图 书 馆
内核的贝叶斯规则Kernel Bayes Rule |
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| 课程网址: | http://videolectures.net/nipsworkshops2012_fukumizu_bayes/ |
| 主讲教师: | Kenji Fukumizu |
| 开课单位: | 日本统计数理研究所 |
| 开课时间: | 2013-01-06 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | A nonparametric kernel-based method for realizing Bayes’ rule is proposed, based on representations of probabilities in reproducing kernel Hilbert spaces. Probabilities are uniquely characterized by the mean of the canonical map to the RKHS. The prior and conditional probabilities are expressed in terms of RKHS functions of an empirical sample: no explicit parametric model is needed for these quantities. The posterior is likewise an RKHS mean of a weighted sample. The estimator for the expectation of a function of the posterior is derived, and rates of consistency are shown. Some representative applications of the kernel Bayes’ rule are presented, including Baysian computation without likelihood and filtering with a nonparametric state-space model. |
| 关 键 词: | 贝叶斯规则; 条件概率; 样本空间函数; 平均加权样本 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-05-22：王淑红(课程编辑志愿者) |
| 阅读次数: | 291 |