Nonlinear objectives, nonlinear constraints, non-convex objective, non-convex feasible region.

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25 views

max min of ratio of quadratic forms

Consider the optimization over two vectors $x$ and $y$ $$\max_{x,y} \min\left(\frac{x^TAx}{y^TAy},\frac{y^TBy}{x^TBx}\right)$$ for two positive definite matrices $A$ and $B$. This problem can be ...
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0answers
25 views

Integer Programming with MATLAB [on hold]

i'd like to know how to solve in MATLAB the following integer optimization problem : where the matrices X and Y are given. The matrice D must be a diagonal matrix where its diagonal elements are 0 ...
0
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1answer
48 views

Quadratically constrained quadratic programming/optimization involving piece-wise function

I have a quadratically constrained quadratic programming/optimization problem involving kind-of piece-wise quadratic functions $f_n (x_m)=a_{n,m} (x_m-\theta_n)^2$, if $|x_m-\theta_n|<c$; ...
0
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0answers
14 views

Finding orthogonal basis with constraint

Is there any fast algorithm that output an orthogonal basis $e_i,i\leq n$ of $R^n$ with $e_i\in V_i$? Where $V_i,i\leq n$ are given linear subspaces of $R^n$. And is there any condition on $V_i,i\leq ...
0
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0answers
41 views

Largest instance of highly nonlinear benchmark functions (e.g. Rastrigin function)

What is the largest instance size (number of variables) ever numerically solved for highly nonlinear (continuous, not combinatorial) optimization benchmarks functions, such as Rastrigin, Schwefel or ...
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22 views

Dennis More' Superlinear Convergence_refrences request

Why in the proof of superlinear convergence of restricted broyden class (for the unconstrained optimization) we need the bounded deterioration condition for the approximation of all the true hessian ...
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0answers
27 views

Which algorithm is most efficient for a specific QP problem

I have a QP problem of the following kind: $\min_{\alpha\in\mathbb{R}^n}\frac{1}{2}\alpha^T M \alpha - p^T\alpha$ s.t. $l\leq \alpha \leq u$ The matrix $M$ is symmetric and positive definite and of ...
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0answers
32 views

Characterization of eigenvector

Let's say we have the following optimization problem. (All the $\Sigma_{ii}$'s are positive definite.) $\max u^\top \Sigma_{12} v\quad$ $\text{subject to}\quad u^\top \Sigma_{11} u = 1\quad and\quad ...
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1answer
92 views

Why polynomial $\psi^\top(t) A^{-1} \psi(t)$ attains maximum on $[-1, 1]$ at $t = \pm 1$, where $\psi_k(t) = t^k$?

Problem. Let $\psi(t) = (1, t, t^2, \ldots, t^{p-1})^\top$ - a polynomial basis. Suppose there is a matrix $$ A = \int_{-1}^1 \psi(t) \psi^\top(t) dt, \ \text{i.e. } \ A_{ij} = [2 \, | \, i+j] ...
4
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2answers
69 views

About optimization with Renyi divergence

Can someone link me to some pedagogic example of computing the Renyi divergence between two discrete/continuous distributions? Like examples where someone has been able to obtain a neat closed form ...
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47 views

About identifying a few diagrams

Please have a look at these beautiful seminar slides, https://math.berkeley.edu/~bernd/coimbra1.pdf Can someone kindly identify the algebraic description of the spectrahedron that is drawn on slide ...
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55 views

Hessian matrix positive definiteness (concavity test) [closed]

I have a rather simple scenario based optimization problem: Maximize $$ Q_1{_s}(A_1{_s}-Q_1{_s}-bQ_2{_s})+ Q_2{_s}(A_2{_s}-Q_2{_s}-bQ_1{_s})-[(Q_1{_s}-K_1)^+ + (Q_2{_s}-K_2)^+]c $$ subject to ...
3
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0answers
153 views

Can the following system of equations be solved analytically/in a closed form?

