2
votes
1answer
55 views

Solving $ \inf \left\{ F[\nu] : \nu \in L^2 , \nu \geq 0, \int _0 ^1 \nu=1\right\}$

Let $\phi \in \mathcal ( [0,1]^2)$ symetric , can we find a solution to the following minimisation problem? $$ \inf \left\{ F[\nu] : \nu \in L^2 , \nu \geq 0, \int _0 ^1 \nu=1\right\}$$ with $$ ...
0
votes
1answer
24 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) ...
4
votes
0answers
223 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 ($X=X^*$) ...
1
vote
1answer
41 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 ...
1
vote
0answers
26 views

can we prove that a certain supremum of affine functions is frechet differentiable or at least continuous?

Let $X$ be a Hilbert space. Let $A\colon \operatorname{dom} A\to X$ be linear operator with closed graph (not necessarily bounded). Define $$ g\colon \operatorname{dom}A\to \mathbb{R}:x\mapsto ...
2
votes
1answer
45 views

What is the name of this object?

Suppose I have a convex set $K\subset X$, where $X$ is say a real Hilbert space (for simplicity). Then, given some $a\in \Bbb{R}$, let $$ \hat{K}=\{x:\langle x,y\rangle \leq a \;\forall y\in K\} $$ ...
1
vote
1answer
61 views

Property for the subdifferential and duality mapping in context of the Moreau-Yosida regularization

I have a question arising from the Moreau-Yosida regularization in Banach spaces. The real Banach space $X$ and its dual $X^*$ are both reflexive strictly convex, $f:X \rightarrow \mathbb{R} \cup ...
1
vote
1answer
90 views

Minimizing a linear function on a strictly convex set.

All the theorems that I know considering the uniqueness of a solution to a minimization/maximization problem requires the strict convexity/strict concavity of the objective function. But consider the ...
1
vote
0answers
36 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 ...
3
votes
1answer
70 views

What type of convex constraint is defined by SQRT?

Let $A$ be an $n \times n$ positive semidefinite matrix and $\forall k, x_k \in \mathbb{R}^n$. The distance with respect to this matrix is defined as $ \|x_i -x_j\|_A := ...
3
votes
1answer
147 views

Attain minimum on boundary of a convex set?

It is well known that there exists a unique minimum norm vector over a closed convex set. Suppose we have a Banach space X (if it needs to be more concrete we can think of $L_2$, the space of square ...
1
vote
1answer
95 views

Convex functions and Hahn-Banach application

Let $Z$ be a convex subset of a real vector space, and $f:Z \to \mathbb{R}^m$ be such that every component $f_i:Z \to \mathbb{R}$ is a convex function. Let $S:\mathbb{R}^m \to \mathbb{R}$ be defined ...
1
vote
2answers
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 ...
3
votes
1answer
192 views

Show that any convex function is locally bounded

Show that a convex function $f:\mathbb{R}^n \rightarrow \overline{\mathbb{R}}$ is bounded in a neighborhood of $x\in \text{ri}(\text{dom}(f))$. Showing that it has an upper bound is not difficult ...
0
votes
1answer
51 views

Quadratic Functions

Consider the strictly convex quadratic function $f(x) = \frac{1}{2}x^tPx - q^tx + r,$ where $P \in \mathbb{R}^{n \times n}$ is a positive definite matrix, $q \in \mathbb{R}^n$ and $r \in \mathbb{R}.$ ...
1
vote
1answer
188 views

Strongly convex function

There is a $\sigma$-strongly convex function, $f(x')\ge f(x)+ \langle x'-x,\mu\rangle +\frac{\sigma}{2}\left|x'-x\right|^2$ where $\mu \in \partial f(x)$, $\mu ' \in \partial f(x')$. How could I get ...
0
votes
1answer
204 views

Is this sum of convex and concave functions a convex function?

Is this a convex function in $X$, where all the entries are real and $Y,\beta$ are constants where $X,Y$ are rectangular matrices and $\beta$ is a constant vector and $A,B$ are constant p.s.d ...
0
votes
1answer
61 views

Projection: two closed convex sets

I am really struggling with this problem: $C$ and $D$ are closed, convex subsets of ${R}^n$ with non-empty intersection, i.e. $C \cap D \neq \emptyset $ . Is it true that projection $p_{C\cap ...
1
vote
1answer
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...
1
vote
1answer
45 views

Showing that $T+S$ is firmly nonexpansive

Show that $T+S$ is firmly nonexpansive considering that $T$ and $S$ are firmly nonexpansive mappings from $\mathbb R^n$ to $\mathbb R^n$. Definition: We say that $F$ is firmly nonexpansive if: ...
3
votes
1answer
59 views

Show that $Z=T(2S−I)+I−S$ is firmly nonexpansive

Suppose $T$ and $S$ are firmly nonexpansive mappings from $\mathbb R^n$ to $\mathbb R^n$. Let $I$ be identity operator. I want to show that $Z=T(2S−I)+I−S$ is firmly nonexpansive. Definition. We say ...
1
vote
1answer
182 views

Max function on a closed compact convex set.

Consider a closed convex compact subset $\mathbb{S}$ of $\mathbb{R}^N$ while we denote any of its point by $x=[x_1,x_2,\ldots,x_N]^T$. Define the function \begin{align} f(x)=max(x_1,x_2,\ldots,x_N) ...
2
votes
3answers
120 views

Proof of Convexity

Is the function $Trace(AX^TBX)$ a convex function in $X$ or not ? Here, $X$ is a rectangular matrix and $A,B$ are square, symmetric, p.s.d matrices. The entries in $X,A,B$ are real valued.