All Questions
Tagged with linear-algebra convex-optimization
53 questions with no upvoted or accepted answers
7
votes
0
answers
1k
views
Closed-form solution of a linear programming question
Among all the probability matrices
\begin{equation*}
P =
\left(\begin{array}{cccc}
p_{00} & p_{01} & \ldots & p_{0,J-1} \\
p_{10} & p_{11} & \ldots & p_{1,J-1} \\
\vdots & \...
7
votes
0
answers
217
views
Characterizing matrices with rank constraint
Given matrix $M\in\Bbb\{0,1\}^{n\times n}$, is there a nice method to characterize $$\mathscr{D}[M]=\{Q\in\Bbb\{0,1\}^{n\times n}:\mathsf{rank}(M-Q)= \mathsf{rank}(Q),\quad M-Q\in\Bbb\{0,1\}^{n\times ...
7
votes
0
answers
209
views
Numerical linear algebra: how to compute $B^TC^{−1}B$ efficiently
Hi,
my question is similar to this one. I have to compute $B^TC^{−1}B$, where $C$ is a strictly positive definite $n\times n$ matrix and $B$ is $n\times m$.
The matrix $C$ is huge ($n$ up to a ...
6
votes
0
answers
136
views
Minimizing $\det(D)$ for all diagonal matrices $D$ that satisfy $D+B \succeq 0$
Let $A$ be an $n \times n$ real matrix and let $B$ be the block bipartite matrix
$$B = \begin{bmatrix} 0&A \\
A^{T}&0 \end{bmatrix}$$
I came across the following optimization problem, which ...
5
votes
0
answers
330
views
Best Approximation in Operator/non-Frobenius Norm
Since the Frobenius norm on matrices is generated by an inner product, solving the optimization/approximation problem of approximating an operator $X$ with a scalar multiple of another operator $Y$
$$\...
4
votes
0
answers
307
views
Derivative of rank $r$ approximation of matrix
Let $Y \in \mathbb R^{n \times c}$ and $r$ be an integer with $1 \le r \le \operatorname{rank}(Y)$. Consider the problem
$$\text{minimize} \|Y-X\|_{\text{Fro}}^2\text{ over }X \in \mathbb R^{n \times ...
4
votes
0
answers
206
views
Basin of Attraction
I have a function $F$ which is defined as follows:
$$
F(x) = \sum_{i=1}^N f(z_i^T x)
$$
where ${z_i}$ are known $m \times 1$ vectors, $x$ is an $m \times 1$ vector, and for $t\in \mathbb{R}$, $f(t) = \...
4
votes
0
answers
126
views
An inequality from the "Interlacing-1" paper
This question is in reference to this paper, http://annals.math.princeton.edu/wp-content/uploads/annals-v182-n1-p07-p.pdf (or its arxiv version, http://arxiv.org/abs/1304.4132)
For the argument to ...
3
votes
0
answers
122
views
Convex optimization upper bound for a non-linear optimization
Is there any good convex optimization problem based upper-bound for the following non-linear optimization problem?
\begin{align}
\max_{x_1,\ldots,x_N}&\quad \sum_{n=1}^{N} \log(1+\frac{x_n}{1+\...
3
votes
0
answers
116
views
convex approximation for a non convex function
Consider the function
$f\left( {{x_1},...,{x_M},{y_1},...,{y_N}} \right) = \left( {\sum\limits_{j = 1}^M {{\alpha _j}{x_j}} } \right)\left( {{e^{ - \sum\limits_{i = 1}^N {{\beta _i}{y_i}} }}} \right)$...
2
votes
0
answers
119
views
Seeking insights on bounded set positive solutions for a set of linear systems in $\mathbb{R}^n$
Before delving into my query, I'd like to provide some context. Consider a continuous function $f:\mathbb{R}^{k}\rightarrow\mathbb{R}^{m}$ and a compact set $\mathcal{B}\subset \mathbb{R}^{k}$ (...
2
votes
0
answers
178
views
Can we get the exact solution of large-scale quadratic programming problems (quadratic objective, linear inequality constraints) using KKT condition?
Crossposted at Computational Science SE
Consider a quadratic programming problem with the following format:
$$
\text{min} Q(x) = c^Tx+\frac{1}{2}x^TDx \\
$$
$$
\text{s.t.} Ax\leq b, \\
x\geq 0
$$
...
