Convex analysis is the study of properties of convex sets and convex functions. For questions about optimization of convex functions over convex sets, please use the (convex-optimization) tag.

learn more… | top users | synonyms (1)

0
votes
0answers
8 views

Mean width of an ellipsoid

Let $E$ be an ellipsoid in $\mathbb{R}^d$ defined by the equation $\sum \frac{x_i^2}{a_i^2}=1$. Is there a formula to express the mean width (or an approximation of the mean width) of $E$ in term of ...
6
votes
3answers
69 views

Exposed point of a compact convex set

I'm trying to show that given a compact convex set $K$ in $R^d$, there must be at least one exposed point (where $v$ is exposed if there exists a hyperplane H such that $H \cap K = \{v\}$ . This is a ...
0
votes
0answers
11 views

log-concavity with PDF and CDF

Assume the following: pdf: $f_X(x)$ cdf: $F_X(x)=P(X \leq x)$ $X$ is a random variable with log-concave pdf $f_X(x)$. $Y = h(X)$ $X \in R^n$ $h: R^n \rightarrow R$ Through the ...
1
vote
1answer
13 views

A proof of property of log-concave

How to prove the $f$ is NOT log-concave? (or equivalently, log$f(x)$ is not concave) log$f(d)+$log$f(a) < $log$f(b) + $log$f(c)$ where $a = x_2 - y_2$, $b = x_2 - y_1$, $c = x_1 - y_2$, $d = x_1 - ...
2
votes
0answers
22 views

Log concavity/convexity of a determinant

I was wondering if anyone would be able to help me determine whether the following quantity is log concave or not with respect to $\alpha$? $$\left[\det(\textbf Y^\top \textbf P \textbf G \textbf ...
1
vote
0answers
10 views

Property of log-concave function

In S.Boyd's lecture: And in his vedio, he said: You are allowed one positive eigenvalue in the Hessian of log-concave function. http://web.stanford.edu/class/ee364a/videos/video04.html (at ...
1
vote
0answers
19 views

Convexity of matrix inverse

If $$f\colon\mathbb{R}^n\times\mathbb{R}^n\to\mathbb{R}$$ where $$f(x,y)=y^T x^{-1}y$$ and dom$(f)=\{(x,y)\ |\ x+x^T\gt 0\}$, then is $f$ convex?
1
vote
0answers
18 views

What are some good books on convex sets (analysis)? [on hold]

I'm looking for both introductory and advanced books.
1
vote
0answers
28 views

Dimension of Polyhedra [on hold]

Can someone explain the question below? I'm pretty new in this area, and I did not understand anything. Question; Let $P$ be defined by the following $$\begin{align}x_1+x_2+x_3&\le ...
0
votes
0answers
17 views

Proof - extreme point of a convex set

everybody! I am wondering how to prove the following theorem: Let $S \subset \mathbf{R}^{n}$ be a non-empty closed convex set. Then $S$ has at least one extreme point iff $S$ does not contain any ...
0
votes
0answers
26 views

Logarithmically Convex Function

By definition a logarithmically convex function is a positive real-valued function $f(x)$ defined on a convex set such that $\log f(x)$ is convex i.e. $$\forall\alpha\in[0,1]\hspace{0.5cm}\log ...
0
votes
0answers
5 views

Variation of linear matrix inequality

When reading "Convex optimization, S. Boyd" p.76, Example 3.4, it says The last condition is a linear matrix inequality (LMI) in $(x,Y,t)$. Therefore, epi($f$) is convex. I am confused about ...
0
votes
0answers
11 views

Proof of the direction of directional derivative is convex

Consider the directional derivative: http://en.wikipedia.org/wiki/Directional_derivative How to prove the following is cvx in $v$ (the direction of directional derivative): $h(v) = $inf ...
1
vote
1answer
32 views

Is $f(x,y)=-xy$ neither concave nor convex?

Is $f(x,y)=-xy$ neither concave nor convex? I used the definition for first differentiable functions and determined it depends on the choice of points, hence it is neither.
1
vote
0answers
20 views

Books on convex sets?

