Timeline for Comparing computational complexity of convex optimization and a heuristic algorithm
Current License: CC BY-SA 3.0
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| Jan 11, 2015 at 21:45 | comment | added | Cror2014 | Thanks for your answer. The thing is that the problem has 3 dimensional variables and I will need to increase the size of each dimension. However right now, even with small size of the dimensions, algorithm 1 takes a lot of iterations to converge. Therefore testing with the large numbers for each dimension even might not be possible due to very low convergence. Is there any bound for the convergence rate of the subgradient method? It might be possible to explain complexity by saying that it needs O(f(error)) iterations and each iteration has O(f(Y)) computations. | |
| Jan 11, 2015 at 21:18 | history | answered | Bill Barth | CC BY-SA 3.0 |