2
votes
1
answer
506
views
Effect of duplicated row on singular values and vectors
Let $\mathbf{A}$ be a $n\times n$ matrix with Singular Value Decomposition (SVD) $\mathbf{A}=\mathbf{U}\mathbf{S}\mathbf{V}$ and $\mathbf{a}_1$ be the first row of $\mathbf{A}$. What can we say about ...
2
votes
0
answers
618
views
block diagonal approximation of (SPD) matrix
I am interested in approximating a symmetric matrix in a block diagonal form, i.e. compute just some entries of the matrix located in blocks around the diagonal. Are there any theoretical guarantees ...
2
votes
0
answers
46
views
Notion of distance between linear programs
Consider the linear programming problem
\begin{align}
\max_{x}&~c^Tx \\~s.t.~~a^Tx &\leq B~,~0\leq x_i \le1
\end{align}
where $c$ and $a$ are $n \times 1$ given non-negative vectors. $B$ is a ...
2
votes
0
answers
298
views
Is the following map a diffeomorphism?
Context:
I'm working on a convergence theorem for an accelerated version of an iterative optimisation algorithm. At regularly-spaced intervals during the algorithm, a number of previous (...
2
votes
0
answers
210
views
projection of a matrix to the the space such that the diagonal elements are the greatest
Suppose there is a symmetric matrix $A$ in $\mathcal{S}^n$. I would like to compute the nearest symmetric matrix $X \in \mathcal{S}^n$ such that $X_{ij} \le X_{ii}$, $i ,j \in \{1,...,n \}$. In other ...
2
votes
0
answers
156
views
Optimization of quadratic form with band matrices
Let $A_1$ be the $N \times N$-matrix for which $a_{i,j} = 1$ for $i=j$ and 0 otherwise. Let $A_2$ be the matrix for which $a_{i,j}=1$ for $|i-j| \leq 1$ and 0 otherwise. Similarly define $A_3$ (which ...
2
votes
0
answers
299
views
Practical application of envelope theorem for linear programs
Assume that we have solved a (standard) linear program
$$
\text{minimize}_{x\in {\mathbb R^n}}\,\, c_0^Tx, \,\,\,\,\, \text{s.t. } A_0x \leq b_0,
$$
and would like to know how sensitive is the optimal ...
2
votes
0
answers
199
views
Constrained absolute orientation of 3D point sets
Let us assume we have two 3D point sets, $P=\{p_i\}$ and $Q=\{q_i\}$, and that we need to recover the transformation that takes $P$ as close to $Q$ as possible. In particular, I am interested in roto-...
2
votes
0
answers
210
views
Finding optimal linear transformation for intersection of convex polytopes
I previously posted this on MathSE and am now trying here.
I have the following situation, as shown in the following diagram:
$W=\{w_i\}_{i=1..|W|}$ is a set of vertices (show in diagram in blue) ...
1
vote
0
answers
37
views
When does an optimal input sequence for a discrete-time system exist?
Suppose an LTI discrete-time system is given by the equations
$$
x_{k+1} = Ax_k + Bu_k,\\
y_{k} = Cx_k + Du_k
$$
with $x_k\in\mathbb{R}^{m}$, $y_k\in\mathbb{R}^{n}$ and $u_k\in\mathbb{R}^{p}$ and $\...
1
vote
0
answers
73
views
What is the closed form of a polyhedral cone's dual cone?
A polyhedral cone can be defined as
$$
\mathcal{K} = \{x~|~Ax\preceq 0\},
$$
where $A \in \mathbb{R}^{m \times n}$, $x\in \mathbb{R}^n$ and $\preceq$ denotes component-wise less than and equal to.
The ...
1
vote
0
answers
204
views
Matrix relative condition number
I've been working on some distributed optimization problems and faced a bit of a challenge with the following question.
Given $A_1, A_2, .., A_m \in M_n({\mathbb{R})} $ symmetric positive definite ...
1
vote
0
answers
98
views
Solution of a simple optimization problem
Let $\mathbf{U}_1$ and $\mathbf{U}_2$ be two arbitrary unitary matrices and $\mathbf{D}$ be a diagonal matrix. What is the solution of the following optimization problem?
\begin{align}
\min_{\mathbf{...
