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For general thinning procedures, its inverse operation, the condensing, is studied and a link to integration-by-parts formulas is established. This extends the recent results on that link for independent thinnings of point processes to…

Probability · Mathematics 2017-04-26 Mathias Rafler

We develop flexible methods of deriving variational inference for models with complex latent variable structure. By splitting the variables in these models into "global" parameters and "local" latent variables, we define a class of…

Computation · Statistics 2019-04-23 Linda S. L. Tan , Aishwarya Bhaskaran , David J. Nott

In this article, we define and study a geometry and an order on the set of partitions of an even number of objects. One of the definitions involves the partition algebra, a structure of algebra on the set of such partitions depending on an…

Combinatorics · Mathematics 2016-11-01 Franck Gabriel

Concentration inequalities, a major tool in probability theory, quantify how much a random variable deviates from a certain quantity. This paper proposes a systematic convex optimization approach to studying and generating concentration…

Probability · Mathematics 2024-08-30 Celine Moucer , Adrien Taylor , Francis Bach

Compositional data (i.e., data comprising random variables that sum up to a constant) arises in many applications including microbiome studies, chemical ecology, political science, and experimental designs. Yet when compositional data serve…

Methodology · Statistics 2025-01-03 Ritwik Bhaduri , Siyuan Ma , Lucas Janson

A specific family of point processes are introduced that allow to select samples for the purpose of estimating the mean or the integral of a function of a real variable. These processes, called quasi-systematic processes, depend on a tuning…

Methodology · Statistics 2016-07-19 Matthieu Wilhelm , Yves Tillé , Lionel Qualité

We review possible measures of complexity which might in particular be applicable to situations where the complexity seems to arise spontaneously. We point out that not all of them correspond to the intuitive (or "naive") notion, and that…

Data Analysis, Statistics and Probability · Physics 2012-08-20 Peter Grassberger

Random embeddings project high-dimensional spaces to low-dimensional ones; they are careful constructions which allow the approximate preservation of key properties, such as the pair-wise distances between points. Often in the field of…

Optimization and Control · Mathematics 2022-06-08 Zhen Shao

Set partitions and permutations with restrictions on the size of the blocks and cycles are important combinatorial sequences. Counting these objects lead to the sequences generalizing the classical Stirling and Bell numbers. The main focus…

Combinatorics · Mathematics 2017-08-01 Victor H. Moll , José L. Ramirez , Diego Villamizar

The paper presents complexity results and performance guaranties for a family of approximation algorithms for an optimisation problem arising in software testing and manufacturing. The problem is formulated as a partitioning of a set where…

Data Structures and Algorithms · Computer Science 2022-12-13 Yakov Zinder , Bertrand M. T. Lin , Joanna Berlińska

We consider colored compositions where only some parts are allowed different colors, depending on their locations in the composition. The counting sequences are obtained through generating functions. Connections to many other combinatorial…

Combinatorics · Mathematics 2025-11-12 Andrew Li , Hua Wang

Unlike classical and free independence, the boolean and monotone notions of independence lack of the property of independent constants. In the scalar case, this leads to restrictions for the central limit theorems, as observed by F.…

Probability · Mathematics 2021-09-14 Carlos Dias-Aguilera , Tulio Gaxiola , Jorge Santos , Carlos Vargas

Random constraint satisfaction problems play an important role in computer science and combinatorics. For example, they provide challenging benchmark instances for algorithms and they have been harnessed in probabilistic constructions of…

Combinatorics · Mathematics 2020-05-27 Amin Coja-Oghlan , Tobias Kapetanopoulos , Noela Müller

A wide range of physical problems can be described by randomly-oriented linear trajectories, including any system of objects, organisms, particles, or rays that follow a linear path. Dependent upon the particular random variables that…

Probability · Mathematics 2014-01-03 Gregory T. Clement

Finding a point in the intersection of a collection of closed convex sets, that is the convex feasibility problem, represents the main modeling strategy for many computational problems. In this paper we analyze new stochastic reformulations…

Optimization and Control · Mathematics 2018-01-16 Ion Necoara , Peter Richtarik , Andrei Patrascu

Structural independence is the (conditional) independence that arises from the structure rather than the precise numerical values of a distribution. We develop this concept and relate it to $d$-separation and structural causal models.…

Probability · Mathematics 2025-06-24 Matthias Georg Mayer

First, we present a concise glossary of formulas for composition of standard, cumulant, factorial, and factorial cumulant moments in superposition (compound) models, where final particles are created via independent emission from a…

Nuclear Theory · Physics 2017-06-28 Wojciech Broniowski , Adam Olszewski

This paper will be devoted to study weighted (deformed) free Poisson random variables from the viewpoint of orthogonal polynomials and statistics of non-crossing partitions. A family of weighted (deformed) free Poisson random variables will…

Probability · Mathematics 2025-09-03 Nobuhiro Asai , Hiroaki Yoshida

We study properties of two resampling scenarios: Conditional Randomisation and Conditional Permutation schemes, which are relevant for testing conditional independence of discrete random variables $X$ and $Y$ given a random variable $Z$.…

Statistics Theory · Mathematics 2023-04-14 Małgorzata Łazęcka , Bartosz Kołodziejek , Jan Mielniczuk

The independence clustering problem is considered in the following formulation: given a set $S$ of random variables, it is required to find the finest partitioning $\{U_1,\dots,U_k\}$ of $S$ into clusters such that the clusters…

Machine Learning · Computer Science 2017-03-21 Daniil Ryabko
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