نتایج جستجو برای: doubly stochastic matrix

تعداد نتایج: 493629  

2009

In this paper we introduce an approximate optimization framework for solving graphs problems involving doubly stochastic matrices. This is achieved by using a low dimensional formulation of the matrices and the approximate solution is achieved by a simple subgradient method. We also describe one problem that can be solved using our method.

Journal: :Proceedings of the ... AAAI Conference on Artificial Intelligence 2023

Doubly stochastic matrix plays an essential role in several areas such as statistics and machine learning. In this paper we consider the optimal approximation of a square set doubly matrices. A structured BFGS method is proposed to solve dual primal problem. The resulting algorithm builds curvature information into diagonal components true Hessian, so that it takes only additional linear cost o...

2010
ALLAN SLY

We investigate the properties of uniform doubly stochastic random matrices, that is non-negative matrices conditioned to have their rows and columns sum to 1. The rescaled marginal distributions are shown to converge to exponential distributions and indeed even large sub-matrices of side-length o(n) behave like independent exponentials. We determine the limiting empirical distribution of the si...

Journal: :Proceedings of the American Mathematical Society 1967

Journal: :Discrete Applied Mathematics 2008
Pavel Yu. Chebotarev

For a graph G, let fij be the number of spanning rooted forests in which vertex j belongs to a tree rooted at i. In this paper, we show that for a path, the fij’s can be expressed as the products of Fibonacci numbers; for a cycle, they are products of Fibonacci and Lucas numbers. The doubly stochastic graph matrix is the matrix F = (fij)n×n f , where f is the total number of spanning rooted for...

Journal: :wavelet and linear algebra 2014
f. khalooei

for vectors x, y ∈ rn, it is said that x is left matrix majorizedby y if for some row stochastic matrix r; x = ry. the relationx ∼` y, is defined as follows: x ∼` y if and only if x is leftmatrix majorized by y and y is left matrix majorized by x. alinear operator t : rp → rn is said to be a linear preserver ofa given relation ≺ if x ≺ y on rp implies that t x ≺ ty onrn. the linear preservers o...

Journal: :Electr. J. Comb. 2009
Jessica Striker

The Birkhoff (permutation) polytope, Bn, consists of the n × n nonnegative doubly stochastic matrices, has dimension (n− 1)2, and has n2 facets. A new analogue, the alternating sign matrix polytope, ASMn, is introduced and characterized. Its vertices are the Qn−1 j=0 (3j+1)! (n+j)! n × n alternating sign matrices. It has dimension (n− 1)2, has 4[(n− 2)2 +1] facets, and has a simple inequality d...

Journal: :Discrete & Computational Geometry 2014
Nathan Linial Zur Luria

Let us denote by Ωn the Birkhoff polytope of n× n doubly stochastic matrices. As the Birkhoff–von Neumann theorem famously states, the vertex set of Ωn coincides with the set of all n× n permutation matrices. Here we consider a higherdimensional analog of this basic fact. Let Ω n be the polytope which consists of all tristochastic arrays of order n. These are n×n×n arrays with nonnegative entri...

2009
Joseph P. S. Kung Gian-Carlo Rota Catherine H. Yan

Gian-Carlo Rota was one of the most original and colorful mathematicians of the twentieth century. His work on the foundations of combinatorics focused on revealing the algebraic structures that lie behind diverse combinatorial areas and created a new area of algebraic combinatorics. His graduate courses influenced generations of students. Written by two of his former students, this book is bas...

2010
Kyle Pula Seok-Zun Song Ian M. Wanless

We consider the minimum permanents and minimising matrices on the faces of the polytope of doubly stochastic matrices whose nonzero entries coincide with those of, respectively, Um,n = [ In Jn,m Jm,n 0m ] and Vm,n = [ In Jn,m Jm,n Jm,m ] . We conjecture that Vm,n is cohesive but not barycentric for 1 < n < m + √ m and that it is not cohesive for n > m + √ m. We prove that it is cohesive for 1 <...

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