Name
Abstract | ||
|---|---|---|
We tackle the problem of graph partitioning for image segmentation using correlation clustering (CC), which we treat as an integer linear program (ILP). We reformulate optimization in the ILP so as to admit efficient optimization via Benders decomposition, a classic technique from operations research. Our Benders decomposition formulation has many subproblems, each associated with a node in the CC... |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/MLHPCAI4S51975.2020.00009 | 2020 IEEE/ACM Workshop on Machine Learning in High Performance Computing Environments (MLHPC) and Workshop on Artificial Intelligence and Machine Learning for Scientific Applications (AI4S) |
Keywords | DocType | ISBN |
correlation clustering,minimum cost multicuts,Benders Decomposition | Conference | 978-1-6654-2291-8 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jovita Lukasik | 1 | 0 | 0.68 |
| Margret Keuper | 2 | 136 | 14.38 |
| m k singh | 3 | 118 | 5.18 |
| Julian Yarkony | 4 | 76 | 9.20 |