0
votes
0answers
40 views

$f:D\subset \Bbb R^2 \rightarrow \Bbb R$, where $D$ is a compact and convex set, reaches it maximum at $int(D)$

I'm trying to prove that if $D$ is a compact and convex (for every two elements of $D$, the line that connects them is contained in $D$) then: If $f:D\subset \Bbb R^2 \rightarrow \Bbb R$ and at ...
0
votes
0answers
21 views

A Difficult combinatorial optimization problem

Let $\mathcal{J}$ be a closed, bounded, compact, convex set in $\mathbb{R}^L$. (Notations: vector $\mathbf{x}$ is denoted in bold letters and its $i^{th}$ co-ordinate is denoted as $x_i$. ...
0
votes
0answers
14 views

Eliminating variables in convex program

This is a basic convex optimisation question. I have the following problem: $$\max_{\substack{t\le e\\ At\le b}} e^\top t$$ How do I find the optimum $t^*$? I write the KKT conditions, get ...
0
votes
1answer
32 views

what is the dual of the following linear program over a convex set?

Let $\mathbf{x}=[x_0,x_1,\dots,x_N]^T$ be a $(N+1)\times 1$vector. Let $\mathcal{S}$ be a bounded, compact convex set in strictly positive quadrant of $\mathbb{R}^{N+1}$. Consider the following ...
0
votes
1answer
69 views

Convex optimization approximation

Consider the optimization problem $\mathcal{P}_0$ $$ \min_{x \in \mathbb{R}^2} \left\| x-p \right\|^2 $$ $$ \text{sub. to: } \ A x \leq b, \ \ x_1^2 + x_2^2 = 1 $$ where $p \in \mathbb{R}^2$ is a ...
1
vote
1answer
59 views

New variable in a convex optimization problem

Consider the convex optimization program $$ \min_{x \in X } x^\top P x + p^\top x \quad \text{ sub. to: } Ax = b $$ where $X \subset \mathbb{R}^n$ is compact, $P \succ 0$, $A \in \mathbb{R}^{m \times ...
1
vote
1answer
53 views

A particular quadratic minimization problem

Given $n^2$ constants $a_{11},a_{12},\ldots,a_{1n},a_{21},\ldots,a_{nn}$ and $n^2$ non-negative variables $x_{11},x_{12},\ldots,x_{1n},x_{21},\ldots,x_{nn}$. Find the minimum value of $$\sum_{i=1}^n ...
1
vote
1answer
34 views

Optimization of a convex target function with inequality constraints

I want to solve the following optimization problem: \begin{equation} \begin{split} \text{maximize} &\;\;\; \ln x_1+\ln x_2+\ln x_3+\ln x_4 \\ \text{s.t} &\;\;\; x_4\le4 \\ ...
0
votes
0answers
26 views

Dual convex pairs

I am currently trying to understand a certain proof. The author uses the term dual convex pair for a pair $(\phi,\psi)$ of convex functions defined on subsets $X,Y$ of $\mathbb R^n$ satisfying: $$ ...
0
votes
0answers
22 views

Robust LP question using box uncertainty model

I am trying to solve this robust LP problem by writing it as a QP $$\min_x x^TSx : \mu \leq r^T x , Ax \leq b$$ Under Box uncertainty model: $$R = \{r : \| r - \hat{r}\|_\infty \leq \rho\}$$ Here ...
0
votes
1answer
25 views

Decreasing Function Projected onto Simplex

Consider $f: \mathbb{R}^n \rightarrow \mathbb{R}^n$, defined as $f(x) := a x + b$, where $a<0$ and $b \in \mathbb{R}_{\leq 0}^{n}$. Note that $f$ is decreasing: $$ x \geq y \Longrightarrow f(x) ...
1
vote
2answers
68 views

Minimization of log-sum-exponential function subject to constraints.

I would like to minimize the following function: $f(x)=log(e^{-x_1}+..+e^{-x_n})$ Subject to: $\sum_{i=1}^{n}{x_i}=1$ $0 \leq x_i \leq 1$ So far I have discovered the following: If all the ...
1
vote
1answer
30 views

Equality constrained Quadratic Program

Consider the QP $$ x^* = \arg \min_{\displaystyle x \in \mathbb{R}^n{\geq 0}} \ \frac{1}{2} x^\top P x + q^\top x \ \text{ sub. to: } A x = b, $$ where $P \succ 0$. Without the non-negativity ...
0
votes
1answer
20 views

On the Composition of simple Projections

Consider the compact convex set $X = \{ x \in \mathbb{R}^n \mid x \geq 0, \ \underline{1}^\top x = 1 \}$. I am wondering if the projection onto $X$ is the composition of the projection on $[0,1]^n$ ...
1
vote
1answer
38 views

Quadratic programs: is the projection onto constraints optimal?

