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

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Quadratic Integer Programming

Would anyone mind helping me solve this problem $$ \min\space f(x) = \frac12 x^\mathrm TQx + bx + c \qquad \text{s.t. } \sum_i x_i=\lambda $$ where $x$ is a vector whose entries are positive ...
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1answer
104 views

Find conjugate indicator function

I'm doubt with this problem. Let $C=\left\{(x,y)\in \mathbb{R}^2|x+\frac{y^2}{2}\le 0\right\}$. I have to find $I_C^{*}(Y)$ defined by $I_C^{*}(Y)=\sup_{X \in \mathbb{R}^2} \left\{\langle ...
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Analogue of Helly’s theorem for non-exact interpolation

Let $\overrightarrow{x}=(x_1,x_2, \ldots ,x_n),\overrightarrow{a}=(a_1,a_2, \ldots ,a_n)$ and $\overrightarrow{b}=(b_1,b_2, \ldots ,b_n)$ be vectors in ${\mathbb R}^n$, with $a_k \leq b_k$ for every ...
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182 views

$\{x:Ax\leq 0\}$ contains a subset of type $\{x:A'x=0, ax\leq 0\}$

If $C:=\{x:Ax\leq 0\}\neq\{x:Ax=0\}$, an independent set of rows of $A$ can be chosen, one denoted by $a$ and the others put as rows into a matrix $A'$, such that $\{x:A'x=0,ax\leq 0\}\subseteq C$. ...
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Nonlinear optimization of constraint parameter - subdifferential?

Disclaimer: I discovered that the FAQ suggests to post research-level to mathoverflow instead of math.stackexchange. I "moved" the question accordingly, cp. post at mathoverflow. Sorry for the ...
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265 views

SDP relaxation of non-convex QCQP and duality gap

Short version Is there a duality gap between a QCQP problem and the SDP problem obtained through lagrangian relaxation? A paper I'm studying is using this fact, but I cannot achieve the authors' ...
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1answer
74 views

Proof for certain matrix results?

There are certain results of matrices that Stephen Boyd uses often in his book on Convex optimization. Can someone provide me proof for the results I have enumerated below: If $B \in S^n$ and $A \in ...
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165 views

Convex optimization and linear programming please help! :)

How would I write the following as a standard form LP? Minimizing $\sum_{i=1}^n x_i + c\max(a_i-x_i)$ for $a_i \ge 0$ and what is the optimal value for when $c=n$ How to express minimize $\frac{1}{2} ...
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156 views

Optimization problem about large matrices

I'd like to solve the following optimization problem: Find non-negative scalar $a$, $b$, $c$ to minimize $\| (D-(aA+bB+cC+D^{-1})^{-1})y\|^2+2\operatorname{trace}((aA+bB+cC+D^{-1})^{-1})$ where ...
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32 views

Convex formulation of a nearly convex optimization problem

The following problem has come up in my studies of logarithmic norms. I wish to find $\mu \in \mathbb{R}$ and a positive semidefinite $B$ so as to minimize the convex function $c \mu - \log\det(B)$ ...
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65 views

the dual of the dual is the primal?

Consider a convex optimization problem (call it $P$). Consider its dual (call it $D$). Is it true that the dual of $D$ is $P$? For linear programming, it is true. I'd just like to know under which ...
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80 views

Examples of functions that are Lipschitz w.r.t. Schatten p-norm?

A convex function $f$ is $R$-Lipschitz w.r.t. to a norm $\|\cdot\|$ if for all points $a, b$ we have $|f(a)-f(b)| \leq R\|a-b\|$. For a real symmetric $n\times n$ matrix $A$ with eigenvalues denoted ...
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108 views

How to minimize the supremum of two convex functions?

Given $f_1(x)$, $f_2(x)$, $x\in \mathbb{R}^d$, two convex functions, we define the following problem: $\underset{x\in C}{{\rm minimize}}\,{\rm ...
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123 views

Numerical Methods for minimizing a Non-Differentiable Convex Function of Several Variables

I have a multi-variable convex continuous function which is not differentiable. I am interested to know about different numerical techniques, possibly also references to them, used for this. Read ...
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31 views

convex optimization with inconsistent constraints

If you have a problem in convex optimization where all $N$ constraints ($N >> 0$) yield no possible solution but you are able to rank, or weight the constraint in terms of their importance are ...
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Convexity of a function

Suppose we have $F: R^n \longrightarrow R$ , $P: R^n \longrightarrow R^n$ and $G: R^n \longrightarrow R$ all nice- let's say given by polynomial and $P$ is invertible - such that $F(x) =G( P(x) )$. ...
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59 views

Prove that $\text{int}(\text{dom}(f))$ is a convex set.

