图 书 馆
非负矩阵分解通过秩一停机日期Nonnegative Matrix Factorization via Rank-One Downdate |
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| 课程网址: | http://videolectures.net/icml08_ghodsi_nmf/ |
| 主讲教师: | Ali Ghodsi |
| 开课单位: | 滑铁卢大学 |
| 开课时间: | 2008-07-29 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Nonnegative matrix factorization (NMF) was popularized as a tool for data mining by Lee and Seung in 1999. NMF attempts to approximate a matrix with nonnegative entries by a product of two low-rank matrices, also with nonnegative entries. We propose an algorithm called rank-one downdate (R1D) for computing a NMF that is partly motivated by singular value decomposition. This algorithm computes the dominant singular values and vectors of adaptively determined submatrices of a matrix. On each iteration, R1D extracts a rank-one submatrix from the dataset according to an objective function. We establish a theoretical result that maximizing this objective function corresponds to correctly classifying articles in a nearly separable corpus. We also provide computational experiments showing the success of this method in identifying features in realistic datasets. The method is much faster than either LSI or other NMF routines. |
| 关 键 词: | 非负矩阵分解; 语料库; 修正幂迭代 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-06-04：毛岱琦(课程编辑志愿者) |
| 阅读次数: | 58 |