All Questions
4 questions
3
votes
1
answer
138
views
Handling absolute value and other discontinuities in numerical optimization methods that use gradients
Suppose we have difficult peak fitting problems where the the users wish to fit asymmetric peaks to their experimental data by the least squares method. One such function is illustrated below:
Here
$...
0
votes
0
answers
68
views
Numerically solve a specific saddle-point problem
Let $(\Omega,\mathcal E,\mu)$ be a probability space, $k\in\mathbb N$, $$W:=\left\{w:E\to[0,\infty)^k:\sum_{i=1}^kw_i=1\;\mu\text{-almost surely}\right\},$$ $G$ be a finite nonempty set and $a^{(g)}:E\...
4
votes
2
answers
672
views
Difference between Chebyshev first and second degree iterative methods
Consider linear equation $Au = f$.
We want to solve it with iterative method (assuming $A$ is good).
First order iterative method is:
$$
u^{k+1} = u^k - \alpha_{k+1}(Au^k - f),
$$
The second degree ...
1
vote
0
answers
90
views
Separable Least squares - is there a notion of conjugate directions?
I have a general question.
Suppose I have the following to optimize
$$\|Y-A(\mathbf{x})B(\mathbf{y})\|^2$$
where $Y$ is a vector, $A(\mathbf{x})$ is a matrix that depends on a vector $\mathbf{x}$ in a ...