Let $f$ be a convex function. I have to prove that $\text{int}(\text{dom}(f))$ is a convex set. (Be careful with $-∞$ )
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sufficient condition for KKT problems

For the Karush-Kuhn Tucker optimsation problem, Wikipedia notes that: "The necessary conditions are sufficient for optimality if the objective function f and the inequality constraints g_j are ...
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3answers
1k views

Trace of a quadratic function, Convexity

Is trace($XX^T$) a convex function of matrix $X$? A linear function of a quadratic should be convex, but I could not prove by definition.
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How to get the initial ellipsoid in the ellipsoid method for solving optimization problem?

If what I assume is correct, assumption : for a maximization problem, we run a binary search over estimated values, starting with max estimated value, and narrow down to the feasible optimal value ...
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Find a vector such that its matrix product is positive in every element

Given a matrix $A$ I want to find a vector $\vec{x}$ such that every element of $A\vec{x}$ is strictly positive. Also, the columns of $A$ do not span the full space, so if I were to just naively pick ...
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574 views

Convex minimization over the Unit Simplex

I have a simple (few variables), continuous, twice differentiable convex function that I wish to minimize over the unit simplex. In other words, $\min. f(\mathbf{x})$, $\text{s.t. } \mathbf{0} \preceq ...
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161 views

What is the dual of this optimization problem?

Consider the points $x_1, \ldots, x_N \in \mathbb{R}^n$, and a (locally bounded, convex) function $f: \mathbb{R}^n \rightarrow \mathbb{R}$. I am looking for the dual of the following optimization ...
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381 views

How to prove a set of positive semi definite matrices forms a convex set?

Let $C$ be the set of positive semi-definite matrices, how can I prove it is a convex set?
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171 views

Entropy expression optimization with Langrange multipliers

I have recently encountered variants of the following expression: \begin{equation} S = H(a,b,c,d)-H(a+b,c+d) \end{equation} where $H$ is the Shannon entropy function, that is $H(X)=\sum_{x\in X}-x\log ...
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68 views

Maximization of a log det function

I want to solve the following optimization problem $$ \text{maximize } f(X) = - \log \mathrm{det}(X+Y) - a^T (X+Y)^{-1} a \\ \text{subject to } X \succeq W, $$ where the design variable $X$ is ...
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1answer
115 views

Free software or algorithm for Second-Order Cone Program

I need to solve the following optimization problem: $$ \mathbf{x}^\ast = \operatorname{argmin}_{\mathbf{x}} \Vert \mathbf{Rx} \Vert_2^2 \;\;\; \mathrm{s.t.} \;\;\; \mathbf{s}^\mathrm{H} \mathbf{x} = ...
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159 views

Why the unit circle in $\mathbf{R^2}$ has one dimension?

When I was reading 'Convex Optimization, Stephen Boyd', I was wondering of following steps Consider the unit circle in $\mathbf{R^2}$, $i.e.$, $\{x\in\mathbf{R^2}|x^2_1+x^2_2=1\}$. Its affine hull ...
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75 views

What is the motivation behind strong convexity

Definition : A function is said to be $\beta$-strongly convex if, $f(\theta w + (1-\theta) w') \le \theta f(w) + (1-\theta) f(w') - \frac{\beta}{2}\theta(1-\theta)(w-w')^2$ What is the motivation ...
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67 views

How many methods for smoothing an unsmoothed function?

Which is the simplest one? For example, we smooth $f(x)=|x|$ to $$f(x)=\begin{cases} \frac{x^2}{\epsilon}+\frac{\epsilon}{2} & |x| \le \epsilon\\ |x| & |x|\ge epsilon ...
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131 views

Is the following problem convex?

