Center-of-gravity method
For convex set
,
convex function
,
we want to minimize
over
Algorithm:
- For
:
- at step
,
let
.
- compute gradient
.
- Return
Proof
By Grünbaum's theorem, cut
the volume of the search space by constant every step. #incomplete
idea: minimizing convex function over convex set using “natural
plane-cutting method”
center of gravity of convex set
defined as:
Additionally, for two convex
sets and ,
the
intersection is
also convex. To see this, consider two
points .
Then for
any ,
we have
because
are in
and
because
are in
.
Drawbacks: computing centroid in general is hard, #P-hard when
is intersection of half-spaces (polytope)
…
Hence, consider Ellipsoid
method
References:
- A. Y. Levin. On an algorithm for the minimization of convex
functions over convex functions. Soviet Mathematics Doklady,
160(1244–1247), 1965. https://www.mathnet.ru/php/archive.phtml?wshow=paper&jrnid=dan&paperid=30770&option_lang=eng
- D. J. Newman. Location of the maximum on unimodal surfaces. J.
ACM, 12(3):395–398, July 1965.
- https://www.chrismusco.com/amlds2023/notes/lecture09.html
- https://www.cs.cmu.edu/~anupamg/advalgos17/scribes/lec16.pdf