Large-scale binary quadratic optimization using semidefinite relaxation and applications
In computer vision, many problems can be formulated as binary quadratic programs (BQPs), which are in general NP hard. Finding a solution when the problem is of large size to be of practical interest typically requires relaxation. Semidefinite relaxation usually yields tight bounds, but its computat...
| Main Authors: | , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
IEEE
2016
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