Questions tagged [semidefinite-programming]

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1answer
51 views

How to optimize nuclear norm subject to positive semidefinite constraints?

For finite dimensional symmetric positive semidefinite matrices $A$ and $B$, I would like to solve \begin{align}&\min |X - A|_1 \\ &\text{subject to}\\ &X \preceq B \\ &0 \preceq X\...
3
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2answers
252 views

log(det(X)) in Semidefinite Programming

I have been solving problems of the form $$max \ log(det(A)) \\ s.t. \ A = A^{T} \succeq 0, \\ p_{i}^{T}Ap_{i} \leq b_{i}$$ where $b_{i}$ and $p_{i}$ are input vectors (to be clear there is more than ...
4
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1answer
178 views

Underdetermined Minimum Volume Enclosing Ellipsoid

Given three vectors in $\mathbb{R}^{512}$, my task is to compute a Minimum Volume Enclosing Ellipsoid (MVEE). I have tried Kachiyan's algorithm, but it requires at least as many vectors as there are ...
-1
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1answer
25 views

Semi-Definite relaxation of non-linear constraint?

I am implementing an optimization problem using semi-definite approach. One of my constraints is of following form $ trace(A∗X)−(k∗trace(A∗X))+(k∗\sqrt {(trace(B∗X)} )==0$ where k is a constant, A ...
3
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0answers
86 views

First order methods for a large scale semidefinite program

I am interested in solving the following semidefinite optimization problem: \begin{equation} \begin{split} \underset{X,\lambda}{\rm maximize} \;\;\;\;&\lambda^Tc \\ &-\mathbb{I} \le X \le \...
2
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0answers
54 views

Looking for a version of DSDP that is less prone to integer overflows than the original

I am working on a problem that involves semidefinite programming (constrained optimization of fairly large positive definite matrices). The software is written in C++ and calls DSDP 5.8 to solve the ...
2
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1answer
207 views

What is the fastest way to solve Ax=b (subject to constraints and an absolute term)

I am trying to solve/optimize $Ax=b$ in the least squares sense subject to box constraints; a few (less than 5) equality/inequality constraints; and an absolute function penalty (or some other ...
4
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0answers
55 views

Obtainting KKT for QSDP for the trace inequality constraint

I am working on developing my own solver(for implementation on hardware), based on IPM for following problem: \begin{equation} \begin{split} \min_{X} \; \frac{1}{2}&\|X\|_F^2 + trace(CX)\\ \text{...
4
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1answer
316 views

Imposing special structure on Positive Semi-Definite matrix

I am trying to implement the algorithm described in reference 1 using cvxpy. However I am struggling to constrain the matrix $Z_j$ as described in equations (33-35)....
3
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1answer
333 views

Translating a nuclear norm constraint to an LMI constraint

I'm attempting to solve a convex optimization problem where one of the constraints is $$\|M\|_* \leq a$$ where $\|M\|_*$ denotes the nuclear norm of matrix $M$. I'm using CVXOPT in Python to solve ...
1
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1answer
222 views

How to deal with quadratic constrain in semidefinite programming

I am using CVX to solve an optimization problem. One of my constraints in the problem is $$M \succeq \eta {\eta}^T$$ where $M$ is a square matrix and $\eta$ is a column vector (both $M$ and $\eta$ ...
0
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1answer
103 views

Express SDP problem in CSDP

I am trying to use CSDP and am struggling with this. Consider for example the SDP problem proposed by prof. Borchers here. Namely: $$\max_{A,z} \sum_{i} z_{i}\quad\text{subject to}\quad\mbox{tr}(P_{...
4
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2answers
147 views

Maximization variant of semidefinite programming (SDP)

Consider the following program: $$\max_{\pmb a} \sum_i z_i\\ u.c. \pmb a \pmb P_i\pmb a^\top\geq z_i$$ where $\pmb a \in\mathbb{R}^p$ and the $\pmb P_i$ are all symmetric positive semidefinite ...
1
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1answer
44 views

How to compute $\mathrm{proj}_{SDP}(C\odot X)./C$ without numerical problems?

I have a matrix, $X$, it is symmetric. I project $C \odot X$ and $D\odot X$ to semidefinite cone. $C$ is a Gramian matrix with some elements near zero and of course semidefinite, with one row and ...
0
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1answer
45 views

Express the $\gamma_{2}^{\epsilon}$ SemiDefinite program in a form that is acceptable by SDPT3

I'm trying to express the following semidefinite program: for given $A \in R^{m \times n}$ and a scalar $\epsilon \in (0,1)$, \begin{align} &\gamma_{2}^{\epsilon}(A):= \min\,t\\ &\text{...
0
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1answer
379 views

Storage complexity of SDP solver SCS

This is a follow up question to this question. Consider the following SDP in standard form: \begin{align} &\min_{X\in S^n, X>0} \operatorname{tr}(AX)\\ &\mbox{subject to}\; \operatorname{...
4
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1answer
373 views

Best platform for complex SDPs with n and m around 5-15K?