I'm looking for good books on convex sets. Idealy I'd like an introductory text AND a more advanced one. Appart from basic definitions and the like I have no background on the topic.
1
vote
3answers
28 views

Questions about coerciveness and convexity

I just have a few yes/no questions, and would really appreciate if you could correct me where I am wrong, and for what fundamental flaw I have. 1. Would the set of coercive functions a linear space? ...
2
votes
1answer
21 views

Using inequalities to find vertices of a polytope

Consider a set $C$ of vectors of integers $x\in\mathbb N^d$ satisfying $$ \begin{align} \forall\ i=1..d & \ \ [0 \leq \ell_i \leq x_i \leq u_i]\\ \forall\ i=1..d-1 & \ \ [x_{i+1} \leq x_i] ...
0
votes
2answers
15 views

Coerciveness and Positive definiteness relation?

Let $A ∈ \mathbb{R}^{n×n}$ be a symmetric matrix. How can I demonstrate that A is positive definite iff the function $q(x) := x^TAx$ is coercive . I know the eigenvalues of A have to be positive for ...
1
vote
1answer
23 views

Why does the Weierstrass theorem fail if a set is not compact?

By Weierstrass theorem I mean that if $f:\mathbb{R}^n \to \mathbb{R}$ is continuous and $C \subset \mathbb{R}^n$ is compact, then the theorem asserts that a solution $x^*$ of $$ \text{min} _{x\in ...
0
votes
2answers
25 views

Union of 2 convex sets

Let $f : \mathbb{R}^n→ \mathbb{R}_∞$ be convex over the sets A, B which are also convex. $A ∩ B = ∅$ and $A ∪ B$ is convex. Then is $f$ is convex on $A ∪ B$? Why or why not? I am confused ...
1
vote
1answer
26 views

Proving convexity using the Hessian

Suppose I have $f: \mathbb{R}^n \to \mathbb{R}_\infty$ which is twice continuously differentiable, on some convex set C, which is open. How can I prove that $f$ is convex over C, iff the hessian ...
0
votes
0answers
24 views

Coerciveness of a function - help

I'm trying to show that $$f(x_1,x_2,x_3) = e^{x_1^2 + x_2^2} + (x_1^2 + x_2^2 + 3x_2)^{500}$$ is not coercive, but am struggling to see anything. Any help is appreciated!
-1
votes
0answers
19 views

Which one(are) true?

My Effort: a,b are true. As f convex means for any 2 points in the curve , curve lies below the line. Thinking geometrically I think c is incorrect as if f negative |f| is positive. I' ll be glad if ...
1
vote
0answers
23 views

Convexity over a line given a convex interval [duplicate]

Let $f : \mathbb{R}^n \to \mathbb{R}_∞$ be a function. I want to prove that $f$ is convex over the line $L_{v,x_0}$ iff $\psi : \mathbb{R} \to \mathbb{R}_∞$ $\psi(t) := f (x_0 + tv)$, is convex ...
0
votes
0answers
11 views

Subsets being cones

I am trying to self-study convex optimization and still trying to get into the gist of it. There is a question in my text as follows: Let $V$ be the set of sequences whose terms are contained in ...
1
vote
1answer
34 views

the relation between positive definite matrix and its ellipsoid

Define $S^n_{++}$ to be the set that contains all the positive definite matrices. That is, if $A \in S^n_{++}$, then $A$ is a positive definite matrix. Then, we associate with each $A \in S^n_{++}$ ...
0
votes
1answer
15 views

Subdifferential is closed, convex and bounded

If $f: \mathbb{R}^n \to \mathbb{R} \cup \{+\infty\}$ is convex, how can I show that $\partial f(x_0)$ (sub differential) is closed and convex, and also bounded (bounded when f over the entire domain)
1
vote
2answers
28 views

Is the support function always unique for a convex set?

