Abstract. An extended sequentially semiseparable (SSS) representation derived from time-varying system theory is used to capture, on the one hand, the low-rank of the off-diagonal blocks of a matrix for the purposes of efficient computations and, on the other, to provide for sufficient descriptive richness to allow for backward stability in the computations. We present (i) a fast algorithm (linear in the number of equations) to solve least squares problems in which the coefficient matrix is in SSS form, (ii) a fast algorithm to find the SSS form of X such that AX = B, where A and B are in SSS form, and (iii) a fast model reduction technique to improve the SSS form
This dissertation presents several fast and stable algorithms for both dense and sparse matrices bas...
Many problems in mathematical physics and engineering involve solving linear systems Ax = b which ar...
In this paper the definition of semiseparable matrices is invest- igated. Properties of the frequent...
Abstract. Randomized sampling has recently been proven a highly efficient technique for computing ap...
In this thesis, we study a important class of structured matrices: "Hierarchically Semi-Separable" m...
AbstractMatrices represented as a sum of diagonal and semiseparable ones are considered here. These ...
International audienceThe class of quasiseparable matrices is defined by a pair of bounds, called th...
International audienceThe class of quasiseparable matrices is defined by the property that any subma...
Abstract. We present a new representation for the inverse of a matrix that is a sum of a banded matr...
Quasi-separable matrices are a class of rank-structured matriceswidely used in numerical linear alge...
Abstract. We present a fast algorithm for linear least squares problems governed by hierarchi-cally ...
Abstract. We present a fast algorithm for linear least squares problems governed by hierarchi-cally ...
This paper presents a class of preconditioners for sparse systems arising from discretized partial d...
Abstract. In this paper, we consider a class of hierarchically rank structured matrices that include...
International audienceWe propose an efficient algorithm for the solution of shifted quasiseparable s...
This dissertation presents several fast and stable algorithms for both dense and sparse matrices bas...
Many problems in mathematical physics and engineering involve solving linear systems Ax = b which ar...
In this paper the definition of semiseparable matrices is invest- igated. Properties of the frequent...
Abstract. Randomized sampling has recently been proven a highly efficient technique for computing ap...
In this thesis, we study a important class of structured matrices: "Hierarchically Semi-Separable" m...
AbstractMatrices represented as a sum of diagonal and semiseparable ones are considered here. These ...
International audienceThe class of quasiseparable matrices is defined by a pair of bounds, called th...
International audienceThe class of quasiseparable matrices is defined by the property that any subma...
Abstract. We present a new representation for the inverse of a matrix that is a sum of a banded matr...
Quasi-separable matrices are a class of rank-structured matriceswidely used in numerical linear alge...
Abstract. We present a fast algorithm for linear least squares problems governed by hierarchi-cally ...
Abstract. We present a fast algorithm for linear least squares problems governed by hierarchi-cally ...
This paper presents a class of preconditioners for sparse systems arising from discretized partial d...
Abstract. In this paper, we consider a class of hierarchically rank structured matrices that include...
International audienceWe propose an efficient algorithm for the solution of shifted quasiseparable s...
This dissertation presents several fast and stable algorithms for both dense and sparse matrices bas...
Many problems in mathematical physics and engineering involve solving linear systems Ax = b which ar...
In this paper the definition of semiseparable matrices is invest- igated. Properties of the frequent...