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Greedy Direction Method of Multiplier for MAP Inference of Large Output Domain
Maximum-a-Posteriori (MAP) inference lies at the heart of Graphical Models and Structured Prediction. Despite the intractability of exact MAP inference, approximate methods based on LP relaxations have exhibited superior performance across a wide range of applications. Yet for problems involving lar...
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| 出版年: | JMLR Workshop Conf Proc |
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| 主要な著者: | , , , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
2017
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5581664/ https://ncbi.nlm.nih.gov/pubmed/28871273 |
| タグ: |
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