图 书 馆
序列数据的随机存储器A Stochastic Memoizer for Sequence Data |
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| 课程网址: | http://videolectures.net/icml09_wood_sms/ |
| 主讲教师: | Frank Wood |
| 开课单位: | 伦敦大学学院 |
| 开课时间: | 2009-08-26 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | We propose an unbounded-depth, hierarchical, Bayesian nonparametric model for discrete sequence data. This model can be estimated from a single training sequence, yet shares statistical strength between subsequent symbol predictive distributions in such a way that predictive performance generalizes well. The model builds on a specific parameterization of an unbounded-depth hierarchical Pitman-Yor process. We introduce analytic marginalization steps (using coagulation operators) to reduce this model to one that can be represented in time and space linear in the length of the training sequence. We show how to perform inference in such a model without truncation approximation and introduce fragmentation operators necessary to do predictive inference. We demonstrate the sequence memoizer by using it as a language model, achieving state-of-the-art results. |
| 关 键 词: | 离散序列数据; 贝叶斯非参数模型; 无界深度分层 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-04-24：lxf |
| 阅读次数: | 28 |