图 书 馆
一种高效的分层音素分类在线算法An Efficient Online Algorithm for Hierarchical Phoneme Classification |
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| 课程网址: | http://videolectures.net/mlmi04ch_keshet_eoahp/ |
| 主讲教师: | Joseph Keshet |
| 开课单位: | 耶路撒冷希伯来大学 |
| 开课时间: | 2007-02-25 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | We present an algorithmic framework for supervised classification learning where the set of labels is organized in a predefined hierarchical structure. This structure is encoded by a rooted tree which induces a metric over the label set. Our approach combines ideas from large margin kernel methods and Bayesian analysis. Following the large margin principle, we associate a prototype with each label in the tree and formulate the learning task as an optimization problem with varying margin constraints. In the spirit of Bayesian methods, we impose similarity requirements between the prototypes corresponding to adjacent labels in the hierarchy. We describe a new online algorithm for solving the hierarchical classification problem and derive a worst case loss-bound for the algorithm. We demonstrate the merits of our approach with a series of experiments on synthetic data and speech data. |
| 关 键 词: | 监督分类学习; 算法框架; 分层结构组织 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-07-02：cjy |
| 阅读次数: | 65 |