All Questions
5 questions with no upvoted or accepted answers
4
votes
0
answers
539
views
Using Linear Programming as an iterative procedure
Suppose, we have a linear program and an optimal solution to it. Suppose now, we get a new constraint. We want to obtain an optimal solution to the given linear program extended by that new constraint....
2
votes
0
answers
56
views
A variant of the elliptope relaxation
Given a p.s.d. matrix $A$, one may want to find:
$$
\max_x x^t A x \mbox{ such that } x \mbox{ has entries }1 \mbox{ or } {-1}.
$$
This hard problem has a well known relaxation based on the so called ...
2
votes
1
answer
240
views
Basis pursuit algorithms for exponentially large matrices?
Are there any efficient algorithms/heuristics for basis pursuit for exponentially large matrices?
That is
$$\begin{array}{ll} \underset{x \in \Bbb R^n}{\text{minimize}} & \lVert x \rVert_0\\ \text{...
0
votes
1
answer
236
views
Solving a 0-1 quadratic matrix inequality
I am working on a binary optimization problem. So far I have derived the following constraint functions.
\begin{align}
\begin{bmatrix} \left( P + \sum_{i=1}^n (\sum_{j=1}^n x_{i, j} \alpha_j) e_i e_i^...
0
votes
0
answers
68
views
Under which conditions discrete versions of convex\concave function are submodular/supermodular?
I have $f(x)$ with $x \in [0,1]$ and $f(x)$ is convex, then, under which conditions discrete function which is defined as $f(x_h)$ on discrete subset of $[0,1]$, for example, $x_h \in \{0, h, 2h, \...