0
votes
1answer
37 views

How to show $f(x,y) \leq \theta f(x,y) + (1-\theta)f(x,y)$ for $\theta \in [0,1]$?

Let $\theta \in [0, 1]$. Let $f(x,y)$ be a function. Is there a way I could prove that $f(x,y) \leq \theta f(x,y) + (1-\theta)f(x,y)$? I have tried to start with $f(x,y) = 2f(x,y) - f(x,y)$ or ...
0
votes
1answer
28 views

Transform unconstrained optimization problems into constrained ones?

I want to formally show that the following minimization problem $$ \min_\theta||\max(0,f_1(\theta)),...,\max(0,f_n(\theta))||^2 $$ is equivalent to $$ \min_{\beta, \{w_i \}^{n}_{i=1}} ...
3
votes
1answer
56 views

Prove that $e^{tx} \le xe^t + 1-x$

Prove that $$e^{tx} \le xe^t + 1-x$$ for $t \ge 1$ and $0 \le x \le 1$ I think I need to use the fact that e is convex? But I can't quite see it. Any help appreciated Thanks.
2
votes
0answers
66 views

How to prove the convexity of the logrithmic gamma function?

Here's what I did: $$\Gamma'(z)=\int_0^\infty \log(t)e^{-t}t^{z-1}dt$$ $$\Gamma''(z)=\int_0^\infty ...
2
votes
0answers
31 views

Strictly convex self-concordant function

Some definitions: A function $f:R^n\rightarrow R$ is convex[strictly convex] if for every $\lambda\in[0,1]$ [$\lambda\in(0,1)$] and for every $x,y$ [$x\neq y$] in $R^n$ we have $f(\lambda ...
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 ...
1
vote
0answers
55 views

Joint cost function with Lagrangian

How can I formulate joint cost functions if Lagrangians are involved? For example, if I have $J_1 = \|\mathbf{Ax} - \mathbf{b}\|^2_2 + \lambda f$ and $J_2 = \|\mathbf{Cx} - \mathbf{d}\|^2_2$, ...
0
votes
1answer
34 views

Help with a property of a convex function

I'm studying linear and nonlinear programming and on my book I bumped into the following statement: $$\lim_{\alpha \to 0} \displaystyle \frac{f(\textbf{x}+\alpha ...
3
votes
1answer
265 views

Solving optimization problems using derivatives and critical points

I have a homework question which I have completed 2/3 of; however I am stuck on the last part of the question. The question is: A drug used to treat cancer is effective at low doses with an ...
3
votes
1answer
87 views

Showing existence of solution by positive definiteness/convexity

For a physics problem, I am considering the following problem: I have a certain function, $S: \mathbb{R}^M \rightarrow \mathbb{R}$, of which the critical points, given by $$ \frac{\partial ...
1
vote
1answer
64 views

Is this function involving matrices convex?

Let $X\in \mathbb{R}^{n \times n}$. Then, is the function $$ \text{Tr}\left( (X^T X )^{-1} \right)$$ convex in $X$? ($\text{Tr}$ denotes the trace operator)
3
votes
1answer
166 views

Hessian of a function that takes matrix arguments

I have a function that that takes a matrix and returns a scalar, $f : \mathbb{R}^{m\times n} \rightarrow \mathbb{R}$. I know how to calculate the derivative of this function with respect to the matrix ...
3
votes
1answer
136 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 ...
0
votes
1answer
261 views

Maximization of sum of two functions

Is there any relationship similar to the following. Let $X$ be the maximum of functions $f_1(x)+f_2(x)$. Let $X_1$ be a maximum of $f_1(x)$ and let $X_2$ be a maximum of $f_2(x)$. Is there any ...
2
votes
2answers
107 views

Constrained maximization problem

I need help with the following optimization problem $$ \max\;\alpha\ln(x(1-y^2))+(1-\alpha)\ln(z) $$ where the maximization is with respect to $x,y,z$, subject to \begin{align} \alpha ...
1
vote
0answers
191 views

How to find $\kappa$ to minimize integral $I = \frac{1}{\kappa}\int\limits_{0}^{T} \mathrm{exp}\left(-f(\kappa,x)\right) \mathrm{d}x$

I am trying to find such value $\kappa \in (0,1)$ that would minimize the integral \begin{equation} \begin{aligned} I = \frac{1}{\kappa}\int\limits_{0}^{T} \mathrm{exp}\left(-f(\kappa,x)\right) ...
0
votes
1answer
267 views

Global Min-Max Optimization

When is \begin{equation} \min_X \max_Y f(X,Y) \end{equation} globally solvable? (i.e. we can find global solution for the optimization problem?) I am not looking for reformulations. Is it only when ...
3
votes
0answers
211 views

Global optimum of sum of convex functions

Take two real differentiable convex functions, $f_1$ and $f_2$, defined on the unit interval $[0; 1]$. I want to find the global optimum of: $\min_{x \in [0;1]} af_1(x)+bf_2(x)$, for given $a, b \in ...
0
votes
2answers
178 views

Simple example where strong convexity is necessary over strict (or even regular) convexity.

I am trying to get a hold on exactly what strong convexity gives you over strict (or regular) convexity. Yes there are simple functions which demonstrate the difference between these ideas, but what ...
1
vote
2answers
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 ...
2
votes
1answer
676 views

Maximum likelihood covariance estimation of Gaussian

I was reading these notes on matrix calculus http://research.microsoft.com/en-us/um/people/minka/papers/matrix/minka-matrix.pdf and I could not figure out how to go from equation (30) to (31). Any ...
1
vote
0answers
164 views

Convexity of a Set

Consider the following function, $$ f(x, y) = e^{m e^{-y}+n e^{-x}-x-y} \left(a x e^y+b e^x y+c x y\right) $$ where $a, b, c, m$ and $n$ are positive constants. I want to show $f(x, y)$ is ...