图 书 馆
潜在迪里克莱分配的在线学习Online Learning for Latent Dirichlet Allocation |
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| 课程网址: | http://videolectures.net/nips2010_hoffman_oll/ |
| 主讲教师: | Matt Hoffman |
| 开课单位: | Adobe公司 |
| 开课时间: | 2011-03-25 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | We develop an online variational Bayes (VB) algorithm for Latent Dirichlet Allocation (LDA). Online LDA is based on online stochastic optimization with a natural gradient step, which we show converges to a local optimum of the VB objective function. It can handily analyze massive document collections, including those arriving in a stream. We study the performance of online LDA in several ways, including by fitting a 100-topic topic model to 3.3M articles from Wikipedia in a single pass. We demonstrate that online LDA finds topic models as good or better than those found with batch VB, and in a fraction of the time. |
| 关 键 词: | 贝叶斯算法; 随机优化; 局部最优值 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-06-29：cxin |
| 阅读次数: | 98 |