An analysis of convex relaxations for MAP estimation of discrete MRFs
<p>The problem of obtaining the maximum a <em>posteriori</em> estimate of a general discrete Markov random field (i.e., a Markov random field defined using a discrete set of labels) is known to be NP-hard. However, due to its central importance in many applications, several approxi...
| Main Authors: | , , |
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| 格式: | Journal article |
| 語言: | English |
| 出版: |
Journal of Machine Learning Research
2009
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