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马尔科夫逻辑网络的最大边缘权重学习Max-Margin Weight Learning for Markov Logic Networks |
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| 课程网址: | http://videolectures.net/ecmlpkdd09_huynh_mmwlmln/ |
| 主讲教师: | Tuyen Ngoc Huynh |
| 开课单位: | 德克萨斯大学 |
| 开课时间: | 2009-10-20 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Markov logic networks (MLNs) are an expressive representation for statistical relational learning that generalizes both first-order logic and graphical models. Existing discriminative weight learning methods for MLNs all try to learn weights that optimize the Conditional Log Likelihood (CLL) of the training examples. In this work, we present a new discriminative weight learning method for MLNs based on a max-margin framework. This results in a new model, Max-Margin Markov Logic Networks (M3LNs), that combines the expressiveness of MLNs with the predictive accuracy of structural Support Vector Machines (SVMs). To train the proposed model, we design a new approximation algorithm for loss-augmented inference in MLNs based on Linear Programming (LP). The experimental result shows that the proposed approach generally achieves higher $F_1$ scores than the current best discriminative weight learner for MLNs. |
| 关 键 词: | 马尔可夫逻辑网络; 统计学习; 线性规划; 向量机 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-06-08：yumf |
| 阅读次数: | 41 |