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All components of complements of discriminant varieties of simple real function singularities are explicitly listed. New invariants of such components (for not necessarily simple singularities) are introduced. A combinatorial algorithm…

Algebraic Geometry · Mathematics 2022-04-25 V. A. Vassiliev

The total matching polytope generalizes the stable set polytope and the matching polytope. In this paper, we first propose new facet-defining inequalities for the total matching polytope. We then give an exponential-sized, non-redundant…

Discrete Mathematics · Computer Science 2023-12-29 Yuri Faenza , Luca Ferrarini

The multi-index matching problem (MIMP) generalizes the well known matching problem by going from pairs to d-uplets. We use the cavity method from statistical physics to analyze its properties when the costs of the d-uplets are random. At…

Disordered Systems and Neural Networks · Physics 2009-11-11 O. C. Martin , M. Mezard , O. Rivoire

This paper introduces the \emph{$d$-distance matching problem}, in which we are given a bipartite graph $G=(S,T;E)$ with $S=\{s_1,\dots,s_n\}$, a weight function on the edges and an integer $d\in\mathbb Z_+$. The goal is to find a maximum…

Combinatorics · Mathematics 2023-01-24 Péter Madarasi

Here we show the connection between topological order and the geometric entanglement, as measured by the logarithm of the overlap between a given state and its closest product state of blocks, for the topological universality class of the…

Strongly Correlated Electrons · Physics 2012-05-11 Roman Orus , Tzu-Chieh Wei

This paper provides a further refinement to the previous response by introducing new structures and algorithms for counting VMPs of common \emph{Edge Requirement} (ER) and hence for counting the perfect matchings.

Computational Complexity · Computer Science 2017-10-10 Javaid Aslam

Incomplete pairwise comparison matrices contain some missing judgements. A natural approach to estimate these values is provided by minimising a reasonable measure of inconsistency after unknown entries are replaced by variables. Two widely…

Optimization and Control · Mathematics 2024-02-07 László Csató , Kolos Csaba Ágoston , Sándor Bozóki

Entropy is a measure of heterogeneity widely used in applied sciences, often when data are collected over space. Recently, a number of approaches has been proposed to include spatial information in entropy. The aim of entropy is to…

Statistics Theory · Mathematics 2019-11-12 Linda Altieri , Daniela Cocchi , Giulia Roli

The work we describe here is a part of a research program of developing foundations of declarative solving of search problems. We consider the model expansion task as the task representing the essence of search problems where we are given…

Logic in Computer Science · Computer Science 2011-09-06 Shahab Tasharrofi , Xiongnan , Wu , Eugenia Ternovska

When pre-processing observational data via matching, we seek to approximate each unit with maximally similar peers that had an alternative treatment status--essentially replicating a randomized block design. However, as one considers a…

Econometrics · Economics 2019-05-30 Gentry Johnson , Brian Quistorff , Matt Goldman

We prove existence and uniqueness of solutions for an entropic version of the semi-geostrophic equations. We also establish convergence to a weak solution of the semi-geostrophic equations as the entropic parameter vanishes. Convergence is…

Analysis of PDEs · Mathematics 2024-04-29 Guillaume Carlier , Hugo Malamut

Comparison-based algorithms are algorithms for which the execution of each operation is solely based on the outcome of a series of comparisons between elements. Comparison-based computations can be naturally represented via the following…

Data Structures and Algorithms · Computer Science 2020-11-17 Michel Schellekens

A new combinatorial-probabilistic diagnostic entropy has been introduced. It describes the pair-wise sum of probabilities of system conditions that have to be distinguished during the diagnosing process. The proposed measure describes the…

Information Theory · Computer Science 2009-09-29 Henryk Borowczyk

Dempster's covariance selection method is extended first to general nonsingular matrices and then to full rank rectangular matrices. Dempster observed that his completion solved a maximum entropy problem. We show that our generalized…

Optimization and Control · Mathematics 2010-06-29 Augusto Ferrante , Michele Pavon

We show that a simple geometric result suffices to derive the form of the optimal solution in a large class of finite and infinite-dimensional maximum entropy problems concerning probability distributions, spectral densities and covariance…

Optimization and Control · Mathematics 2012-12-24 Michele Pavon , Augusto Ferrante

We propose an entropy function for simplicial complices. Its value gives the expected cost of the optimal encoding of sequences of vertices of the complex, when any two vertices belonging to the same simplex are indistinguishable. We show…

Information Theory · Computer Science 2016-03-24 Stefan Dantchev , Ioannis Ivrissimtzis

Despite encouraging recent progresses in ensemble approaches, classification methods seem to have reached a plateau in development. Further advances depend on a better understanding of geometrical and topological characteristics of point…

Computer Vision and Pattern Recognition · Computer Science 2007-05-23 Tin Kam Ho

Given a large real symmetric, positive semidefinite m-by-m matrix, the goal of this paper is to show how a numerical approximation of the entropy, given by the sum of the entropies of the individual eigenvalues, can be computed in an…

Numerical Analysis · Mathematics 2014-06-13 Thomas P. Wihler , Bänz Bessire , André Stefanov

Feature selection methods are usually evaluated by wrapping specific classifiers and datasets in the evaluation process, resulting very often in unfair comparisons between methods. In this work, we develop a theoretical framework that…

Machine Learning · Statistics 2016-10-11 Cláudia Pascoal , M. Rosário Oliveira , António Pacheco , Rui Valadas

The task of estimating a matrix given a sample of observed entries is known as the \emph{matrix completion problem}. Most works on matrix completion have focused on recovering an unknown real-valued low-rank matrix from a random sample of…

Statistics Theory · Mathematics 2014-08-27 Olga Klopp , Jean Lafond , Eric Moulines , Joseph Salmon
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