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9.520 统计学习理论与应用9.520 Statistical Learning Theory and Applications |
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| 课程网址: | http://ocw.mit.edu/courses/brain-and-cognitive-sciences/9-520-sta... |
| 主讲教师: | Dr. Ryan Rifkin ; Dr. Sayan Mukherjee ; Prof. Tomaso Poggio; Alex Rakhlin |
| 开课单位: | 麻省理工学院 |
| 开课时间: | 2006-01-01 |
| 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: | 监督学习; 统计学习; 多元函数; 支持向量机; 回归; 分类; VC理论; 计算机视觉; 计算机图形学; 生物信息学 |
| 课程来源: | 麻省理工学院公开课 |
| 最后编审: | 2024-05-11：chenjy |
| 阅读次数: | 41 |