# Tagged Questions

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.

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### Geometrical interpretation of Pseudoconvexity?

I see in wolfram that a function $f$ is pseudo convex if it satisfies following, $\nabla f(x)\cdot (y-x) ≥ 0 \Rightarrow f(y) ≥ f(x)$ My question is, with this definition, how come $g(x)=x^3$ is ...
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### Why is the Euclidian norm convex, if the square root function is concave?

I have some trouble figuring out if the Euclidean norm is convex. $\left\|{\boldsymbol {x}}\right\|:={\sqrt {{\boldsymbol {x}}\cdot {\boldsymbol {x}}}}$ On one side I read that all norms are convex (...
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### The Set of Extremal Point Need not be closed

Exercise: Consider the Convex Hull $C$ of the points $(0,0,\pm 1)$ and the circle $\{(1+\cos\varphi,\sin\varphi,0): 0\leq \varphi \leq 2\pi\}$ in $\mathbb{R}^3$. Determine the extremal point of $C$. ...
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### Convex set or not?

This question is related to my previous question Set of all positive definite matrices with off diagonal elements negative I know that the set of all positive definite matrices form a convex set. ...
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### minimum of sum of strictly convex functions

Is the following statement true? If so, how can I find a proof? Suppose that $f_1$ and $f_2$ are strictly convex functions on a convex set $X \subseteq \mathbb{R}^n$. If $f_1$ and $f_2$ have minimum,...
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### how to calculate infimum of Augmented Lagrangian?

should any body explain that how do we calculate these step? \begin{align*} L(x,y) &= f(x) + y^T(Ax-b)\\ g(y) &= \inf_x \, L(x,y) \\ &= \inf_x \, f(x) - \langle -A^Ty, x \rangle - \langle ...
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### Why is this matrix symmetric?

There is an example in the Convex Optimization lecture notes, Boyd. He just said in the lecture that the matrix which is underlined in red color is symmetric! How can we claim that when there is no ...
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### Stochastic gradient descent for convex optimization

What happens if a convex objective is optimized by stochastic gradient descent? Is a global solution achieved?
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### Helly theorem application

Let $X$ be a normed space, $dim(X)=d$, let $r>0, A$ and $\subset X$ . Show that if every $d+1$ points of $A$ are contained in a closed ball of radius $r$, then $A$ is contained in a closed ball of ...
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### Why are generalized inequalities defined over proper cone?

Why generalized inequality is defined over a proper cone? What property does not hold if we define it over non-convex cone? Same with `pointed'. For example, generalized inequality makes sense in a ...
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### Convexity of the composite of convex function by exponential function

Let $\exp : \mathbb{R}^2 \to \mathbb{R}^2$ be the function given by $\exp(x_1,x_2) := (e^{x_1}, e^{x_2})$. Suppose that $f : \mathbb{R}^2 \to \mathbb{R}$ is a smooth (i.e. $\mathcal{C}^2$) convex ...
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### random pursuit without function evaluations

Assume we want to minimize a convex function $f(x)$ with $x\in \mathbb{R}^n$. Function $f(x)$ represents cost of a system which we cannot compute directly but can observe if system is at state $x$. My ...
### The Teichmüller space $T_g$ of a closed riemann surface $S_g$ of genus $g \geq 2$ can't be parametrized by $6g-6$ geodesic length functions
Setting: It is well known that the Teichmüller space $T_{g,b}$ of an oriented Riemann surface $S_{g,b}$ of genus $g \geq 2$ with $b \geq 1$ boundary components (satisfying $2g + b \geq 3$) can be ...