On Matrices with Only One Non-SDD Row

Estimation of matrices with row sparsity

An increasing number of applications is concerned with recovering a sparsity can be defined in terms of lq balls for q 2 [0, 2), defined as Bq(s) = { v = (vi) 2 R2 : n2 ∑

Matrices with Prescribed Row and Column Sums

This is a survey of the recent progress and open questions on the structure of the sets of 0-1 and non-negative integer matrices with prescribed row and column sums. We discuss cardinality estimates, the structure of a random matrix from the set, discrete versions of the Brunn-Minkowski inequality and the statistical dependence between row and column sums.

On nonnegative matrices with given row and column sums

On Element SDD Approximability

This short communication shows that in some cases scalar elliptic finite element matrices cannot be approximated well by an sdd matrix. We also give a theoretical analysis of a simple heuristic method for approximating an element by an sdd matrix.

Row Products of Random Matrices

Let ∆1, . . . ,∆K be d × n matrices. We define the row product of these matrices as a d × n matrix, whose rows are entry-wise products of rows of ∆1, . . . ,∆K . This construction arises in certain computer science problems. We study the question, to which extent the spectral and geometric properties of the row product of independent random matrices resemble those properties for a d × n matrix ...