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9.520统计学习理论与应用（麻省理工学院）9.520 Statistical Learning Theory and Applications (MIT) |
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| 课程网址: | http://ocw.mit.edu/courses/brain-and-cognitive-sciences/9-520-sta... |
| 主讲教师: | 信息不详。欢迎您在右侧留言补充。 |
| 开课单位: | 麻省理工学院 |
| 开课时间: | 信息不详。欢迎您在右侧留言补充。 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Focuses on the problem of supervised learning from the perspective of modern statistical learning theory starting with the theory of multivariate function approximation from sparse data. Develops basic tools such as Regularization including Support Vector Machines for regression and classification. Derives generalization bounds using both stability and VC theory. Discusses topics such as boosting and feature selection. Examines applications in several areas: computer vision, computer graphics, text classification and bioinformatics. Final projects and hands-on applications and exercises are planned, paralleling the rapidly increasing practical uses of the techniques described in the subject. |
| 关 键 词: | 多元函数; 泛化界; 近似稀疏数据 |
| 课程来源: | 信息不详。欢迎您在右侧留言补充。 |
| 最后编审: | 2015-10-12：linxl |
| 阅读次数: | 438 |