Knowledge Commons of Institute of Automation，CAS
| Consensus hashing | |
Leng, Cong ; Cheng, Jian
| |
| 发表期刊 | MACHINE LEARNING
 |
| 2015-09-01 | |
| 卷号 | 100期号:2-3页码:379-398 |
| 文章类型 | Article |
| 摘要 | Hashing techniques have been widely used in many machine learning applications because of their efficiency in both computation and storage. Although a variety of hashing methods have been proposed, most of them make some implicit assumptions about the statistical or geometrical structure of data. In fact, few hashing algorithms can adequately handle all kinds of data with different structures. When considering hybrid structure datasets, different hashing algorithms might produce different and possibly inconsistent binary codes. Inspired by the successes of classifier combination and clustering ensembles, in this paper, we present a novel combination strategy for multiple hashing results, named consensus hashing. By defining the measure of consensus of two hashing results, we put forward a simple yet effective model to learn consensus hash functions which generate binary codes consistent with the existing ones. Extensive experiments on several large scale benchmarks demonstrate the overall superiority of the proposed method compared with state-of-the-art hashing algorithms. |
| WOS标题词 | Science & Technology ; Technology |
| DOI | 10.1007/s10994-015-5496-x |
| 关键词[WOS] | SEARCH |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS研究方向 | Computer Science |
| WOS类目 | Computer Science, Artificial Intelligence |
| WOS记录号 | WOS:000359747100009 |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://ir.ia.ac.cn/handle/173211/8910 |
| 专题 | 紫东太初大模型研究中心_图像与视频分析 |
| 作者单位 | Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing, Peoples R China |
| 第一作者单位 | 模式识别国家重点实验室 |
| 推荐引用方式 GB/T 7714 | Leng, Cong,Cheng, Jian. Consensus hashing[J]. MACHINE LEARNING,2015,100(2-3):379-398. |
| APA | Leng, Cong,&Cheng, Jian.(2015).Consensus hashing.MACHINE LEARNING,100(2-3),379-398. |
| MLA | Leng, Cong,et al."Consensus hashing".MACHINE LEARNING 100.2-3(2015):379-398. |
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