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Comment by Rodrigo de Azevedo on Symmetric linear least-squares solution...

In general, ${\bf X}^+ {\bf X} \neq {\bf I}$. Perform some experiments with MATLAB using pinv

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Comment by Rodrigo de Azevedo on Symmetric indefinite matrix of fixed rank —...

You might want to take a look at slides 13-19 of Parrilo's The convex algebraic geometry of rank minimization (2009) [PDF]

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Comment by Rodrigo de Azevedo on Expressing an invertible sparse matrix as a...

Possibly related

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Comment by Rodrigo de Azevedo on On a matrix equation with Kronecker product

If $A$ is not the unknown, why vectorise, then? Why not write in matrix form without $\otimes$?

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Comment by Rodrigo de Azevedo on Solve NP-hard type problems with linear...

If you have a convex polytope whose vertices are integral, then you can solve integer programs via linear programming. But these are extremely special instances

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Comment by Rodrigo de Azevedo on Fundamental regions in convex programming

Would "feasible" be better than "fundamental"?

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Comment by Rodrigo de Azevedo on Norm bound in simultaneous stability to...

Is the operator norm the spectral norm?

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Comment by Rodrigo de Azevedo on Two questions about three circulant matrices

Have you tried writing the $\binom{n+1}{2}$ equations in $3n$ binary unknowns for, say, $n=3$?

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Answer by Rodrigo de Azevedo for Maximize the Euclidean norm of a matrix...

$$\mathrm A \mathrm x = \begin{bmatrix} \mathrm A_1 & \mathrm A_2 & \cdots & \mathrm A_n\end{bmatrix} \begin{bmatrix} \mathrm x_1\\ \mathrm x_2\\ \vdots \\ \mathrm x_n\end{bmatrix}$$where...

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Answer by Rodrigo de Azevedo for When is the following block matrix invertible?

The only easy case I can think of is where $\mathrm A_{ij} = \mathrm A_0$, where $\mathrm A_0$ is an invertible $n \times n$ matrix, for all $i,j \in [d]$. In this special case,$$\mathrm A =...

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Answer by Rodrigo de Azevedo for Nontrivial lower bound on the sum of matrix...

Let function $f : \mathbb R^{m \times n} \to \mathbb R_0^+$ be defined as follows$$f (\mathrm X) := \| \,\mathrm X \mathrm A^\top \|_\text{F}^2 + \| \,\mathrm X^\top \mathrm A \,\|_\text{F}^2 + \left(...

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Answer by Rodrigo de Azevedo for Is this inequality involving the Frobenius...

Given $\mathrm A \in \mathbb R^{m \times n}$ and $\mathrm B \in \mathbb R^{n \times p}$, let $\mathrm B \mathrm B^{\top} = \mathrm Q \Lambda \mathrm Q^{\top}$ be an eigendecomposition of $\mathrm B...

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Answer by Rodrigo de Azevedo for Quadratically constrained linear program...

We have the following (non-convex) quadratically constrained linear program (QCLP) in $\mathrm x, \mathrm y \in \mathbb R^n$$$\begin{array}{ll} \text{minimize} & \mathrm w^\top \mathrm x\\...

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Answer by Rodrigo de Azevedo for Nearest matrix orthogonally similar to a...

Using the spectral norm, we have the following optimization problem in matrix $\mathrm X \in \mathbb R^{n \times n}$$$\begin{array}{ll} \text{minimize} & \| \mathrm A \mathrm X - \mathrm X \mathrm...

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Answer by Rodrigo de Azevedo for Coupled Sylvester equations

We have two coupled linear matrix equations in $\mathrm X_1, \mathrm X_2 \in \mathbb R^{n \times n}$$$\begin{array}{rl} \alpha \, \mathrm A \mathrm X_1 + \mathrm X_1 \mathrm B &= \gamma \, \mathrm...

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Answer by Rodrigo de Azevedo for Finding Toeplitz matrix nearest to a given...

The set of $n \times n$ symmetric Toeplitz matrices is$$\left\{ x_1 \mathrm M_1 + x_2 \mathrm M_2 + \cdots + x_n \mathrm M_n \mid x_1, x_2, \dots, x_n \in \mathbb R \right\}$$where $\mathrm M_1,...

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Answer by Rodrigo de Azevedo for Large power of an adjacency matrix

Since the adjacency matrix $\mathrm A$ is not symmetric, we have a directed graph.Given a positive integer $k$, the $(i,j)$-th entry of $\mathrm A^k$ gives us the number of directed walks of length $k$...

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Answer by Rodrigo de Azevedo for How to calculate $y^T \mbox{diag}(A^T B A)...

$$\mathrm y^\top \mbox{diag}(\mathrm A^\top \mathrm B \,\mathrm A) \,\mathrm y = \sum_{k=1}^n \mathrm e_k^\top\mathrm A^\top \mathrm B \,\mathrm A \,\mathrm e_k \, y_k^2 = \sum_{k=1}^n \mathrm a_k^\top...

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Answer by Rodrigo de Azevedo for Upper bound on the number of non-zero...

Rephrasing:Given matrices $\mathrm A_1 \in \mathbb R^{m \times k}$ and $\mathrm A_2 \in \mathbb R^{k \times n}$, is there an upper bound on the number of nonzero entries of the $m \times n$ matrix...

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Answer by Rodrigo de Azevedo for Maximise singular value decay by sparse...

Maximizing the "decay" of the singular values could be thought of as minimizing the (numerical) rank. Hence, I believe that the original problem could be rephrased as follows:Given $\mathrm A \in...

