All Questions
Tagged with numerical-linear-algebra factorization
7 questions
2
votes
1
answer
214
views
How to do LU factorization efficiently based on the factorized result added with a low-rank matrix?
Suppose a square $n\times n$, dense matrix $A^{\text{old}}$ has been factorized into $L^{\text{old}}$ and $U^{\text{old}}$ components by performing a LU decomposition $A^{\text{old}} = L^{\text{old}}U^...
- 21
1
vote
0
answers
18
views
Optimal Truncation of LDL-factorization to improve conditioning
Suppose I factored real symmetric quasi-definite $ A_0= L_0 \cdot D_0 \cdot L_0^T$ and the factorization exists, with $D$ diagonal and $L$ unit lower-triangular; and suppose $L$ and $D$ are badly ...
- 51
1
vote
0
answers
34
views
Slope assertion in Cholesky on digital computers
For a real symmetric positive definite linear system
$$ A \cdot x = b, $$
solved using Choelsky with forward- and backward-substitution, we know it for the numerical approximation $\tilde{x}$ to $x$ ...
- 51
3
votes
2
answers
276
views
Practical symmetric equivalent to QR factorization updates
As we know, the QR-factorization $Q\cdot R=A$ of any real symmetric $n \times n$ matrix $A$ with full rank is unconditionally numerically stable. Further, when A is rank-1-updated, the factorization ...
- 51
2
votes
1
answer
128
views
Matrix factorization for dimensional reduction similar to spectral decomposition/SVD
I have a graph clustering problem I'm working on and it basically involves finding a factorization of the adjacency matrix $A$ such that the following equations are (approximately) satisfied:
$$
A \...
- 123
12
votes
2
answers
4k
views
How can one construct a sparse null space basis using recursive LU decomposition?
Given an $m$ by $n$ matrix $A$ I'm familiar with the standard method to compute a basis for the null space of $A$ by computing a QR factorization of $A^T$. If $A$ is large and sparse, we can use ...
- 723
4
votes
0
answers
381
views
Efficiently factorize a KKT system with block diagonal upper corner
I have a system resulting from a quadratic energy minimization with linear equality constraints enforced with Lagrange multipliers which has the form:
\begin{equation}
A =
\left[\begin{array}{c|c}
\...
- 723