From a constrained non-linear maximization problem I obtained the following system of equations: $a_1=\frac{1+a_3-\sqrt{a_2a_3}\sqrt{v_1}}{1+\sqrt{\frac{a_3}{a_2}}\sqrt{v_1}}$ ...
3
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1answer
112 views

Global minimum of nonlinear least square

We have a continuous and differentiable function $f(\cdot)$ that maps from $R^n$ to $R^n$. We are trying to solve a nonlinear least square problem: Minimize $J(x)=\Vert f(x)-z\Vert^2$ subject to box ...
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0answers
175 views

A contractive mapping which I don't understand

Given a matrix $Y$ and a vector $c$ define the following iteration $\hat{c} = f(c)$, where each element of $\hat{c}$ is given by $$\hat{c}_{\ell} = \frac{\sum_k ...
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0answers
48 views

Separable Least squares - is there a notion of conjugate directions?

I have a general question. Suppose I have the following to optimize $$\|Y-A(\mathbf{x})B(\mathbf{y})\|^2$$ where $Y$ is a vector, $A(\mathbf{x})$ is a matrix that depends on a vector $\mathbf{x}$ in a ...
4
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0answers
62 views

What does the Von Neumann's stability analysis tell us about non-linear finite difference equations?

I've asked this question on computation science stackexchange, but it did not receive any answers so I have decided to ask it here as well. I am reading a paper [1] where they solve the following ...
0
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1answer
71 views

a sum of ratios of quadratic forms

I have the following function that I would like to optimize over the value A $$f(A)=\sum_k \frac{\mathbf{y}_k^H\left[\begin{array}{cc} 1&0\\ 0& A \end{array} ...
2
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0answers
27 views

$\min \sum_i f(w^i) +\sum_j g(w_j)$ wrt col and rows of a matrix

I've got an unconstrained optimization problem, and all function involved can be regarded as differentiable as you like. The variable is a rectangular matrix $M$. Target Function is $\sum_i f(w^i) ...
2
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0answers
61 views

Conditions under which the dual function is self-concordant

Consider the following optimization problem \begin{align} \min_{x}&\quad f(x)\\ \nonumber \text{subject to } \quad&h_i(x) = 0,\,i=1,\ldots,m\\ \nonumber \quad&x\in ...
3
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0answers
44 views

measure of an image under an argmax function

I am trying to find any techniques to analyze the measure of an image of a set under an argmax function. For example, let $\Omega\subset\mathbb{R}^n$ be compact and $\phi:\Omega\to\mathbb{R}$ be ...
2
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1answer
114 views

A graph assignment problem

Consider bipartite graph with vertex set $V_1\cup V_2$ where $|V_1|=\frac{n(n-1)}2$ and $|V_2|=n$. The vertices in $V_1$ all have degree $2$ and connected to two vertices in $V_2$. The vertices in ...
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1answer
99 views

Generalized Lax-Milgram for Weak Formulation of 1D Linear Schrodinger

I am interested in the variational formulation of the 1D Schrodinger equation: $i u_t- \beta u_{xx} = 0 $ and $u(x,0)=u_0(x)$ which upon integration by parts yields: $i(u_t,v) + \beta (u_x,v_x) = 0$ ...
2
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0answers
55 views

What's the advantage of majorization-minimization (MM) algorithm [closed]

The majorization-minimization (MM) algorithm is a framework for convex and nonconvex optimization. When applied to nonconvex optimization, the MM algorithm solves a sequence of convex problems to ...
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0answers
42 views

Nuclear norm maximization

I am trying to solve a nuclear norm maximization problem: $$\arg \max_{Q \in O(n)} \|WQV^T\|_*$$ where $Q$ is an $n \times n$ orthogonal matrix and $W$ and $V$ are real $d \times n$ matrices. I've ...
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2answers
93 views

Is finding a local minimizer of a NP-hard optimization problem is still NP-hard [closed]

