图 书 馆
机器学习中的优化算法Optimization Algorithms in Machine Learning |
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| 课程网址: | http://videolectures.net/nips2010_wright_oaml/ |
| 主讲教师: | Stephen J. Wright |
| 开课单位: | 威斯康星大学 |
| 开课时间: | 2011-01-12 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Optimization provides a valuable framework for thinking about, formulating, and solving many problems in machine learning. Since specialized techniques for the quadratic programming problem arising in support vector classification were developed in the 1990s, there has been more and more cross-fertilization between optimization and machine learning, with the large size and computational demands of machine learning applications driving much recent algorithmic research in optimization. This tutorial reviews the major computational paradigms in machine learning that are amenable to optimization algorithms, then discusses the algorithmic tools that are being brought to bear on such applications. We focus particularly on such algorithmic tools of recent interest as stochastic and incremental gradient methods, online optimization, augmented Lagrangian methods, and the various tools that have been applied recently in sparse and regularized optimization. |
| 关 键 词: | 机器学习; 向量分类; 拉格朗日方法 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-07-14：yumf |
| 阅读次数: | 48 |