为印度自助餐流程加速吉布斯抽样][Accelerated Gibbs Sampling for the Indian Buffet Process ]

为印度自助餐流程加速吉布斯抽样 Accelerated Gibbs Sampling for the Indian Buffet Process


课程网址:	http://videolectures.net/icml09_doshi_velez_ags/
主讲教师:	Finale Doshi
开课单位:	剑桥大学
开课时间:	2009-08-26
课程语种:	英语
中文简介:	我们经常寻求在一组观察中识别共同发生的隐藏特征。印度自助餐过程（IBP）为每个观察中提供的特征提供了非参数先验，但IBP的当前推理技术通常难以扩展。用于IBP的折叠的Gibbs采样器具有观察数量的运行时间立方体，并且未折叠的Gibbs采样器虽然是线性的，但通常混合缓慢。我们提出了一个新的线性时间折叠Gibbs采样器的共轭似然模型，并证明了它在大型真实世界数据集上的功效。
课程简介:	We often seek to identify co-occurring hidden features in a set of observations. The Indian Buffet Process (IBP) provides a nonparametric prior on the features present in each observation, but current inference techniques for the IBP often scale poorly. The collapsed Gibbs sampler for the IBP has a running time cubic in the number of observations, and the uncollapsed Gibbs sampler, while linear, is often slow to mix. We present a new linear-time collapsed Gibbs sampler for conjugate likelihood models and demonstrate its efficacy on large real-world datasets.
关键词:	非参数; 印度自助餐过程; 线性
课程来源:	视频讲座网
最后编审:	2019-04-21：lxf
阅读次数:	142

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