Given an arbitrary set $A ⊂ \mathbb{R}^n$ , the support function associated with the set $A$ $ σ_A : \mathbb{R}^n \to \mathbb{R} ∪ \{+\infty\}$ is defined as $\sigma_A(x):= \sup_{z \in A} \langle ...
0
votes
0answers
13 views

The conditions on marginals that guarantees a certain class of measures

$x$ and $y$ are $m\times n$ matrices. $a, B,C$ are $m\times 1$ matrices. $b, A$ are $n\times 1$ matrices. $$\sum a_i=1, 0\leq a_i\leq 1, \forall i$$ $$\sum b_j=1, 0\leq b_j\leq 1, \forall j$$ ...
1
vote
2answers
18 views

Showing coercivity of a function

I am well attuned to the definition for a function to be coerce, which is that $\lim_{\|x\| \to \infty}f(x) = \infty$ ie the values of $f$ go to infinity as the norm goes to infinity. So Ex.1 ...
1
vote
0answers
29 views

How to find a hyperplane

Let $A, B ⊂ \mathbb{R}^n$ be two nonempty sets such that $A ∩ B = ∅$. $H(A, B) := \{(w, d) ∈ \mathbb{R}^{n+1} : \sup_{x\in A} \langle w,x\rangle ≤ d ≤ \inf_{y \in B} \langle w, y\rangle \}$ How do I ...
2
votes
1answer
17 views

Reversing minimax function

Let $$g(x) = \inf_{a \in A} \sup_{b \in B} f(a,b,x).$$ When it is true that $$g^{-1}(x) = \inf_{a \in A} \sup_{b \in B} f^{-1}(a,b,x)\ ?$$ where $f^{-1}(a,b,x)$ means that $f^{-1}(a,b,f(a,b,x)) =x$ ...
1
vote
2answers
18 views

How to find ellipsoid bounding the intersection of an ellipsoid and half-space?

How does one prove that the bounding ellipsoid $E(A', a')$ of the intersection of an ellipsoid $E(A,a) = [ x | (x-a)^TA^{-1}(x-a) ]$ and half-space $H = [x | c^Tx \le c^Ta ]$ is given by the ...
2
votes
0answers
34 views

does this convex set have a specific name?

Let $x_1,\dots,x_N$ be points of $\mathbb{R}^n$. Define the following set: $\mathcal{A} = \left\{\sum_{j=1}^N a_j x_j : -1 \le a_j \le 1, \, \, \forall j=1,...,N\right\}$. It is an easy exercise to ...
0
votes
0answers
17 views

How to prove convexity of a function below with multiple variables?

Let a function $f$ on $[0, 1]^n$ be defined as $$f(x_1,\cdots, x_n)=\frac{1-\prod_i x_i} {\sum_i (1-x_i)}.$$ It is known that $1/n \le f(x_1, \cdots, x_n) \le 1$ and it is convex when $n=2$. Does the ...
1
vote
1answer
16 views

Convexity of a subset is convex?

Let $V$ be the set of sequences whose terms are contained in $\mathbb{R}^n . V$ is the set of functions $x(·) : N → \mathbb{R}^n $ which we denote as $\{x_n\}_n \subset \mathbb{R}^n$. $V$ is a vector ...
1
vote
1answer
27 views

Support function of a set is convex

Given an arbitrary set $A ⊂ \mathbb{R}^n$ , the support function associated with the set $A$ $ σ_A : \mathbb{R}^n \to \mathbb{R} ∪ \{+\infty\}$ is defined as $\sigma_A(x):= \sup_{z \in A} \langle ...
1
vote
1answer
25 views

The set of separating hyperplanes is a convex cone

Let $A, B ⊂ \mathbb{R}^n$ be two nonempty sets such that $A ∩ B = ∅$. $H(A, B) := \{(w, d) ∈ \mathbb{R}^{n+1} : \sup_{x\in A} \langle w,x\rangle ≤ d ≤ \inf_{y \in B} \langle w, y\rangle \}$ I can't ...
4
votes
1answer
45 views

When the closure of a convex set contains a ball

Suppose $C$ is a convex set in $\mathbb{R}^n$ whose closure contains the open ball $B(x,r)$. Is it true that $C$ contains $B(x,r)$? Motivation: I am asking this because something like this seems to ...
0
votes
0answers
14 views

definition of open set and is gauge function is well defined?