I think the following problem is convex (due to the results of some simulations), but I am not sure: $min_x||e^{(Ax)}-b||^2_2$ s.t. x>0 where $A$ is m x n, $x$ is n x 1, and b is m x 1. $A,x,b$ are ...
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127 views

Convex Sets Versus Convex Functions

Can we specify all convex sets, in terms of convex constraints (convex inequality functions) on a variable?
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29 views

multi-objective optimization

I am currently encounterring a optimization problem. The goal is optimize an objective function A and B at the same time. But the problem is that optmizing A will almost always tradoff with B, such ...
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33 views

Why is $L_0$ norm not convex? [closed]

I have this confusion in understanding the convexity of the $L_0$ norm. Why is $L_0$ norm not convex?
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74 views

Formulation and computation of “the” unique median of an even-sized list

Consider an even-sized set of numbers $X = \{x_k\}$, such as $X = \{1, 2, 7, 10\}$. The median $m$ is defined as: $$m = \mathrm{arg \min_x} \sum_k \lvert x_k - x\rvert^1$$ Any $m \in [2, 7]$ is a ...
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Constraint to unconstraint optimization problem by subsitution

Given the following convex optimization problem $\min_{x,p} ||x|| - p$ subject to $p > 0$ Can I change the above to an unconstrained convex optimization problem by substituting $c = ...
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52 views

Composition of non-monotonic convex function

Given the following composition of functions: $h:\Bbb R^k\rightarrow\Bbb R$ $g:\Bbb R^n\rightarrow\Bbb R$ $f(x)=h(g_1(x),g_2(x),...,g_k(x))$ There are known rules which guarantee ...
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30 views

Is this a polyhedron?

Is $S$ a polyhedron? $$S=\{x\in\mathbb{R}^n|\|x-x_0\|\le\|x-x_1\|\}$$ where $x_0, x_1$ are given. $S$ is the set of points that are closer to $x_0$ than to $x_1$. I was thinking the ...
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99 views

formulating the dual for an instance of a SOCP with linear constraints

I have an optimization problem with second-order cone constraints and linear inequalities and inequalities (shown below). I want to formulate the dual, but have been having trouble. ...
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1answer
39 views

Optimization of several cost functions together

Say I want to minimize several functions together: $$\min \lVert f_1\rVert, \min \lVert f_2\rVert, \min \lVert f_1-f_2\rVert$$ where $\lVert f\rVert$ is the $L_2$ norm of $f$. I am wondering can I ...
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53 views

Minimize the function

Minimize the function $$f(x) = (ax+b)^2 \left(\frac{c}{x} + d\right),$$ where $a , b , c \text{ and } d$ are all positive constants and $x$ is the variable. Thanks and regards
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433 views

Carathéodory's theorem

Carathéodory's theorem says "If $C\subset R^n$, then every point from ${\rm conv}\; C$ can be expressed as a convex combination at the most of $n+1$ elements from $C$" In every proof I found, it ...
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346 views

A question dealing with the convexity of functions involving the absolute value

Just beginning to learn convex analysis and optimization, I have some inquiries to make with regard to the absolute value function $f(x)= |x|$. This function is clearly convex, but since we know that ...
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112 views

directional derivative sublinear of a convex function sublinearity problem to show

How to show the following: If $f:\mathbb R^d \rightarrow \mathbb R$ is convex then its directional derivative is sublinear? Thank you...
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1answer
95 views

Removing redundant half-spaces that bound a convex polytope

I am computationally representing a convex polytope in $\mathbb{R}^n$ as a set $A$ of half-spaces that bound it; each such half-space is represented by a row vector $\mathbf{v} = \begin{bmatrix}v_1 ...
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746 views

Explain `All polyhedrons are convex sets´

My teacher in course in Mat-2.3140 of Aalto University claims that 'All polyhedrons are convex sets' here. This premise was in a false-or-not-problem 'The feasible set of linear integer problem is ...
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137 views

How does the two phase method for linear programs work…

I understand that by adding artificial variables the problem can be reformulated as a new problem where the "starting point" is readily found. What I don't get is how when this extended problem is ...
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446 views

LP relaxation for ILP\IP (integer linear programming)

I am familiar with LP relaxation for ILP (or IP). Assume we concern with integer minimization problem, which we formalize using ILP; we then relax the ILP into LP and we say that the LP provides a ...
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565 views

Null space of a matrix

I was referring to this lecture http://www.stanford.edu/class/ee364a/videos/video05.html (about 0:38:10) related to convex optimization and for optimization it had a certain affine function equality ...
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260 views

Maximizing a function by finding derivative

I want to find the value of $\vec{p}$, $p_s$, $p_t$ each of which is a function of the form $f:\mathbb{R}^2 \to \mathbb{R}$ that maximize the following function : $$\begin{align} \int_\mathbb{R^2} ...