# Tagged Questions

Convex Optimization is a special case of mathematical optimization. It includes Linear Programming and least-squares.

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### Solve the closed form solution for argmax of $x^Ty - x^T\ln(x)$

Let $y \in \mathbb{R}^n, \ln(x) = \begin{bmatrix} \ln(x_1) \\ \vdots \\ \ln(x_n) \end{bmatrix} \in \mathbb{R}^n$ Show that $$x^* = \text{argmax}_{x \in \mathcal{D}} \quad x^Ty - x^T\ln(x)$$ ...
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### Solving $I^* = \arg\min_{I'} \left( \|\phi_\ell(I) - \phi_\ell(I')\|_2^2 + R(I') \right)$ with gradient descent

I am trying to create the results from this a paper that is trying to understand the types of features a convolutional neural network is learning to recognize. I don't think understanding ...
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### Benders decomposition Master Problem

I am currently working on implementation of Bender's Decomposition for MIP. I am looking at the simplest model \begin{split} \min_{x,y} &\; c^Tx + f(y)\\ s.t. & \; Ax + Dy \ge ...
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### Interpolating polynomial such that it is convex in specified region

The problem I have is that I have data at two points $x_1,x_2$ and $x_2>x_1>0$. At these two points, I know that the function $f$ has values $f(x_1)$ and $f(x_2)$ respectively. It is also ...
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### On accelerated Proximal Gradient Methods

I am working on accelerated optimization scheme, which unified in the paper by Paul Tseng, "On Accelerated Proximal Gradient Methods for Convex-Concave Optimization". But unfortunately, it is ...
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### Is convexity the most general dividing line between “easy” and “hard” optimization problems?

Just got started with Boyd's Convex Optimization. It's great stuff and I see how it directly subsumes the all-important linear programming class of models. However, it seems that if a problem is non-...
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### Does projected gradint descent(pgd) results in the same minimizer as the one given by unconstrained gd and projected back on the constrained set?

For $f: \mathbb{R}^n \mapsto \mathbb{R}$ with $f(x) < \infty,\;\forall x \in \mathbb{R}^n$ and for convenience let's assume $f$ is continuously differentiable. Suppose we are trying to solve the ...
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### Finding minimizer from different order

Let a nonnegative function $f(x,y)$: $\mathbb R^2\to \mathbb R$ be second order continuous differentiable. We also know that $f$ is not convex in its two arguments, but only separately in each of them....
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### Is generalized mean convex / concave?

The generalized mean can be given using the following equation: $M_p(x_1, \dots, x_n) = (\frac{1}{n}\sum_i x_i^p)^{1/p}$ Is it convex /concave when $p<1$ ?
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### Conjugate of difference of convex functions

I am reading through this tutorial on DC programming and the author makes a startling claim without proof: If $g$ and $h$ are two lower semi-continuous convex function, then the conjugate function of ...