Skip to main content

All Questions

Filter by
Sorted by
Tagged with
2 votes
1 answer
170 views

Equivalence of minimizing trace and determinant over matrix quadratic form in multivariate regression

Consider the multivariate regression model $$Y = XB + E$$ where $Y$ is $n \times p$ and corresponds to the dependent variables, $X$ is $n \times k$ and corresponds to the independent variables, $B$ is ...
respectableuser1's user avatar
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 $\|{\bf A} \odot {\bf XX}^H\|_2$, ...
usergh's user avatar
  • 43
5 votes
3 answers
496 views

Eigenvectors that are tensor products?

Consider a fixed $N\times N$ positive definite symmetric matrix $A$. Assume $N=d^r$ for some $d,r\geq 1$. I wonder if one can find a closed formula for the maximizer/maximum of the function $$f(x):=\...
Adrien Hardy's user avatar
  • 2,135
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: $$ \text{min} Q(x) = c^Tx+\frac{1}{2}x^TDx \\ $$ $$ \text{s.t.} Ax\leq b, \\ x\geq 0 $$ ...
ximeng fan's user avatar
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}}^{\...
Math_Y's user avatar
  • 287
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 ...
TrevLou's user avatar
  • 11
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{...
Math_Y's user avatar
  • 287
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 $\...
Math_Y's user avatar
  • 287
1 vote
1 answer
336 views

A close-form solution for a simple quadratic optimization problem

Is there any closed form solution for the following optimization problem: \begin{align} &\min_{\mathbf{X},\alpha} \mathrm{Tr}[(\mathbf{A}-\mathbf{B}\mathbf{X})(\mathbf{A}-\mathbf{B}\mathbf{X})^{\...
Math_Y's user avatar
  • 287
1 vote
1 answer
234 views

Log Fractional optimization problem

Let $\mathbf{x}$ be a vector of $N$ variables. Then, how can I solve the following optimization problem? \begin{align} \max_\mathbf{x}&\quad \sum_{n} \log(1+\frac{x_n}{\alpha+\sum_{m}\beta_m^{(n)}...
Math_Y's user avatar
  • 287
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+\...
Math_Y's user avatar
  • 287
0 votes
1 answer
153 views

Difference of two optimization problem's optimal value

Let we have two following optimization problems: \begin{align} \text{(P1)}\quad \alpha_1 = \max_{x_1,\ldots,x_M} &\quad \sum_{m=1}^{M}\log(1+f_m(x_1,\ldots,x_M))\\ \textrm{s.t.} &\quad \...
Math_Y's user avatar
  • 287
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 ...
Math_Y's user avatar
  • 287
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 ...
dineshdileep's user avatar
  • 1,421
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{...
user145905's user avatar
7 votes
1 answer
373 views

Is the solution of this optimization problem always positive semidefinite?

We are given a set of unit vectors $U \subset \mathbb{C}^n$ which spans the space $\mathbb{C}^n$. Given another unit vector $x$, consider then the following optimization problem: $$ \sup_H \left\{ x^*...
F.G.'s user avatar
  • 73
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 $2\times2$ ...
Turbo's user avatar
  • 13.9k
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{...
F Researcher's user avatar
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 ...
Pew's user avatar
  • 263
4 votes
1 answer
2k views

lipschitz constant of a multivariate function

I have a function $f:\mathbb{R}^{50} \rightarrow \mathbb{R}$ and I need to compute the Lipschitz constant of $f$ to solve an optimization problem using a specific algorithm. Does any one have ...
user32429's user avatar
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 ...
Turbo's user avatar
  • 13.9k
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 ...
Parsis's user avatar
  • 33
0 votes
0 answers
80 views

Finding gradient of an optimization

I am trying to find the gradient of the following optimization problem and then add to objective, but I got some trouble in computing. Could you please help me? Assume that we have an optimization ...
Royeh's user avatar
  • 161