For many least-squares decomposition models efficient algorithms are well known. A more difficult problem arises in decomposition models where each residual is weighted by a nonnegative value. A special case is principal components analysis with missing data. Kiers (1997) discusses an algorithm for minimizing weighted decomposition models by iterative majorization. In this paper, we propose a m...

In this paper we give some useful combinatorial properties of polynomial paths. We also introduce generalized majorization between three sequences of integers and explore its combinatorics. In addition, we give a new, simple, purely polynomial proof of the convexity lemma of E. M. de Sá and R. C. Thompson. All these results have applications in matrix completion theory.

For $A,Bin M_{nm},$ we say that $A$ is left matrix majorized (resp. left matrix submajorized) by $B$ and write $Aprec_{ell}B$ (resp. $Aprec_{ell s}B$), if $A=RB$ for some $ntimes n$ row stochastic (resp. row substochastic) matrix $R.$ Moreover, we define the relation $sim_{ell s} $ on $M_{nm}$ as follows: $Asim_{ell s} B$ if $Aprec_{ell s} Bprec_{ell s} A.$ This paper characterizes all linear p...

A vector x E Rn is weakly k-majorized by a vector q 6 R^ if the sum of r largest components of x is less than or equal to the sum of r largest components of q for r = 1,2,. . . , k and k < n. In this paper we extend the components of x to their absolute values in the above description and generalize some results in [2] and [3] by G. Dahl and F. Margot.

Given a complex matrix H, we consider the decomposition H = QRP∗, where R is upper triangular and Q and P have orthonormal columns. Special instances of this decomposition include the singular value decomposition (SVD) and the Schur decomposition where R is an upper triangular matrix with the eigenvalues of H on the diagonal. We show that any diagonal for R can be achieved that satisfies Weyl’s...

In this paper, we discuss some general connections between the notions of positive map, weak majorization and entropic inequalities in the context of detection of entanglement among bipartite quantum systems. First, basing on the fact that any positive map Λ : Md(C) → Md(C) can be written as the difference between two completely positive maps Λ = Λ1 − Λ2, we propose a possible way to generalize...

Abstract: Portfolio risk forecasts are often made by estimating an asset or factor covariance matrix. Practitioners commonly want to adjust a global covariance matrix encompassing several sub-markets by individually correcting the sub-market diagonal blocks. Since this is likely to result in the loss of positive semi-definiteness of the overall matrix, the off-diagonal blocks must then be adjus...