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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 …
Sin Nombre's user avatar
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 …
Sin Nombre's user avatar
3 votes
1 answer
271 views

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 …
Sin Nombre's user avatar