图 书 馆
贝叶斯非参数Bayesian Nonparametrics |
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| 课程网址: | http://videolectures.net/mlss2011_teh_nonparametrics/ |
| 主讲教师: | Yee Whye Teh |
| 开课单位: | 牛津大学 |
| 开课时间: | 2011-10-12 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Machine learning researchers often have to contend with issues of model selection and model fitting in the context of large complicated models and sparse data. The idea which I am pushing for in this project is that these can be nicely handled using Bayesian techniques. Model selection is selecting, among a class of models each of which has finite capacity, the model of the right capacity. Nonparametric Bayesian modelling sidesteps model selection by simply using models of potentially unbounded (or infinite) capacity. Overfitting is avoided simply by the usual Bayesian approach of integrating out all parameters (perhaps using MCMC or variational methods). |
| 关 键 词: | 机器学习; 复杂模型; 稀疏数据 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-07-23：cwx |
| 阅读次数: | 178 |