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Archipelago：非参数贝叶斯半监督学习Archipelago: Nonparametric Bayesian Semi-Supervised Learning |
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| 课程网址: | http://videolectures.net/icml09_adams_anb/ |
| 主讲教师: | Ryan Prescott Adams |
| 开课单位: | 多伦多大学 |
| 开课时间: | 2009-08-26 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Semi-supervised learning (SSL), is classification where additional unlabeled data can be used to improve accuracy. Generative approaches are appealing in this situation, as a model of the data’s probability density can assist in identifying clusters. Nonparametric Bayesian methods, while ideal in theory due to their principled motivations, have been difficult to apply to SSL in practice. We present a nonparametric Bayesian method that uses Gaussian processes for the generative model, avoiding many of the problems associated with Dirichlet process mixture models. Our model is fully generative and we take advantage of recent advances in Markov chain Monte Carlo algorithms to provide a practical inference method. Our method compares favorably to competing approaches on synthetic and real-world multi-class data. |
| 关 键 词: | 半监督学习; 概率密度; 非参数贝叶斯方法 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-04-21：lxf |
| 阅读次数: | 98 |