Name
Title | ||
|---|---|---|
A branch and bound approach for a class of non-convex problems with applications to robust regression |
Abstract | ||
|---|---|---|
We consider a class of non-convex problems, with application to robust regression and robust support vector machines. We propose an algorithm that computes the exact solution using a branch and bound approach in parameter space. Numerical experiments show that, in some cases, the time complexity of the algorithm is linear with respect to the number of samples, while it is exponential with respect to the number of regressors. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/MED.2017.7984148 | 2017 25th Mediterranean Conference on Control and Automation (MED) |
Keywords | Field | DocType |
branch and bound approach,nonconvex problems,robust regression,robust support vector machines,parameter space,time complexity | Approximation algorithm,Applied mathematics,Mathematical optimization,Branch and bound,Control theory,Branch and cut,Robustness (computer science),Robust regression,Convex function,Linear programming,Time complexity,Mathematics | Conference |
ISSN | ISBN | Citations |
2325-369X | 978-1-5090-4534-1 | 0 |
PageRank | References | Authors |
0.34 | 3 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Francesco Denaro | 1 | 0 | 0.68 |
| Luca Consolini | 2 | 276 | 31.16 |
| Marco Locatelli | 3 | 926 | 80.28 |