图 书 馆
高斯过程的非线性矩阵分解Non-Linear Matrix Factorization with Gaussian Processes |
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| 课程网址: | http://videolectures.net/icml09_urtasun_nlmf/ |
| 主讲教师: | Raquel Urtasun |
| 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: | A popular approach to collaborative filtering is matrix factorization. In this paper we consider the "probabilistic matrix factorization" and by taking a latent variable model perspective we show its equivalence to Bayesian PCA. This inspires us to consider probabilistic PCA and its non-linear extension, the Gaussian process latent variable model (GP-LVM) as an approach for probabilistic non-linear matrix factorization. We apply approach to benchmark movie recommender data sets. The results show better than previous state-of-the-art performance. |
| 关 键 词: | 协同过滤; 矩阵分解; 潜变量模型 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-04-24：lxf |
| 阅读次数: | 113 |