Convex Optimization is a special case of mathematical optimization. It includes Linear Programming and least-squares.

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Projection onto convex set defined by $\|\mathbf{t} -\mathbf{W}^T\mathbf{y}\|^2 \leq k$

I want to use the method of Projections Onto Convex Sets, and for the problem at hand I need to find a closed form solution for $\mathbf{P}_C$, the projection onto set $C$, defined as: $$C = \{ ...
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125 views

About Schur complement in a non-linear matrix inequality

I have the following matrix inequality which is nonlinear due to $M^TM$. In order to transform into an LMI, I apply the Schur complement, however I am not sure about the result. Can you tell me if ...
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1answer
42 views

Got stuck with this $L^2(-1, 1)$ optimization problem. Any ideas where it comes from?

Statement Let $u(x) \in L^2(-1, 1)$. Solve the following optimization problem: $$ \begin{cases} J(u) = 4 \int_{-1}^{1} \sqrt{|x| (1 - |x|)} u(x) dx + \left(\int_{-1}^1 \sin(3\pi x) u(x) dx\right)^2 ...
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37 views

convex hull function in matlab

Is there anyway to compute the convex hull of a finite set of points in Matlab and gives the half-space representation as its result? I usually use a toolbox called MPT developed at ETHZ Zurich, but ...
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14 views

Interpreting constraints in an optimization problem

I am working on an optimization-based image denoising project in which I have three "flavors" of an optimization problem, one constrained and two unconstrained. They are given as follows: ...
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1answer
62 views

Is this function involving matrices convex?

Let $X\in \mathbb{R}^{n \times n}$. Then, is the function $$ \text{Tr}\left( (X^T X )^{-1} \right)$$ convex in $X$? ($\text{Tr}$ denotes the trace operator)
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1answer
19 views

Is a constrained optimization problem equalivant to its Lagrangian form?

For the following problem: $\text{min:}\ f(x)\\ s.t. \ g(x)\leq t$ Is the above problem equalivant to the following problem? $\text{min:}\ f(x) + \lambda g(x) \\ s.t. \ \lambda\geq0$ where $t$ and ...
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245 views

How to prove this function is quasi-convex/concave?

this is the function: $$\displaystyle f(a,b) = \frac{b^2}{4(1+a)}$$
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1answer
42 views

What's the solution for $\max_{x\in(0,1]}: \{-1-x\}$

What's the solution for the following optimization problem? Is the constraint set convex? $$\max_{x\in(0,1]}:\{-1-x\}$$
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1answer
25 views

Convex Subset Projection

Suppose that C is a closed convex subset of $\mathbb R^n$ and $x \in \mathbb R^n$. The projection of $\mathbf x$ onto C is the closest point $\mathbf y \in C : \mathbf z = \mathbf y$ minimizes ...
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2answers
30 views

Critical points and Convexity?

Function $f(x)$ has no critical points in $M$, can we say $f(x)$ is either convex or concave over $M$?
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No critical points means convex or conave? [closed]

If we don't know whether $f(x)=0$ is convex or concave or not, but we know under certain constraint sets there is no critical points of $f(x)$ inside meaning the solution of $df(x)=0$ is outside the ...
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14 views

Formal definition of convexity for multivariate function?

Let $M\in R^{M\times N}$, a function $f: M\rightarrow R$ is called convex on $M$ if $f\big((1-\lambda)X1+\lambda X2, (1-\lambda)Y1+\lambda Y2\big) \leq (1-\lambda)f(X1,Y1) + \lambda f(X2,Y2)$ For ...
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1answer
26 views

Underdetermined system with inequality constraints

I have an underdetermined system of equations of the form \begin{equation} Ax = b, \end{equation} where $A \in \mathbf{R}^{m \times n}$ with $m < n$, subject to \begin{equation}0 \preceq x ...
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24 views

Duality gap problem

I have checked that the objective function is concave and the constraint functions are convex. Now to find the duality gap, one need to find the optimum of the primal and dual problem, and find the ...
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1answer
383 views

generalized inequalities defined by proper cones

The generalized inequality defined by a proper cone $K$ is that $x \ge_{K} y$ if $x-y \in K$ for $x,y \in K$. Does this means that for any $x \in K$, we have $x \ge_{K} 0$ since $x - 0 = x \in K$ ? ...
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Optimization of Product of Different Objective functions (Ex.: Maximize The Product of projections of a complex vector)

Suppose We have this optimization problem which is convex $\mathbf{x}={\arg}\: \underset{\mathbf{x}}\max f_{i}\left (\mathbf{x} \right )$ But the product of different objective function is ...
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1answer
335 views