I was wondering if for a NP-hard optimization problem, I only want to find its local minimizer, is it still NP-hard or NP-hard is only true when trying to find a global minimizer?
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0answers
18 views

Deterministic global solution to find the Optimal-knot placements for continuous piecewise linear functions to fit nonlinear data

I have been searching lately for a deterministic global technique to linearize a nonlinear function with continuous piecewise linear regions. I've a univariate nonlinear function y=f(x). where f(x) ...
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1answer
90 views

A bound on the number of bilinear functions needed in order to obtain the minmax

For $n\in\mathbb N$, let $\Delta(n)=\{x\in\mathbb R^n:x_i\geq 0, \sum_ix_i=1\}$ be the set of probability vectors in $\mathbb R^n$. Is there a function $m:\mathbb N\to\mathbb N$ such that for any ...
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0answers
46 views

Question on solving an optimization problem using Variable splitting and ADMM

Tell me if I have found the right approach to the following optimization problem: $$ min_{x} \frac{1}{2}\left \| Ax-b \right \|_2^2 \\ s.t. \ \ \Phi v=x \ , \ {x^T(1-x)}=0 $$ $A$ and $\Phi$ ...
1
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1answer
73 views

Envelope theorem for second derivative

I am maximizing a function $f(x,z)$ on $x$ ($z$ is treated a parameter in the maximization). The function $f$ is strictly concave on both variables. I know how to use the envelope theorem for the ...
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0answers
34 views

Is this QCQP convex or nonconvex

\begin{equation} \begin{split} \min_{x\in \mathbb{R}^n}\:f(x)=(1/2)x^{T}Q_0x+c_0^T x \end{split} \end{equation} s.t. $$ g_i(x)=\frac{1}{2}x^T Q_ix-lmax_i\leq0,i\in\{1,...,m/2\} $$ $$ ...
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1answer
76 views

$0/1$ programming multiple quadratic constraints

If we have an $n$-variable rank $n$-linear system it is clear we can find whether there exists a $0/1$ solution in polynomial time. If we have an $n$-variable degree $2$ system how many constraints ...
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0answers
31 views

solution of an infinite horizon optimization problem

Give the following formulation: $\min_{\{x_s(t):\forall s,t\}} \sum_{s \in \mathcal{S}} \mathbf{1}\left(\lim_{T\rightarrow \infty} \frac{1}{T} \sum_{t=1}^T \frac{y_s(t)}{x_s(t)}\leq 1\right)$ $s.t. ...
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0answers
30 views

Finding the Lagrangian dual problem for a quadratic programm [closed]

I've problems to find the Lagrangian dual problem to \begin{align*} \min \limits_{x \in \mathbb{R}^n} \; \frac{1}{2} x^{ T} Q x + q^{T} x \\ \text{s.t.} \quad Ax &=b \\ x &\geq 0 ...
0
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1answer
57 views

Solving a nonlinear optimisation problem

I have the following nonlinear optimisation problem arising in my model. $$\min \sum_{k=0}^{N-1} (\tau-t_k)^+\quad \text{ s.t. } {\mathbf{x}^\top\mathbf{w}\le W,\ \mathbf{x}\ge0}, t_k=t_{k-1}+x_k ...
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0answers
168 views

Minimization of nonlinear integral operator

See also on MSE. For non-negative self-adjoint traceclass operators $0\leq T \leq 1$ with $\mathrm{tr}T^\alpha=N$ on the Hilbert space $L^2(\mathbb{R}^3)$ s.t. $\operatorname{tr}(-\Delta ...
2
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0answers
86 views

Solve non-linear Optimization Problem [closed]

I have to find $x$ that minimizes: $$ \sum_{k}(x^H\textbf A_kx - b_k)^2$$ where $A_k$ are 4 x 4 positive definite matrices ($A_1, A_2,...A_k$), $x$ is 4 x 1 vector and $b_k$ are scalars ...
4
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0answers
177 views

