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Optimization with convex constraints and convex objectives; notions related to convex optimization such as sub-gradients, normal cones, separating hyperplanes
1
vote
0
answers
101
views
When does the metric projection operator have a closed form?
I have a simple question. Often times in optimization, the following function is used:
Let $H$ be a real Hilbert space and $C$ a nonempty closed convex subset of $H$, then the metric projection is def …
0
votes
1
answer
115
views
Are there search algorithms that are competitive against (gradient based) optimization routi...
Suppose that $f: \mathbb{R}^n \to \mathbb{R}$ is a continuous function for which we want to minimize. We may arbitrarily impose good conditions for $f$, such as Lipschitzness, smoothness, convexity, e …
3
votes
1
answer
271
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What is a non-trivial example of an unbounded subdifferential?
Let $f: X \to [ -\infty, \infty]$ be some function,
Can someone provide a non-trivial example where the subdifferential evaluated at a point $x$,
$$\partial f(x)$$ is "unbounded"? (trivial examples i …