Consider the Quadratic Program $$ x^* := \arg \min_{ x \in X } \ \{ x^\top x + c^\top x \} \ \text{ sub. to: } Ax=b $$ where $X \subset \mathbb{R}^n $ is a non-empty, convex, bounded polyhedron. ...
0
votes
2answers
73 views

Solution in general for a seemingly simple problem

Let $\mathbb{S}$ be a closed, bounded, convex set in $\mathbb{R}^N$. Let $\mathbb{x}=[x_1,\dots,x_N]$ be any arbitrary vector in $\mathbb{S}$. Then what can we comment on the problem \begin{align} ...
2
votes
1answer
76 views

How can the sum of two closed cones be not closed?

Can there be two closed cones $K_1$ and $K_2$ in $\mathbb{R}^3$ such that $K_1+K_2$ need not be closed?
0
votes
1answer
22 views

Quadratic Program over Box Constraints

Consider $f:\mathbb{R}^n \rightarrow \mathbb{R}$ defined as $$ f(x) := x^\top x + c^\top x $$ for some $c \in \mathbb{R}^n$. Define the (compact) "Box" $$X := \{ x \in \mathbb{R}^n \mid x_i \in [ ...
1
vote
1answer
55 views

Partial derivative on convex set

If we have a function $f:U \rightarrow R$ ($U \subset R^n$) which is partially differentiable on a convex set U with $\frac{\delta f}{\delta x_1} = 0$ for all $x \in U$. How can we prove that $f$ ...
0
votes
0answers
33 views

Show that the Rosenbrock function is strictly convex for a specific region

So we know that the Rosenbrock function is a test function of sorts, but can anyone prove that a specific region is strictly convex? Rosenbrock eqn: $ f(x_{1},x_{2}) = 100(x_{2} - x_{1}^{2})^{2} + ...
0
votes
1answer
91 views

Can a Lipschitz continuous function be strictly convex?

Let $\varphi:\mathbb R^n\to\mathbb R$, and suppose for all $x,y\in\mathbb R^n$, $$\|\varphi(x)-\varphi(y)\|\leq L\|x-y\|$$ for Lipschitz constant $L$. Is it possible for such a function to satisfy ...
-1
votes
1answer
78 views

Prove or disprove the concavity of the function [closed]

Prove or disprove the concavity of $f$ over the following two domains. $$f(x_1,x_2)=10-2(x_2-x^{2}_{1})^{2}$$ defined either over $$S_1=\{(x_1,x_2) : -1\leq x_1 \leq 1, -1 \leq x_2 \leq ...
2
votes
2answers
90 views

Verifying the convexity of some function

Convex function: We will say that $f:X\rightarrow R$ is convex function if for every $\lambda\in [0,1]$ and for every $x,y\in X$ ($X$ is convex space) $f(\lambda x+(1-\lambda)y)\leq\lambda ...
0
votes
1answer
48 views

Prove that proximal function is convex

How to prove that the proximal function $$ \Phi (y) \equiv \min_x \left(f(x)+\frac{1}{2} ||x-y||_2^2\right) $$ is a convex function of $y$ if $f(x)$ is a convex function of $x\in \mathbb{R}^n $? ...
1
vote
0answers
40 views

Differentiability of the Value (Support) Function

Consider the following problem, \begin{align} c(y,\mathbf{w})=\inf_{\substack{\mathbf{x} \in \mathbb{R}^n_{+} \\ \text{s.t. }f(\mathbf{x}) \geq y }} \mathbf{w} \cdot \mathbf{x} \end{align} where ...
0
votes
0answers
30 views

Hessian of a conic function

i got a conic System: $Ax =b, x\in C$, where $A\in\mathbb{R}^{m\times n}, b\in\mathbb{R}^m$ and C is the cone of the $n\times n$ positive semidefinite matrices, so ...
1
vote
1answer
80 views

strict separation theorem?

Im learning and we have a theorem that says: Let $C$ be a non-empty, convex subset of $\mathbb R^d$ and let $p \in \mathbb R^d$ be a point which is not in the closure of $C$. Then there exists a ...
1
vote
1answer
90 views

Prove that $ri (epi f)=\{(x, y): x\in ri (dom f), y >f(x)\}$

$f: R^n \to (-\infty, \infty]$ is a convex function. Prove that $ri (epi f)=\{(x, y): x\in ri (dom f), y >f(x)\}$ I have used definition of convex functions to prove that the right-side is ...
3
votes
2answers
1k views

Second derivative positive $\implies$ convex

In proof of the following theorem; If $f$ has a second derivative that is non-negative (positive) over an interval then $f$ is convex (strictly convex). $f$ is in real number space., the book I ...
1
vote
1answer
94 views

Convex combination of orthogonal matrices

How would I show that the convex combination of orthogonal matrixes has spectral norm $ \leq 1$? (I have some idea how to do it ... but right now I'm stuck). Also, how would I prove that the unit ...
1
vote
1answer
49 views

