图 书 馆
移位不变内核中的位置敏感二进制代码Locality-Sensitive Binary Codes from Shift-Invariant Kernels |
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| 课程网址: | http://videolectures.net/nips09_raginsky_lsbc/ |
| 主讲教师: | Maxim Raginsky |
| 开课单位: | 杜克大学 |
| 开课时间: | 2010-01-19 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | This paper addresses the problem of designing binary codes for high-dimensional data such that vectors that are similar in the original space map to similar binary strings. We introduce a simple distribution-free encoding scheme based on random projections, such that the expected Hamming distance between the binary codes of two vectors is related to the value of a shift-invariant kernel (e.g., a Gaussian kernel) between the vectors. We present a full theoretical analysis of the convergence properties of the proposed scheme, and report favorable experimental performance as compared to a recent state-of-the-art method, spectral hashing. |
| 关 键 词: | 高维数据; 随机投影; 二进制代码 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-09-06：lxf |
| 阅读次数: | 64 |