图 书 馆
一种对偶映射线性松弛的交替方向法An Alternating Direction Method for Dual MAP LP Relaxation |
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| 课程网址: | http://videolectures.net/ecmlpkdd2011_globerson_alternating/ |
| 主讲教师: | Amir Globerson |
| 开课单位: | 耶路撒冷希伯来大学 |
| 开课时间: | 2011-10-03 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Maximum a-posteriori (MAP) estimation is an important task in many applications of probabilistic graphical models. Although finding an exact solution is generally intractable, approximations based on linear programming (LP) relaxation often provide good approximate solutions. In this paper we present an algorithm for solving the LP relaxation optimization problem. In order to overcome the lack of strict convexity, we apply an augmented Lagrangian method to the dual LP. The algorithm, based on the alternating direction method of multipliers (ADMM), is guaranteed to converge to the global optimum of the LP relaxation objective. Our experimental results show that this algorithm is competitive with other state-of-the-art algorithms for approximate MAP estimation. |
| 关 键 词: | 计算机科学; 机器学习; 图形模型 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2021-02-16：nkq |
| 阅读次数: | 32 |