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Convex Optimization is a special case of mathematical optimization where the feasible region is convex and the objective is to either minimize a convex function or maximize a concave function.
1
vote
Underdetermined Minimum Volume Enclosing Ellipsoid
You don't need SDP for an easy task like this. $X$ are your points. Do a PCA on $Y Y', Y = X - \operatorname{mean}(X)$, reduce dimension to 2-dimensions (others dimensions are zeros). 3 points on the …
0
votes
Semi-Definite relaxation of non-linear constraint?
square both side ?
(1-k)^2*trace(A*X)^2 == k^2*trace(B*X)
(1-k)^2*trace(A*X)^2 - k^2*trace(B*X) == 0
move from SDP to QCQP.
Or move to unconstrained problem with last term penalized with quadratic …
3
votes
0
answers
119
views
Why the MIRACLE of Lanczos/CG-like?
Lanczos/Arnoldi/Rietz/CG-like algorithm share the same core strategy...
In each, a little miracle appears, most of the Gram-Schmidt inner products are zeroes! In others words, new direction need only …