1
vote
0
answers
52
views
When the summands of a positive definite matrix are positive definite
Let $A,B$ be two real symmetric matrices. Let $C = A+B$ be a positive-definite matrix. Write $C>0$ for $C$ being positive-definite. Suppose that $A>0 \implies C>0$ and $B > 0 \implies C>...
1
vote
0
answers
176
views
Maximum mutual information of random unitary transformation
Let $\mathbf{U}$ and $\mathbf{V}$ be random unitary matrices independent of random input vector $\mathbf{x}$. Moreover, $\mathbf{z}$ be random iid complex Gaussian vector with zero mean and identity ...
1
vote
0
answers
139
views
Subgradient chain rule
Suppose $$F:\mathbb{R}^n \to \mathbb{R},\; F(x)=\mathrm{max}_\mathrm{eig}(C-\mbox{diag}(x)).$$
I am trying to find a subgradient of $F$ at $x_0$. A subgradient of $\mathrm{max}_\mathrm{eig}$ is given ...
1
vote
0
answers
150
views
Minimax optimization of diagonal entries of function of matrix
Let $\mathbf{A}$ and $\mathbf{U}$ be arbitrary complex $M\times N$ and $N\times M$ matrices, respectively. Let denote superscript $(\cdot)^{\dagger}$ and $(\cdot)^{\mathrm{H}}$ as pseudo-inverse and ...
1
vote
0
answers
208
views
Maximum theorem with linear constraints. On parametric continuity of in optimization
Given
\begin{align}
s(\theta)= &\text{arg min}( g( \boldsymbol{x}) ) \\
\text{subject to }& \boldsymbol{A}(\theta) \boldsymbol{x} = \boldsymbol{b}(\theta) \\
&c_1 \le x_i \le c_2 , ...
1
vote
0
answers
163
views
Properties of vector combinations in the non-negative orthant
Given a vector $x \in \mathbb{R}^{n}_{0+}$ such that $x = \sum^{k}_{i=1} \alpha_{i}v_{i}$, the vectors $(v_{1},...,v_{k}) \in \mathbb{R}^{n}_{0+}$ are an independent set, $k < n$, and $\alpha_{i} &...
1
vote
0
answers
138
views
Matrix completion in $2\times2$ case by nuclear norm minimization to guarantee rank $1$?
Does fixing diagonal entries and minimizing nuclear norm under weighted sum of entries conditions produce a rank $1$ matrix? I think the answer for this is no.
At least could it be true in $2\times2$ ...
1
vote
0
answers
483
views
minimize norm of matrix product
I have the matrix Product $PAP^H$ and I need to minimize $\|(PAP^H)^{-1}\|^2$ (over $P$ and Frobenius norm).
$A$ is a positive definite Hermitian matrix and $P$ has the structure
$$P=\left[\begin{...
1
vote
0
answers
481
views
psd condition for matrix completion
The nuclear norm minimization for the matrix completion problem is given by
\begin{align}
\textrm{minimize } \quad &\|X\|_{*}\\
\textrm{subject to } \quad & X_{ij}=M_{ij} \quad \forall (i,j)...
1
vote
0
answers
1k
views
Analytic formula for minimizing the maximum inner product of a set of vectors
Given $x_j\in\mathbb{R}^n$, $j=1,\ldots,p$, find
$$
\widehat{w} \in \arg\min_{\Vert w\Vert=1}\max_{1\le j\le p} |\langle w,x_j\rangle|.
$$
I am also interested in the special case where we further ...
1
vote
0
answers
227
views
Find optimal value for a regularization parameter in generalized eigenvalue problem
Consider the generalized eigenvalue problem :
$ \Sigma_{XY} \Sigma_{YX} {W} = \lambda \Sigma_{XX} {W} $
where $\Sigma_{XX} $ and $\Sigma_{XY}$ are sample covariance matrices are of the matrices $X$...
1
vote
0
answers
100
views
Changing a nonlinear equality constraint into some conic inequality plus rank constraint
If we have a constraint optimization problem in which one of our constraint is $\prod\limits_{k = 1}^N {\left( {x - {a_k}} \right) = 0} $ . How could this nonlinear equality condition be changed into ...
1
vote
0
answers
1k
views
Diagonal entries of a Cholesky factorization
Let $I$ denote an identity matrix, $E$ denote the all-one matrix of dimension $k\times k$ and $c$ some positive real number. Define $X=B(I-cE)B^T$ where $B$ is given by
$B:=\begin{pmatrix}
1 &\...
