where affinity weights appearing in the objective correspond to a general connected graph. These bounds and their analysis lead to a better understanding of clustering…

Machine Learning · Statistics 2026-05-26 Sam Rosen , Jason Xu

We give several descriptions of positive quadrature formulas which are exact for trigonometric -, respectively, Laurent polynomials of degree less or equal $n-1-m$, $0\leq m\leq n-1$. A complete and simple description is obtained with the…

Classical Analysis and ODEs · Mathematics 2010-01-15 Franz Peherstorfer

We propose a graph clustering formulation based on multicut (a.k.a. weighted correlation clustering) on the complete graph. Our formulation does not need specification of the graph topology as in the original sparse formulation of multicut,…

Computer Vision and Pattern Recognition · Computer Science 2023-06-06 Ahmed Abbas , Paul Swoboda

We derive an efficient method to perform clustering of nodes in Gaussian graphical models directly from sample data. Nodes are clustered based on the similarity of their network neighborhoods, with edge weights defined by partial…

Machine Learning · Computer Science 2019-10-08 Keith Dillon

We compute a complete set of isomorphism classes of cubic fourfolds over $\mathbb{F}_2$. Using this, we are able to compile statistics about various invariants of cubic fourfolds, including their counts of points, lines, and planes; all…

Algebraic Geometry · Mathematics 2023-06-19 Asher Auel , Avinash Kulkarni , Jack Petok , Jonah Weinbaum

We give a generating function for the number of graphs with given numerical properties and prescribed weighted number of connected components. As an application, we give a generating function for the number of bipartite graphs of given…

Combinatorics · Mathematics 2016-06-28 Joungmin Song

An important question in the theory of approximate integration is to study the conditions on the nodes $x_{k,n}$ and weights $w_{k,n}$ that allow an estimate of the form $$ \sup_{f\in \mathcal{B}_\gamma}|\sum_k…

Numerical Analysis · Mathematics 2017-09-06 Hrushikesh N. Mhaskar

In this paper, we study sequences of perfect t-embeddings of a uniformly weighted family of graphs we call generalized tower graphs. We show that the embeddings of these graphs satisfy certain technical assumptions, in particular, the…

Mathematical Physics · Physics 2025-09-24 David Keating , Hieu Trung Vu

A new type of quadrature is developed. The Gaussian quadrature, for a given measure, finds optimal values of a function's argument (nodes) and the corresponding weights. In contrast, the Lebesgue quadrature developed in this paper, finds…

Numerical Analysis · Mathematics 2020-02-25 Vladislav Gennadievich Malyshkin

Driven by several successful applications such as in stochastic gradient descent or in Bayesian computation, control variates have become a major tool for Monte Carlo integration. However, standard methods do not allow the distribution of…

Machine Learning · Statistics 2022-10-06 Rémi Leluc , François Portier , Johan Segers , Aigerim Zhuman

In enumerative combinatorics, it is often a goal to enumerate both labeled and unlabeled structures of a given type. The theory of combinatorial species is a novel toolset which provides a rigorous foundation for dealing with the…

Combinatorics · Mathematics 2013-12-03 Andy Hardt , Pete McNeely , Tung Phan , Justin M. Troyka

In 2013, Lee, Li, and Zelevinsky introduced combinatorial objects called compatible pairs to construct the greedy bases for rank-2 cluster algebras, consisting of indecomposable positive elements including the cluster monomials.…

Combinatorics · Mathematics 2024-09-24 Amanda Burcroff , Kyungyong Lee , Lang Mou

A graphical model provides a compact and efficient representation of the association structure of a multivariate distribution by means of a graph. Relevant features of the distribution are represented by vertices, edges and other…

Statistics Theory · Mathematics 2020-09-03 Alberto Roverato , Robert Castelo

We study the beta functions for the dimensionless couplings in quadratic curvature gravity, and find that there is a simple argument to restrict the possible form of the beta functions as derived from the counterterms at an arbitrary loop.…

High Energy Physics - Theory · Physics 2024-07-12 Hikaru Kawai , Nobuyoshi Ohta

A natural representation of random graphs is the random measure. The collection of product random measures, their transformations, and non-negative test functions forms a general representation of the collection of non-negative weighted…

Probability · Mathematics 2022-04-21 Caleb Bastian , Herschel Rabitz

The G-Wishart distribution is an essential component for the Bayesian analysis of Gaussian graphical models as the conjugate prior for the precision matrix. Evaluating the marginal likelihood of such models usually requires computing…

Methodology · Statistics 2025-04-11 Ching Wong , Giusi Moffa , Jack Kuipers