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It is well known that correlations in microarray data represent a serious nuisance deteriorating the performance of gene selection procedures. This paper is intended to demonstrate that the correlation structure of microarray data provides…

Applications · Statistics 2007-12-18 Lev Klebanov , Andrei Yakovlev

We consider the problem of statistical inference on unknown quantities structured as a multiway table. We show that such multiway tables are naturally formed by arranging regression coefficients in complex systems of linear models for…

Methodology · Statistics 2013-09-06 Xiaoquan Wen

Several real-world and abstract structures and systems are characterized by marked hierarchy to the point of being expressed as trees. Because the study of these entities often involves sampling (or discovering) the tree nodes in a specific…

Physics and Society · Physics 2022-04-18 Alexandre Benatti , Luciano da F. Costa

We construct tree-decompositions of graphs that distinguish all their k-blocks and tangles of order k, for any fixed integer k. We describe a family of algorithms to construct such decompositions, seeking to maximize their diversity subject…

Combinatorics · Mathematics 2014-04-25 Johannes Carmesin , Reinhard Diestel , Matthias Hamann , Fabian Hundertmark

We consider the problem of evaluating designs for a two-arm randomized experiment with the criterion being the power of the randomization test for the one-sided null hypothesis. Our evaluation assumes a response that is linear in one…

Methodology · Statistics 2020-08-14 Abba M. Krieger , David Azriel , Michael Sklar , Adam Kapelner

Tensor ring (TR) decomposition is a simple but effective tensor network for analyzing and interpreting latent patterns of tensors. In this work, we propose a doubly randomized optimization framework for computing TR decomposition. It can be…

Numerical Analysis · Mathematics 2023-03-30 Yajie Yu , Hanyu Li , Jingchun Zhou

In this paper we present a method ofcomputing the posterior probability ofconditional independence of two or morecontinuous variables from data,examined at several resolutions. Ourapproach is motivated by theobservation that the appearance…

Artificial Intelligence · Computer Science 2013-01-14 Dimitris Margaritis , Sebastian Thrun

We study a class of evolutionary partial differential systems with two components related to second order (in time) non-evolutionary equations of odd order in spatial variable. We develop the formal diagonalisation method in symbolic…

Exactly Solvable and Integrable Systems · Physics 2007-05-23 Vladimir S. Novikov , Jing Ping Wang

Matching mechanisms play a central role in operations management across diverse fields including education, healthcare, and online platforms. However, experimentally comparing a new matching algorithm against a status quo presents some…

Methodology · Statistics 2026-01-30 Chonghuan Wang

Can you decide if there is a coincidence in the numbers counting two different combinatorial objects? For example, can you decide if two regions in $\mathbb{R}^3$ have the same number of domino tilings? There are two versions of the…

Combinatorics · Mathematics 2024-09-16 Swee Hong Chan , Igor Pak

Decompositions of networks are useful not only for structural exploration. They also have implications and use in analysis and computational solution of processes (such as the Ising model, percolation, SIR model) running on a given network.…

Disordered Systems and Neural Networks · Physics 2020-04-29 Konstantin Klemm

This paper describes a process for clustering concepts into chains from data presented randomly to an evaluating system. There are a number of rules or guidelines that help the system to determine more accurately what concepts belong to a…

Artificial Intelligence · Computer Science 2014-03-05 Kieran Greer

We propose a new class of models for random permutations, which we call log-linear models, by the analogy with log-linear models used in the analysis of contingency tables. As a special case, we study the family of all Luce-decomposable…

Statistics Theory · Mathematics 2007-11-19 V. Csiszár

Within the last fifteen years, network theory has been successfully applied both to natural sciences and to socioeconomic disciplines. In particular, bipartite networks have been recognized to provide a particularly insightful…

Physics and Society · Physics 2015-12-07 Fabio Saracco , Riccardo Di Clemente , Andrea Gabrielli , Tiziano Squartini

We describe a basic correspondence between linear algebraic structures within vector embeddings in artificial neural networks and conditional independence constraints on the probability distributions modeled by these networks. Our framework…

Machine Learning · Computer Science 2024-07-15 Matthew Trager , Alessandro Achille , Pramuditha Perera , Luca Zancato , Stefano Soatto

We investigate point arrangements $v_i\in\mathbb R^d,i\in \{1,...,n \}$ with certain prescribed symmetries. The arrangement space of $v$ is the column span of the matrix in which the $v_i$ are the rows. We characterize properties of $v$ in…

Metric Geometry · Mathematics 2021-03-02 Martin Winter

Decomposition is a common tool for synthesis of many physical systems. It is also used for analyzing large scale systems which then known as tearing and reconstruction. On the other hand, commutativity of cascade connected systems have…

Systems and Control · Computer Science 2020-08-13 Mehmet Emir Koksal , Ali Yakar

In this paper we propose several variants to perform the independence test between two random elements based on recurrence rates. We will show how to calculate the test statistic in each one of these cases. From simulations we obtain that…

Methodology · Statistics 2020-09-21 Juan Kalemkerian , Diego Fernández

There are multiple cluster randomised trial designs that vary in when the clusters cross between control and intervention states, when observations are made within clusters, and how many observations are made at that time point. Identifying…

Methodology · Statistics 2023-07-20 Samuel I. Watson , Alan Girling , Karla Hemming

The aim of this paper is to provide a new method for learning the relationships between data that have been obtained independently. Unlike existing methods like matching, the proposed technique does not require any contextual information,…

Machine Learning · Statistics 2016-01-05 Alexandra Carpentier , Teresa Schlueter
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