图 书 馆
利用聚类结构预测图的标号Exploiting Cluster Structure to Predict The Labeling of a Graph |
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| 课程网址: | http://videolectures.net/wehys08_herbster_ecspl/ |
| 主讲教师: | Mark Herbster |
| 开课单位: | 伦敦大学学院 |
| 开课时间: | 2008-12-13 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | The nearest neighbor and the perceptron algorithms are intuitively motivated by the aims to exploit the "cluster" and "linear separation" structure of the data to be classified, respectively. We develop a new online perceptron-like algorithm, Pounce, to exploit both types of structure. We refine the usual margin-based analysis of a perceptron-like algorithm to now additionally reflect the cluster-structure of the input space. We apply our methods to study the problem of predicting the labeling of a graph. We find that when both the quantity and extent of the clusters are small we may improve arbitrarily over a purely margin-based analysis. |
| 关 键 词: | 聚类; 线性分离; 算法 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-10-29：cwx |
| 阅读次数: | 22 |