Comparison of Constrained Optimization Methods

I am trying to solve a constrained optimization problem using filter methods and came across two papers on the topic that I am having some problems with. The original filter method paper is the ...
5
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0answers
80 views

max-min optimization problem

I'm curious if there is any nice way to approach solving the following kind of optimization problem. Given a $n \times m$ matrix $A = (a_{ij})$, I want to solve \begin{align*} & \max_{c}\min_{1 ...
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1answer
109 views

Convert general optimization problem to LP problem

I am trying to convert the following problem into a linear programming problem: There are $M\times N$ matrix $T$ of real numbers between 0 and 1 and $N\times 1$ vector $w$ of real numbers between 0 ...
2
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0answers
53 views

How to approximate higher-degree multivariate polynomial in space of lower-degree multivariate polynomials with some constraints?

For a polynomial $P_{1}(x)$, $x\in {\mathbb R}^n$ with a higher-degree, how to find a lower-degree polynomial $P_{2}(x)$ with determined structure or bounded degree to approximate it with the ...
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0answers
22 views

Maximizing modular function subject to supermodular constaint

I'm trying to solve a constrained optimization problem with submodular functions and get some nice properties of the solution. Unfortunately, I think I am in a setting where Topkis' theorem does not ...
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0answers
47 views

How to use the property of Frobenius norm in this proof?

Let $A \in \mathcal{S}^{n}$($\mathcal{S}^{n}$ is the $n \times n$ symmetric matrix space), $P,Q \in\mathbb R^{n \times n}$, and $\rho \geq 0$ be given. Show that: $$A \succeq P^{T}ZQ+Q^{T}Z^{T}P$$ for ...
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1answer
64 views

Quadrature formula for singular integrals over rectangular cuboids

A)Find the maximum of the following : $$\int_{\Omega_{a,b,c}}\int_{\Omega_{a,b,c}}\frac{dV(X)dV(Y)}{\|X-Y\|^2}$$ where ${\Omega_{a,b,c}}=[0,a]\times[0,b]\times[0,c]$, given $abc=1$ with $a,b,c>0$. ...
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108 views

Lower bound on the value $\textbf{1}^Tx$ such as $Ax\geq b$

The problem may be formulated as follows: We are given a set of $m$ positive numbers $\{b_1,...,b_m\}$ and a set of $n$ positive numbers $\{v_1,...,v_n\}$. We have $v_j\leq K$, $j=1,...,n$, for a ...
2
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0answers
70 views

Learning rule for recurrent neural network with flexible time steps

Summary: I want to train a recurrent network to output some answers, but the recurrent network is allowed to re-iterate through itself a flexible number of times for each input-output pair. Why this ...
2
votes
1answer
86 views

Better alternative to solve quadratic programming for large matrices

I have the following problem. Let's say we have $x_{jk}$ it is an expression value of gene $j$ in a sample $k$. It is the average of expression levels across the cell types $s_{ij}$, weighted by ...
3
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1answer
132 views

Computational complexity of low rank SDP

Suppose we are given a general SDP of the form with an additinal rank requirement \begin{array}{rl} {\displaystyle\min_{X \in \mathbb{S}^n}} & \langle C, X \rangle_{\mathbb{S}^n} \\ \text{subject ...
2
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0answers
121 views

Minimize L-infinity norm with restrictions

I need to minimize the following L-infinity norm with respective to $\tau$. L-infinity norm of a matrix $A$ is defined as $\|A\| = max_{i,j}|a_{i,j}|$. $$ min_{\tau} \| I -S(S+\tau)^{-1}\| $$ $$ ...
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0answers
73 views

reconstructing a linear order corrupted by noise

Suppose we have a partial order (efficiently computable), $\leq$, on $\mathbb{R}^n$, a set $S \subset \mathbb{R}^n$, and let $\rho$ be the standard Euclidean metric. We want to find a set $S^\prime = ...