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Operations research, linear programming, control theory, systems theory, optimal control, game theory
29
votes
7
answers
8k
views
Solving NP problems in (usually) Polynomial time?
Just because a problem is NP-complete doesn't mean it can't be usually solved quickly.
The best example of this is probably the traveling salesman problem, for which extraordinarily large instances …
51
votes
7
answers
23k
views
Is all non-convex optimization heuristic?
Convex Optimization is a mathematically rigorous and well-studied field. In linear programming a whole host of tractable methods give your global optimums in lightning fast times. Quadratic programmin …
2
votes
1
answer
130
views
Are there intuitive/classically algorithmic analogues to Semidefinite programs on networks?
Many network optimization algorithms, including shortest path, push-relabel, augmenting path, etc, actually have an interpretation in terms of linear programming.
A famous application of semidefinite …
0
votes
0
answers
269
views
L1-regularized Least Squares on a matrix with Toeplitz Blocks (not block-Toeplitz)
I am trying to speed up a sparse signal recovery algorithms.
My sensing matrix is a set of Toeplitz Blocks, M = [T1,T2,T3,...,Tk]
The objective is min ||Mx - b||_2^2 + ||x||1
What I'm actually doin …
3
votes
1
answer
357
views
Mathematical Programming with other Algebras than Linear
Linear Programming is strongly entwined with linear algebra, as are many of its generalizations under the heading of mathematical programming / convex optimization.
What analogies are there for conve …
1
vote
2
answers
479
views
Optimizing directly on the eigenspectrum of a matrix
I have an application where I want to the eigenvalues of the graph to be involved in the objective and constraints in a flexible way (moreso than just the nuclear or frobenius norm). Whats a good surv …