What Stopping Criteria to Use in Projected Gradient Descent

Suppose we want to solve a convex constrained minimization problem. We want to use projected gradient descent. If there was no constraint the stopping condition for a gradient descent algorithm would ...
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40 views

max and min values on symmetric polytope

Let $-N\leq t \leq N$. Let $A$ be regular $(N-1)$-dimensional simplex with vertices $(t,0, \ldots, 0)\ldots (0, 0,\ldots, t)$ and $B$ be regular $(N-1)$-dimensional simplex with vertices $(t-N+1,1, ...
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2answers
42 views

Minimize Function over Convex Subset

Suppose that C is a closed convex subset of $\mathbb R^n$ and $x \in \mathbb R^n$. The projection of $\mathbf x$ onto C is the closest point $\mathbf y \in C : \mathbf z = \mathbf y$ minimizes ...
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1answer
41 views

Convex Functions and Subsets

Suppose that $f, g: \mathbb R^n \to \mathbb R $ are $C^1$ convex functions. Show that $C = ${$\mathbf x \mid g(\mathbf x) \leq 0$} is a convex subset of $\mathbb R^n$. Show that if $\nabla f(\mathbf ...
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22 views

Convex cones and positively homogenous and subadditive functional

Let $V$ be a linear topological space, $K \subsetneq V$ a convex, closed cone with $0 \in K$ and $k \in K \setminus (-K)$. Show that the functional $\varphi : V \to \mathbb R \cup \{ \pm \infty \}$ ...
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1answer
197 views

Checking convexity

I know that the function $(\mathbf{a}-\mathbf{b})'(\mathbf{a}-\mathbf{b})$ is convex in $\mathbf{a}$ ($\mathbf{a}$ and $\mathbf{b}$ are vectors, not scalars). Would ...
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30 views

Issues with quasi Newton method convergence

I have this issue with the convergence of the quasi newton method. I have a convex objective function which I need to minimize wrt some parameters. I generated some synthetic data using a defined ...
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211 views

Dual to the dual norm is the original norm (?)

I have the following questions about dual norms : How do you prove that the dual of the dual norm is in fact the original norm? This is what I have so far: If I have $\|y\|_* $ as the norm dual of ...
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1answer
31 views

Min of concave symmetric function on a convex set

Consider the convex set $$C=\left\{ \mathbf{x}\in \mathbb{R}^N :0\le x_1\le x_2\le\dots\le x_i\le x_{i+1}\le \ldots\le x_N\le \frac 1{N-1}\text{ and } \sum_{k=1}^{N}x_k=1\right\}$$ I need to minimize ...
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3answers
71 views

Concave function divided by a convex function. What is the result?

Let us say that I have a function $f(x)$ that we know is a concave. And let us also say that we have another function $g(x)$ that is a convex. If I make a new function, $h(x) = \frac{f(x)}{g(x)}$, ...
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35 views

Why is pointwise maximum a convex function?

It seems like if you have a family of function $$g = \{a(x), \: b(x), \: c(x), \:d(x)\}$$ $$\text{given} \:\: f(x):= max(g),$$ $$\text{if} \: f(1) = a(1), \: f(2) = b(2), \: f(3) = c(3), \: f(4) = ...
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24 views

Why does convexity of a function required the following

What is the significance of the following condition $$\forall x_1, x_2 \in dom(f) , \forall \theta \in [0, 1], f(\theta x - (1-\theta)y) \leq \theta f(x) + (1-\theta)f(y)$$ and why isn't the ...
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44 views

Dual of a Semi Definite Programming Problem

How do I write the dual of the following semi definite programming problem? \begin{align} \max_{\lambda,y_i}~&\lambda \\ &\sum_{i=1}^{L}y_i\mathbf{C}_i-\lambda\mathbf{I}\geq 0 \\ ...
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1answer
17 views

How do I justify that a second order cone is an intersection of half space

I am studying convex optimization right now, and the text book claims that a second order cone is a collection of intersections of half space $$K_n = \bigcap_{ u:\|u\|_2 \leq 1} \{(x,y) \in R^{n+1 } ...
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37 views

Confusion related to k neighborly polytope

I was reading this paper related to neighborly polytope where they mentioned: Consider a $d \times n$ matrix $A$, with $d < n$. The problem of solving for $x$ in $y = Ax$ is underdetermined, ...
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Convex Sets and extreme supports

Let the set $S$ in $R^n$ consists of the origin $0$ and $n$ lineary independent vectors $T_1, \ldots, T_n$. Show that $C(S)$, the convex hull of of $S$, is the intersection of its extreme supports, ...
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26 views