Q1 :I know that a set A $ \subset$ X is open if it contains an open ball about each of its points i.e. for all x in A ,there exists $ \epsilon $>0 s.t. $ B_\epsilon $(x) $\subset $ A But then does ...
1
vote
0answers
37 views

Hölder's inequality and log convexity of $L^{p}$ norm

Hölder's inequality of $L^{p}(X,\mu)$ $\left\Vert fg \right\Vert_{r} \leq \left\Vert f \right\Vert_{p} \left\Vert g \right\Vert_{q}$ where $0<p,q,r\leq \infty$ and ...
1
vote
1answer
11 views

Dual cone of $K = \{(x,t) \mid \| \boldsymbol{x} \|_1 \le t \}$

This slide shows the dual cone of $K = \{(x,t) \mid \| \boldsymbol{x} \|_1 \le t \}$ is $K^{*} = \{(x,t) \mid \| \boldsymbol{x} \|_{\infty} \le t\}$. Is it right? How is it proved?
1
vote
1answer
44 views

Hessian to show convexity - check my approach please

I need to check the convexity of $f(x)$ for these two questions, using the Hessian matrix. I am aware the function can be said to be convex if over the domain of $f$ the hessian is defined and is ...
0
votes
1answer
39 views

Help with this convex set proof

Take $C ⊂ \mathbb{R}^n$ a convex set. Fix $x_0 ∈ C$ and a nonzero vector $v ∈ \mathbb{R}^n$ . Define the set $I(x_0,v) := \{t ∈ R : x_0 + tv ∈ C \}$. Prove that $I_(x_0,v)$ is a convex subset of ...
1
vote
0answers
44 views

Showing convexity of a function with the restriction over an arbitrary line proof

Let $f : \mathbb{R}^n → \mathbb{R}_∞$ be a function and let $C ⊂ dom f$ be a convex set. $$**Part I**$$ Prove that $f$ is a convex function if and only if $f$ is convex over every line $L_{v,x_0}$ ...
1
vote
1answer
20 views

How to prove the following convex cone property

Suppose $A,B$ are closed cvx cones. $A^*,B^*$ are their dual cones respectively. How to show $$ (A^*+B^*)^*\subset A \cap B$$ My idea is: $$A^* = \{x_1|x_1^Tx \geq 0, \forall x \in A\}$$ ...
1
vote
2answers
50 views

Convexity of mutual information $I(X;Y)$ in conditional $p(y \mid x)$

I'm trying to understand the proof that $I(X;Y)$ is convex in conditional distribution $p(y \mid x)$ - from Elements of Information Theory by Cover & Thomas, theorem 2.7.4. In the proof we fix ...
1
vote
0answers
39 views

Any example of strongly convex functions whose gradients are Lipschitz continuous in $\mathbb{R}^N$

Let $f:\mathbb{R}^N\to\mathbb{R}$ be strongly convex and its gradient is Lipschitz continuous, i.e., for some $l>0$ and $L>0$ we have $$f(y)\geq f(x)+\nabla f(x)^T(y-x)+\frac{l}{2}||y-x||^2,$$ ...
0
votes
1answer
15 views

improper convex function

In Rockafellar's convex analysis there was an example of improper convex function: $$ f(x) = \begin{cases} -\infty & \text{if } ||x||<1, \\ 0 & \text{if } ||x|| =1, \\ +\infty ...
0
votes
0answers
11 views

how to construct the sup convex function with fixed values

Set $\mathcal{S} = \{(x_1, f_1),(x_2,f_2),...\vert x_i \in \mathbb{R}^d, f_i \in \mathbb{R}\}$, we assume convex functions $f(x): \mathbb{R}^d\rightarrow \mathbb{R}, $ which passes those points exist. ...