I am looking to solve a class of SDPs with complex entries, with the semi-definite cone $S^n$, $n$ around 5000 to 15000. Also, $m$, the number of equality/inequality constraints is close to $n$. I ...
4
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1answer
158 views

Rank constrained SDP

I would like to optimize a function of the following form: \begin{equation} \sum_{i,j=1}^N c_{i,j} \mathbf{x}_i \cdot \mathbf{x}_j, \end{equation} where $\mathbf{x}_i \in \mathbf{R}^d$. Is it possible ...
5
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1answer
935 views

Fast projection onto semidefinite cone

Lots of algorithms for semidefinite programming make use of the Frobenius projection onto the cone of semidefinite matrices: $$\mathcal{P}(A) = \min_{X\succeq0} \|A-X\|_{\mathrm{Fro}}^2.$$ Let's ...
5
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1answer
624 views

Semidefinite Programming Using CVX in Matlab

I have the following optimization problem $$\begin{align} &\min_{ X_{1}, \dots,X_{k} } \max_{ \theta, \phi } \left|P_{d}(\theta,\phi) - \sum_{k=1}^K \operatorname{Tr}(a_{k}(\theta,\phi)a_{k}^{H}...
0
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1answer
269 views

How to write Goemans-Williamson MAX-CUT relaxation as SDP

Let W be a graph Laplacian (symmetric diagonally dominant, and thus PSD), and X the matrix variable. Let $<A,B>=Tr(A^TB)$. $$\text{Maximize}\;\; \displaystyle\sum_{i,j} w_{ij}(x^{(i)}\cdot x^{(...
2
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2answers
2k views

Solve large dense positive-definite linear system

Which method should I choose to solve a large (~20 000 variables) dense symmetric positive-definite, possibly ill-conditioned, system of linear equations? The system will be solved for two vectors. I'...
7
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3answers
1k views

Nearest positive semidefinite matrix to a symmetric matrix in the spectral norm

So I have a symmetric matrix $A$ and I would like to solve the optimization problem, $$\hspace{2.5mm}\text{Minimize}\;\; \|A-S\|_2$$ $$\hspace{-5mm}\text{Subject to}\;\; S\geq0.$$ $A$ is given and $S$ ...
10
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3answers
2k views

Do they use semidefinite programming in industry?

I can't see any mention of it in job listings. I've seen mentioned integer programming, MIP, mixed-integer nonlinear programming, LP, dynamic programming etc., but no SDP. Is it much trendier in the ...
0
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1answer
464 views

Fastest linear solver for sparse positive semidefinite, striclty diagonally dominant matrix

What is the state of the art for fastest linear solver for sparse, positive semi definite and strictly diagonally dominant matrix with N varies from ~700 to ~3000, and about a 1/16 of the matrix is ...
2
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1answer
111 views

How can I convert this SDP constraint?

I have the following SDP problem: max: $Tr(CX)$ subject to: $X \geq 0, I - X \geq 0$. I want to convert it into the standard form specified by CSDP (I'm using the callable C interface), which is: ...
2
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1answer
618 views

Efficient formulation of an SDP involving L1 norm

I am trying to reformulate the following problem to be solved efficiently (by MOSEK) $$ \min_{X} \text{Tr}(CX)+\lambda\sum_{i,j}|x_{i,j}| \\ \text{s.t.} \quad ||X||_F\le1 \quad \text{and} \quad X\ge 0 ...
2
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2answers
852 views

How to put following SDP probllem into an equality standard form

I have the following semi-definite programming problem that I want to put in a standard form in order to estimate its order of complexity. The problem is: $$ \max_{x_{i,j}}\sum_{i \in \mathbf{F} }^{...
5
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1answer
413 views

How to transform such an SDP to standard form

I plans to use CSDP to solve the following semi-definite problem: $$\min_{B, \beta}\operatorname{trace}(CB) \\ \text{s.t.} \ \operatorname{trace}(AB)=1 \\ \beta\geqslant 0 \\ \begin{bmatrix} 1 & \...
1
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0answers
219 views

Sign or cardinality constraint when solving for sparse signal

I'm currently learning about using linear and semidefinite programming to find sparse solutions to problems. In particular, finding sparse solutions where the sampling functions are sinusoidal (...
4
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3answers
431 views

How to implement this trigonometric polynomial maximum finding semidefinite program

Hi All, I posted this on the math.se site, but this may be a better location. I need a method of finding the maximum of a real valued trigonometric polynomial where I can trade accuracy for speed. ...
4
votes
1answer
595 views

What is a vector programming problem?

In a note: semi-definite programming is equivalent to vector programming. ... A Vector Program is a Linear Program over dot products. In Boyd's Convex Optimization, a vector optimization ...