All Questions
Tagged with disciplined-convex-programming optimization
11 questions
2
votes
1
answer
41
views
Modeling $-\ln(1 - w \cdot \sigma(x))$ as disciplined convex programming
Given $0 < w \leq 1$, I would like to use the function:
$$
-\ln(1 - w \sigma(t)),
$$
where $\sigma(t) = 1 / (1 + \exp(-t))$ is the sigmoid function, in my objective. It's a bit tedious, but this ...
- 131
2
votes
0
answers
164
views
Global optimizers handling minimization of an expression arising from the likelihood of a multivariate normal
I am interested in converting the following optimisation problem into a form that an exponential cone and/or SDP solver such as MOSEK can handle. This is a multivariate version of the question I ...
- 269
5
votes
2
answers
184
views
Global optimizers handling minimization of expressions like $\log{v}+\frac{1}{v}$
Consider the simple problem of maximum likelihood estimation of the variance of a mean zero normal distribution. The expression to be minimised is:
$$N \log{v}+\frac{1}{v}\sum_{n=1}^N{b_n^2},$$
where $...
- 269
2
votes
1
answer
313
views
Quadratic optimisation with $\ell_1$ constraints with CVXPY
Crossposted on Mathematics SE
I seek to minimize a convex quadratic objective subject to linear and $\ell_1$-based equality constraints. When I turn to CVXPY, an error is raised indicating that it ...
- 21
8
votes
1
answer
294
views
Distributed optimization problem
Consider the following optimization problem:
\begin{equation}
\label{eq:1}
\min_{x\in\mathcal X} \max_{i\in\mathcal I}\sum_{j\in\mathcal J} f_i(x_{(j)}),
\end{equation}
where $\mathcal{I}$ and $\...
- 215
3
votes
1
answer
547
views
Adding CVXPY abs to optimization problem turns out to be non-DCP
I have tried to solve an optimization problem using CVXPY library. This problem aims to minimize the distance between a vector of $n$ variables ($\beta$), which can be positive or negative real ...
- 39
2
votes
1
answer
168
views
Constraint raises DCP Error
I have defined a problem which will minimize the cost of to run a pump. That is defined as the objective of the problem.
...
- 141
4
votes
0
answers
68
views
Help with constrained or regularized optimization problem involving variable matrices and powers of matrices (or perhaps matrix logarithms)
I am attempting to solve the following optimization problem:
$$
\small\min_{A,B,C} \| Y_A - AX_A \|_F + \| Y_B - BX_B \|_F + \| Y_C - CX_C \|_F + \lambda_1 \|B - A^2\|_F + \lambda_2 \|C - A^4\|_F
$$
...
- 41
6
votes
0
answers
452
views
How to make constraints satisfy disciplined convex programming guidelines?
How do I turn my convex constraints (described below) into constraints that are DCP so that I can solve them in CVXPy? Is there some ``cheat sheet'' of standard tricks?
I'm trying to implement the ...
- 61
8
votes
1
answer
503
views
How to resolve this issue in multi-objective optimization?
I have the following multiobjective optimization problem. The objectives are non-conflicting.
The Optimization Problem:
$$\underset{\large{a^{(l)}_{c,u},f^{(l)}_{c,u},z_{l,t},l\in\mathcal{L}}}{\max}\...
- 2,397
8
votes
1
answer
321
views
Disciplined convex programming representation of $x\cdot\min x$
How can I reformat the problem below to follow DCP rules?
DCP rules are Disciplined Convex Programming Rules that allow convex programs to be solved. DCP
Is there a way to reformat the problem ...
- 309