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Optimization with convex constraints and convex objectives; notions related to convex optimization such as sub-gradients, normal cones, separating hyperplanes

3 votes

Does removing some constraints in convex program change the optimal solution?

In convex optimization, a local optimum is a global one. So if you do not change the neighbourhood of the optimal solution, you do not change the optimal solution.
J Fabian Meier's user avatar
1 vote
Accepted

A difficult combinatorial optimization problem

First of all, one can shift the set $\mathcal{J}$ so that the condition $x_i \leq 1$ can be replaced by $x_i \geq 0$. Let $M_i$ be the maximal absolute value of $x_i$ in $\mathcal{J}$, then we can i …
J Fabian Meier's user avatar
2 votes

Fastest 'Oracle' Algorithm for satisfying a single linear constraint on a convex set?

Actually, I guess that they do not mean that such an oracle always exists. Usually, the argument is of the form: If, for your special problem, you have a quick method of checking if this problem has a …
J Fabian Meier's user avatar