图 书 馆
无序列信息的线性动态系统的学习Learning Linear Dynamical Systems without Sequence Information |
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| 课程网址: | http://videolectures.net/icml09_huang_llds/ |
| 主讲教师: | Tzu-Kuo Huang |
| 开课单位: | 卡内基梅隆大学 |
| 开课时间: | 2009-08-26 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Virtually all methods of learning dynamic systems from data start from the same basic assumption: that the learning algorithm will be provided with a sequence, or trajectory, of data generated from the dynamic system. In this paper we consider the case where the data is not sequenced. The learning algorithm is presented a set of data points from the system's operation but with no temporal ordering. The data are simply drawn as individual disconnected points. While making this assumption may seem absurd at first glance, we observe that many scientific modeling tasks have exactly this property. In this paper we restrict our attention to learning linear, discrete time models. We propose several algorithms for learning these models based on optimizing approximate likelihood functions and test the methods on several synthetic data sets. |
| 关 键 词: | 动态系统; 时间顺序; 近似似然函数 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-12-05：lxf |
| 阅读次数: | 62 |