图 书 馆
收敛的消息传递算法推理在一般图凸自由能量Convergent Message-Passing Algorithms for Inference over General Graphs with Convex Free Energies |
|
| 课程网址: | http://videolectures.net/uai08_hazan_cmpa/ |
| 主讲教师: | Tamir Hazan |
| 开课单位: | 耶路撒冷希伯来大学 |
| 开课时间: | 2008-07-30 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Inference problems in graphical models can be represented as a constrained optimization of a free energy function. It is known that when the Bethe free energy is used, the fixed points of the belief propagation (BP) algorithm correspond to the local minima of the free energy. However BP fails to converge in many cases of interest. Moreover, the Bethe free energy is non-convex for graphical models with cycles thus introducing great difficulty in deriving efficient algorithms for finding local minima of the free energy for general graphs. In this paper we introduce two efficient BP-like algorithms, one sequential and the other parallel, that are guaranteed to converge to the global minimum, for any graph, over the class of energies known as ”convex free energies”. In addition, we propose an efficient heuristic for setting the parameters of the convex free energy based on the structure of the graph. |
| 关 键 词: | 计算机科学; 机器学习; 图形模型; 人工智能 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-11-16：cwx |
| 阅读次数: | 42 |