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Answer by Rodrigo de Azevedo for Positive definite matrices diagonalised by...

Let $n \times n$ matrix $\rm A$ be symmetric and positive definite. Since $\rm A$ is symmetric, it is diagonalizable. Hence, there exists a (non-singular) matrix $\rm P$ such that $\mathrm A = \mathrm...

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Answer by Rodrigo de Azevedo for Calculate percentage of symmetry of a given...

Consider the following $2 \times 2$ matrix and its decomposition in a "natural" orthonormal basis.$$\begin{bmatrix} 1 & 1\\ 0 & 1\end{bmatrix} = \begin{bmatrix} 1 & 0\\ 0 &...

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Answer by Rodrigo de Azevedo for Solving system of bilinear equations

We have a system of $m$ bilinear equations in $\mathrm x, \mathrm y \in \mathbb R^n$$$\begin{aligned} \mathrm x^\top \mathrm A_1 \,\mathrm y &= b_1\\ \mathrm x^\top \mathrm A_2 \,\mathrm y &=...

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Answer by Rodrigo de Azevedo for Determining if some permutation of a vector...

Let $\mathbb P_n$ be the set of $n \times n$ permutation matrices. Given matrix $\mathrm A \in \mathbb R^{m \times n}$ and vector $\mathrm v \in \mathbb R^n$, we would like to find a permutation matrix...

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Answer by Rodrigo de Azevedo for Solving diagonal simultaneous quadratic...

We have the following system of quadratic equations in $\mathrm x \in \mathbb R^n$$$\mathrm A (\mathrm x \circ \mathrm x) + \mathrm B \mathrm x + \mathrm c = 0_m$$where $\mathrm A \in \mathbb R^{m...

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Answer by Rodrigo de Azevedo for Minimization problem involving the inverse...

Rephrasing slightly, given (symmetric) matrix $\mathrm A \succeq \mathrm O_n$, we have the following minimization problem in (symmetric) matrix $\mathrm X \succeq \mathrm O_n$$$\begin{array}{ll}...

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Answer by Rodrigo de Azevedo for Symmetric linear least-squares solution

Complementing Denis Serre's answer and rephrasing the original problem slightly, given tall matrices $\rm A$ and $\rm B$, we have the following quadratic program in square matrix $\rm...

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Answer by Rodrigo de Azevedo for Applications of mathematics in clinical setting

From the Automatic Control Laboratory at ETH Zürich, a project on automating anaesthesia:The first steps to introduce feedback control in anesthesia were undertaken more than ten years ago. The project...

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Answer by Rodrigo de Azevedo for Roots of determinant of matrix with...

Let $r_i := p_i - q_i$.$${\bf A} (x) := \begin{bmatrix} p_1 (x) & q_1 (x) & \ldots & q_1 (x)\\ q_2 (x) & p_2 (x) & \ldots & q_2 (x)\\ \vdots & \vdots & \ddots &...

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Answer by Rodrigo de Azevedo for Applications of knot theory to...

Some papers on knots and proteins:William R. Taylor, A deeply knotted protein structure and how it might fold, Nature, Volume 406, pages 916–919, August 2000.Michael A. Erdmann, Protein similarity from...

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Answer by Rodrigo de Azevedo for Prominent non-mathematical work of...

Doctor Ahmed Chalabi earned a PhD from the University of Chicago in 1969, founded Petra Bank in 1977, was sentenced in absentia in Jordan for bank fraud in 1992, and (allegedly) very successfully...

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Answer by Rodrigo de Azevedo for Complexity of convex quadratically...

Convex quadratically constrained quadratic programming (QCQP) can be reduced to semidefinite programming (SDP). Suppose that we are given the following convex QCQP in $\mathrm x \in \mathbb...

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Answer by Rodrigo de Azevedo for Mindset to understand category theory

You may want to take a look at Applied Compositional Thinking for Engineers (ACT4E), an ongoing graduate course at ETH Zürich:In many domains of engineering it would be beneficial to think explicitly...

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Answer by Rodrigo de Azevedo for Spectral radius of a rank-1 perturbation

Arguably, the simplest case is where the matrix $\bf A$ is symmetric and positive semidefinite (PSD) and ${\bf u} = {\bf v}$, which ensures that the eigenvalues of the rank-$1$ update are in $\Bbb...

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Answer by Rodrigo de Azevedo for Spectral radius of a rank-1 perturbation

To complement Christian's comment, since the spectral radius is upper-bounded by the spectral norm,$$\begin{aligned} \rho \left( {\bf A} + {\bf u} {\bf v}^\top \right) &\leq \left\| {\bf A} + {\bf...

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Answer by Rodrigo de Azevedo for Eigenvalues of $\operatorname{diag}({\bf v})...

The smallest eigenvalue can be found (approximately) via the following semidefinite program (SDP).$$ \begin{array}{ll} \underset {t} {\text{maximize}} & t \\ \text{subject to} &...

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Answer by Rodrigo de Azevedo for What phenomena are better modelled by SDE...

Since the Earth is not at zero degrees Kelvin, thermal noise is a reality that cannot be ignored. Much of electrical engineering is designing analog filters to remove as much noise as possible from...

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Answer by Rodrigo de Azevedo for Is there a name for matrices of the form...

Some call them currency exchange matrices. From Boyd & Vandenberghe's Introduction to Applied Linear Algebra:6.7Currency exchange matrix. We consider a set of $n$ currencies, labeled $1,\dots,n$....

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