Vector majorization via nonnegative definite doubly stochastic matrices of maximum rank
نویسندگان
چکیده
منابع مشابه
Embedding nonnegative definite Toeplitz matrices in nonnegative definite circulant matrices, with application to covariance estimation
Ahtract -The class of nonnegative definite Toeplitz matrices that can be embedded in nonnegative definite circulant matrices of larger sue is characterized. An equivalent characterization in terms of the spectrum of the underlying process is also presented, together with the corresponding extrema1 processes. It is shown that a given finite duration sequence p can be extended to be the covarianc...
متن کاملSeparating doubly nonnegative and completely positive matrices
The cone of Completely Positive (CP) matrices can be used to exactly formulate a variety of NP-Hard optimization problems. A tractable relaxation for CP matrices is provided by the cone of Doubly Nonnegative (DNN) matrices; that is, matrices that are both positive semidefinite and componentwise nonnegative. A natural problem in the optimization setting is then to separate a given DNN but non-CP...
متن کاملDoubly stochastic matrices of trees
In this paper, we obtain sharp upper and lower bounds for the smallest entries of doubly stochastic matrices of trees and characterize all extreme graphs which attain the bounds. We also present a counterexample to Merris’ conjecture on relations between the smallest entry of the doubly stochastic matrix and the algebraic connectivity of a graph in [R. Merris, Doubly stochastic graph matrices I...
متن کاملOn Reduced Rank Nonnegative Matrix Factorization for Symmetric Nonnegative Matrices
Let V ∈ R be a nonnegative matrix. The nonnegative matrix factorization (NNMF) problem consists of finding nonnegative matrix factors W ∈ R and H ∈ R such that V ≈ WH. Lee and Seung proposed two algorithms which find nonnegative W and H such that ‖V −WH‖F is minimized. After examining the case in which r = 1 about which a complete characterization of the solution is possible, we consider the ca...
متن کاملNonnegative Rank Factorization via Rank Reduction
Abstract. Any given nonnegative matrix A ∈ R can be expressed as the product A = UV for some nonnegative matrices U ∈ R and V ∈ R with k ≤ min{m, n}. The smallest k that makes this factorization possible is called the nonnegative rank of A. Computing the exact nonnegative rank and the corresponding factorization are known to be NP-hard. Even if the nonnegative rank is known a priori, no simple ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Linear Algebra and its Applications
سال: 1997
ISSN: 0024-3795
DOI: 10.1016/s0024-3795(96)00399-0