نتایج جستجو برای: g row stochastic matrices

تعداد نتایج: 649119  

2016
Gabriel Peyré Marco Cuturi Justin Solomon

This paper presents a new technique for computing the barycenter of a set of distance or kernel matrices. These matrices, which define the interrelationships between points sampled from individual domains, are not required to have the same size or to be in row-by-row correspondence. We compare these matrices using the softassign criterion, which measures the minimum distortion induced by a prob...

A matrix R is said to be g-row substochastic if Re ≤ e. For X, Y ∈ Mn,m, it is said that X is sglt-majorized by Y , X ≺sglt Y , if there exists an n-by-n lower triangular g-row substochastic matrix R such that X = RY . This paper characterizes all (strong) linear preservers and strong linear preservers of ≺sglt on Rn and Mn,m, respectively.

Journal: :SIAM J. Comput. 1994
Phillip G. Bradford Gregory J. E. Rawlins Gregory E. Shannon

The matrix chain ordering problem is to find the cheapest way to multiply a chain of n matrices, where the matrices are pairwise compatible but of varying dimensions. Here we give several new parallel algorithms including O(lg3 n)-time and n/lgn-processor algorithms for solving the matrix chain ordering problem and for solving an optimal triangulation problem of convex polygons on the common CR...

2013
Gene Awyzio Jennifer Seberry G Awyzio

In order to efficiently compute some combinatorial designs based upon circulant matrices which have different, defined numbers of 1's and 0's in each row and column we need to find candidate vectors with differing weights and Hamming distances. This paper concentrates on how to efficiently create such circulant matrices. These circulant matrices have applications in signal processing, public ke...

2007
Werner Ulrich Nicholas J. Gotelli

Two opposing patterns of meta-community organization are nestedness and negative species co-occurrence. Both patterns can be quantified with metrics that are applied to presence-absence matrices and tested with null model analysis. Previous meta-analyses have given conflicting results, with the same set of matrices apparently showing high nestedness (Wright et al. 1998) and negative species co-...

Journal: :CoRR 2014
Demetres Christofides

Consider an invertible n × n matrix over some field. The Gauss-Jordan elimination reduces this matrix to the identity matrix using at most n row operations and in general that many operations might be needed. In [1] the authors considered matrices in GL(n, q), the set of n × n invertible matrices in the finite field of q elements, and provided an algorithm using only row operations which perfor...

2008
VASILIOS N. KATSIKIS DIMITRIOS PAPPAS

In this article a fast computational method is provided in order to calculate the Moore-Penrose inverse of full rank m× n matrices and of square matrices with at least one zero row or column. Sufficient conditions are also given for special type products of square matrices so that the reverse order law for the Moore-Penrose inverse is satisfied.

Journal: :CoRR 2011
Jeffrey W. Miller Matthew T. Harrison

We describe a dynamic programming algorithm for exact counting and exact uniform sampling of matrices with specified row and column sums. The algorithm runs in polynomial time when the column sums are bounded. Binary or non-negative integer matrices are handled. The method is distinguished by applicability to non-regular margins, tractability on large matrices, and the capacity for exact sampling.

2017
LeRoy B. Beasley LEROY B. BEASLEY

Let Sn(S) denote the set of symmetric matrices over some semiring, S. A line of A ∈ Sn(S) is a row or a column of A. A star of A is the submatrix of A consisting of a row and the corresponding column of A. The term rank of A is the minimum number of lines that contain all the nonzero entries of A. The star cover number is the minimum number of stars that contain all the nonzero entries of A. Th...

2007
Sepp Hochreiter Klaus Obermayer

with Application to Gene-Expression Analysis Sepp Hochreiter [email protected] Klaus Obermayer Fakultät für Elektrotechnik und Informatik Technische Universität Berlin Franklinstr. 28/29, 10587 Berlin, Germany [email protected] We consider the classification task for datasets which are described by matrices. Rows and columns of these matrices correspond to objects where row and column ...

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