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Extended Formulations, Nonnegative Factorizations, and Randomized Communication Protocols

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Yuri Faenza, Hans Raj Tiwary
2012

Résumé

We show that the binary logarithm of the nonnegative rank of a nonnegative matrix is, up to small constants, equal to the minimum complexity of a randomized communication protocol computing the matrix in expectation. We use this connection to prove new conditional lower bounds on the sizes of extended formulations, in particular, for perfect matching polytopes.

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https://infoscience.epfl.ch/entities/publication/7f441b95-021b-4b85-9227-e2f1222e56dc

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Concepts associés (21)

Matrice à coefficients positifs

Une matrice de type est à coefficients positifs lorsque tous ses éléments sont réels positifs ; on écrira alors . Elle est dite strictement positive lorsque tous ses éléments sont strictement positifs ; on écrira alors . et étant deux matrices réelles on définit une relation d'ordre partiel sur ces matrices en posant . Il est immédiat que cette relation d'ordre est compatible avec l'addition. De même elle est compatible avec la multiplication (à gauche ou à droite) par une matrice positive.

Matrix decomposition

In the mathematical discipline of linear algebra, a matrix decomposition or matrix factorization is a factorization of a matrix into a product of matrices. There are many different matrix decompositions; each finds use among a particular class of problems. In numerical analysis, different decompositions are used to implement efficient matrix algorithms. For instance, when solving a system of linear equations , the matrix A can be decomposed via the LU decomposition.

Definite matrix

In mathematics, a symmetric matrix with real entries is positive-definite if the real number is positive for every nonzero real column vector where is the transpose of . More generally, a Hermitian matrix (that is, a complex matrix equal to its conjugate transpose) is positive-definite if the real number is positive for every nonzero complex column vector where denotes the conjugate transpose of Positive semi-definite matrices are defined similarly, except that the scalars and are required to be positive or zero (that is, nonnegative).

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