how to discern between convex and non-convex objectives in practice?
chenruis
Convex objective may be able to be distinguished by second order derivative being constantly >=0.
large_goobler
Is it computationally expensive to determine whether a domain/objective is convex? My presumption is that even if so, it would save computes later.
haotingl
Does cost of determining whether a domain is convex or not depends on the complexity of the domain?
alexz2
Sum of squares can turn any concave optimization problem (that can be written in polynomial-ish thing) to a convex problem, but the problem may be too expensive to solve
stroucki
"If every line between two points within a domain lies within the domain, the domain is convex"
how to discern between convex and non-convex objectives in practice?
Convex objective may be able to be distinguished by second order derivative being constantly >=0.
Is it computationally expensive to determine whether a domain/objective is convex? My presumption is that even if so, it would save computes later.
Does cost of determining whether a domain is convex or not depends on the complexity of the domain?
Sum of squares can turn any concave optimization problem (that can be written in polynomial-ish thing) to a convex problem, but the problem may be too expensive to solve
"If every line between two points within a domain lies within the domain, the domain is convex"