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Nov, 2014
利用半定松弛和应用程序实现大规模的二值二次规划
Large-scale Binary Quadratic Optimization Using Semidefinite Relaxation and Applications
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Peng Wang, Chunhua Shen, Anton van den Hengel
TL;DR
本文提出了一种针对大规模二次二次规划问题的新型SDP(半定规划)公式,并基于此提出了两种求解方法,即准牛顿法和平滑牛顿法,该方法能有效地解决许多计算机视觉问题,包括聚类、图像分割、共同分割和注册等。
Abstract
In
computer vision
, many problems such as image segmentation, pixel labelling, and scene parsing can be formulated as
binary quadratic programs
(BQPs). For submodular problems, cuts based methods can be employed
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