Solution for a optimization of $\max$ function

Let $\mathbb{S}^m$ be an arbitrary closed, compact, convex set in $\mathbb{R}^m$. Let $\mathbf{x}=(x_1,\dots,x_m)$ denote a point in $\mathbb{S}^m$. Then, I define the function \begin{align} ...
1
vote
2answers
69 views

Absract convergence of a suboptimal version of steepest descent

I'm looking for a citable reference to fill in a gap in an intermediate step of a proof which requires convergence of a suboptimal version of steepest descent. The function $f:\bf{R}^n\to\bf{R}^n$ I ...
0
votes
1answer
47 views

Determine negligible coefficients in spectrum

Suppose I have some function $f$ that I have sampled at $N$ points and I preform a transform on it (this could be a Fourier transform, or perhaps a Hadamard, or really anything eles - I'm hoping for a ...
1
vote
1answer
89 views

Supporting hyperplanes Theorem in Boyd's Convex Optimization

On page 51, the authors applied the separating hyperplane theorem to the sets ${x_0}$ and the interior of $C$ to prove the supporting hyperplanes theorem (assuming the interior of $C$ is nonempty). ...
0
votes
1answer
230 views

Convex homogeneous function

Prove (or disprove) that any CONVEX function $f$, with the property that $\forall \alpha\ge 0, f(\alpha x) \le \alpha f(x)$, is positively homogeneous; i.e. $\forall \alpha\ge 0, f(\alpha x) = \alpha ...
0
votes
1answer
502 views

Pointwise supremum of a convex function collection

In Hoang Tuy, Convex Analysis and Global Optimization, Kluwer, pag. 46, I read: "A positive combination of finitely many proper convex functions on $R^n$ is convex. The upper envelope (pointwise ...
2
votes
3answers
229 views

A robust convex optimization problem

Consider a function $ f: \mathbb{R}^n \times \mathbb{R}^m \rightarrow \mathbb{R} $ such that $\forall x \in \mathbb{R}^n$ the map $f(x,\cdot)$ is convex, and $\forall y\in \mathbb{R}^m$ the map ...
3
votes
1answer
150 views

Strictly Convex Function and Well-Separated Minimum

Suppose $\Theta \subset \mathbb{R}^d$ is a convex set, and $f:\Theta \rightarrow \mathbb{R}$ is a strictly convex function that has a minimum at $\theta_0\in\Theta$. Is it true then that $\forall ...
9
votes
2answers
2k views

What is the difference between minimum and infimum?

What is the difference between minimum and infimum? I have a great confusion about this.
1
vote
1answer
120 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...
0
votes
1answer
77 views

convex conjugate $f^*$ is proper if both $f$ and $f^{**}$ are

If $f$ and $f^{**}$ on $\mathbb R^d$ are proper functions where $f^*$ stands for the convex conjugate of $f$ why does that follow that $f^*$ is proper, too? Thanks a lot...
0
votes
0answers
115 views

convex lsc function affine minorant theorem proof

How to show the following: f:R^n->R A lower semicontinuous convex function f equals the pointwise supremum of all its affine minorants. Thank you!
0
votes
1answer
57 views

Epigraph supported at some point meaning of the sentence

Can you tell me what does the following sentence mean? Let $z \in \mathbb{R}^d$ and $(-z,1)$ supports epigraph of $f$ at $(x_0,f(x_0))$ Thank you..
0
votes
1answer
124 views

Direction of recession, convex analysis

Hi how to show the following: Let $C$ and $D$ be two non-empty closed convex sets with no common direction of recession. Then $C - D$ is closed. Thanks a lot...
0
votes
1answer
29 views

Intersection of a 2-Dimensional body and a Line given west-most point and south-most point

I have a 2-Dimensional Closed Convex Compact Body $\mathbb{S}$(a set, for eg, a circular disc)). Assume, it has a non-zero intersection with the all-negative quadrant. Consider the following 2-D point ...
2
votes
1answer
1k views

Prove the supremum of the set of affine functions is convex

Let $\langle f_i \rangle _{i \in I}$ be a family of affine functions on a convex and compact set $\Omega \subset \mathbb{R^d}$ such that $f_i = a_i.x +b_i$ for $x \in \Omega$. Prove that f, defined by ...
1
vote
2answers
176 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 ...
3
votes
1answer
121 views

Lower bound of a function

Given $x \geq y > 0$ and an integer $n$. We want to minimize the following term $\sum_{i=1}^n (x_i^2 - x_iy_i)$ over $(x_1,\ldots,x_n)$, $(y_1,\ldots,y_n)$ non-negative such that $\sum_{i=1}^n x_i ...
2
votes
1answer
133 views

Local min and differentiability of a function

Suppose there is a function $f: X \rightarrow \mathbb{R}$, where $X \subseteq \mathbb{R}^n$. If $x^*$ is a local minimizer of $f$ over $X$, must $x^*$ be either of the two cases: if $f$ is ...