0
votes
0
answers
52
views
What are the injective embeddings of R^d into the cone of (semi-) positive definite matrices of dimension d?
How can we characterize the set of all injective functions from $\mathbb{R}^d$ to the set of all symmetric positive definite matrices of dimension d?
0
votes
0
answers
51
views
Minimizer of forward and reverse Kullback-Leibler divergence with sum constraints on marginals
Consider minimization of the Kullback Leibler divergence between two discrete distributions $p$ and $q$:
\begin{align*}
D_{KL} \left( p \parallel q \right) = \sum_i p_i \log \left( \frac{p_i}{q_i} \...
0
votes
0
answers
72
views
Minimizing the Spectral Norm of the Hadamard Product of a Quadratic Form Using CVX
I am trying to use CVX to minimize the spectral norm of the Hadamard product of two matrices, one of which is in quadratic form. Specifically, I am trying to minimize $\|{\bf A} \odot {\bf XX}^H\|_2$, ...
0
votes
0
answers
30
views
Application of greedy approach for optimization
I want to maximize an objective given by $$\max_{\{q_n,p_n\}} \sum_{n=0}^\infty (\alpha_1 - \beta_1 n) p_n + (\alpha_2 - \beta_2 n) q_n$$
where $\alpha_1 > \beta_1 >0$ and $\alpha_2 > \beta_2 ...
0
votes
0
answers
177
views
Given optimality of L1 norm, prove that absolute value of sum of a vector with proper sign is less than 1?
Problem:
Given a domain $\mathcal{D}\subset\mathbb{R}^{l}$, we can find $l$
points $\boldsymbol{v}_{i}\in\mathcal{D}$, $i=1,\cdots,l$. Each
point is a column vector with dimension $l\times1$. They ...
0
votes
0
answers
156
views
Optimal solution of complex optimization problem
Let $Q(x)=a(x)e^{jb(x)}$ be a complex function of $x$. We want to approximate this function with $R(x)=\alpha e^{jx\beta}$ such that
\begin{align}
\text{arg}\min_{\alpha,\beta} \int_{-\frac{A}{2}}^{\...
0
votes
0
answers
124
views
The best unitary matrices that approximate a matrix product
Let $\mathbf{A}$ be an arbitrary $N\times N$ complex matrix. Moreover, $\mathcal{U}_1$ and $\mathcal{U}_2$ are distinct subsets of all unitary matrices. Suppose the matrices $\mathbf{U}_1$ and $\...
0
votes
0
answers
137
views
Any technique for linearization, or linear approximation?
Consider the following Matrix constraint:
$$
\begin{bmatrix} -U+\psi\Sigma_b^{-1} & V \\ V^T & -V^TU^{-1}V+\tau_2 -\psi \end{bmatrix} \leq 0
$$
where $\Sigma_b$ is a known positive definite ...
0
votes
0
answers
41
views
Iterative algorithm for obtaining similarity
Let $x_1,x_2,\ldots,x_M$ be $M$ non-negative variables. Moreover, assume that $f_m(x_m)=\frac{x_m}{1+\sum_{n}\beta_{n}^{(m)}x_n}$ be $M$ fractional functions with non-negative constants $\beta_{n}^{(m)...
0
votes
0
answers
136
views
Finding a specific solution to $X^T\Sigma X = D$
I'm looking to solve for a specific $X$ in the following equation:
$$X^T\Sigma X = D,$$
where $\Sigma \succ 0$, $D$ is a diagonal matrix with strictly positive entries, and all matrices are square. It ...
0
votes
0
answers
121
views
Closed form solution to an equation
Let $X \in \mathbb{R}^{n \times d}, w \in \mathbb{R}^d, y \in \{\pm 1
\}^{n}, \alpha \in (0, 1)$. Consider the equation
$$ X^{\top}(Xw-y)+\alpha \|w\|_{2}X^{\top}\operatorname{sign}(Xw-y)+\alpha\frac{...
0
votes
0
answers
614
views
Hadamard / matrix product adjoint
First of all I would like to thank everyone over here at mathoverflow for their amazing generosity and help (for both pros and newbies like myself).
I apologize if this question seems dumb; I'm a new ...