Exact Line Search in Projected Gradient Descent

How is exact line search adapted for projected gradient descent in convex optimization? One way I think of is that unconstrained exact line search is run, and the new point is projected into the ...
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1answer
33 views

Derivative of a minimum

The expression, $e=\left(x(t,w)-c_x\right){}^2+\left(y(t,w)-c_y\right){}^2$, has a local minimum with respect to $t$ at some $t_0(w)$. Now what does $t_0'(w)$ look like?! $x,y\in C^2$ with respect to ...
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91 views

straightforward way to determine if this set is convex?

straightforward way to determine if this set is convex? $Z=\left\{x\in\mathbb{R}^2:3x_1^4-x_1x_2+x_2^4\le x_2,x_1>2,x_2>2\right\}$ I know I can try by manipulation of linear combination of two ...
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160 views

Properties of the square norm in Banach spaces

Let $X$ be a Banach space with its dual $X^*$. Consider the mapping $f: X\rightarrow \mathbb{R}$ given by $$ f(x)=\frac{1}{2}\|x\|^2. $$ We have know that when $X$ is a real Hilbert space ($X=X^*$) ...
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37 views

An application of Separation Theorem

Let $X$ be a Hausdorff locally convex topological vector space. Suppose $X_0 \subset X$ is nonempty convex set, $g:\; X\to \mathbb R^m$ is a convex vector function (each component $g_i(x): X\to ...
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1answer
39 views

A Simple Algorithm for Imposing Semi-definite Constraints

What is the simplest algorithm to implement, to impose semi-definite constraints? $\min_{X\succeq 0} f(X) $, where $X$ is an $n \times n$ symmetric matrix, and $f$ is a general smooth convex ...
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1answer
214 views

Convex Optimization of quadratic function with inequality constraints

How would I solve the following problem? $$\min_{x\in\mathbb{R}^n} x^T A x$$ subject to the constraints $$x_i\geq 1,\,i=1,\dots,n,$$ where A is positive semidefinite and symmetric. Is it possible to ...
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Impact of constraints on convex optimization

Let me start by saying I know almost nothing about optimization so please bear with me. Basically, I am wondering whether it is possible to solve a problem with two constraints by solving the problem ...
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147 views

Compressive sensing with non square matrices

I'm implementing the algorithm in the following paper: "Compressive sensing for wideband cognitive radios" http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=04218361 However I've run into a ...
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Derivative of nuclear norm

I'm trying to take the derivative of nuclear norm with respect to its argument. nuclear norm is defined in the following way: $$\|x\|_*=\mathrm{tr}(\sqrt{x^Tx})$$ I'm trying to calculate: ...
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57 views

Distribution of the Objective Value and the Variables in an Optimization Program

For random variables $X$ and $Y$, where $X\sim f(X;\theta)$ ($X$ is drawn from some distribution with pdf $f$ which is parametrized by $\theta$ ), $Y=g(X)$; we know that we can find the pdf of $Y$ if ...
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1answer
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Confusion related to the convexity of a bunch of functions

I have this confusion related to the convexity of some function.I was reading this paper - www.sigkdd.org/sites/default/files/issues/V14-01-02-Ye.pdf‎. I have this graph consisting of nodes denoted by ...
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1answer
297 views

Convex conjugate of $\ell_1$ and $\ell_2$ norm

Given a function $f$, we can define a function $f^{*}$, called the convex conjugate (also known as the Fenchel conjugate) of $f$ as follows: $$ f^*(\vec{z})= \sup_{\vec x \in \mathbb ...
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1answer
27 views

Dual formulation of an SDP problem

Could you help me formulate the dual problem to this SDP? maximize $\frac{1}{2} Tr(GW)$, subject to $ G \ge 0$ (and G symmetric), and $ \forall i$, $ G_{ii} = G_{1i} = G_{i1} $ Note that $G$ and ...
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Finding the maximum/minimum of a homogeneous function on $R^n$

Suppose that $f:R^n\to R$ is homogeneous. Also, suppose that the $argmin_xf(x)$ is non-empty. Is it true that if there exist $x^*\in R^n$ such that $f(x^*)=0$, then $x^*=argmin_xf(x)$?
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34 views

Convert Semidefinite program forms

How do I convert the following SDP problem (written in the standard inequality form): $$\min c^T x$$ $$\text{s.t. }F(x)\succeq0$$ When $F(x)\equiv F_{0}+\sum_{i=1}^{m}x_{i}F_{i}$ when $F_{i}\in ...
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196 views

Closed form solution of a convex optimization problem

Suppose we want to solve the following optimization problem: \begin{equation*} \begin{aligned} & \underset{x,y,z}{\text{minimize}} && x(a-y) \\ & \text{subject to} && ...