Consensus hashing
Leng, Cong; Cheng, Jian
2015-09-01
发表期刊MACHINE LEARNING
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
DOI10.1007/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
专题模式识别国家重点实验室_图像与视频分析
作者单位Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing, Peoples R China
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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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