{"title":"加权网格主成分分析哈希","authors":"Xiancheng Zhou, Zhi-Qian Huang, Wing W. Y. Ng","doi":"10.1109/ICMLC.2014.7009117","DOIUrl":null,"url":null,"abstract":"Principal Component Analysis (PCA) is one of the most widely used components of hashing. In this paper, we propose three PCA-based hashing methods to improve the performance of the Principal Component Hashing (PCH). Different principal components have different among of variances of data. In the PCH, each principal component corresponds to a hash function. Hence, the PCH treats each principal component to have the same importance which will lead to the loss of much information in constructing hashing table. To deal with this shortage, we propose the weighted PCH (WPCH), the grid PCH (GPCH) and the weighted grid PCH (WGPCH).","PeriodicalId":335296,"journal":{"name":"2014 International Conference on Machine Learning and Cybernetics","volume":"39 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Weighted grid Principal Component Analysis hashing\",\"authors\":\"Xiancheng Zhou, Zhi-Qian Huang, Wing W. Y. Ng\",\"doi\":\"10.1109/ICMLC.2014.7009117\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Principal Component Analysis (PCA) is one of the most widely used components of hashing. In this paper, we propose three PCA-based hashing methods to improve the performance of the Principal Component Hashing (PCH). Different principal components have different among of variances of data. In the PCH, each principal component corresponds to a hash function. Hence, the PCH treats each principal component to have the same importance which will lead to the loss of much information in constructing hashing table. To deal with this shortage, we propose the weighted PCH (WPCH), the grid PCH (GPCH) and the weighted grid PCH (WGPCH).\",\"PeriodicalId\":335296,\"journal\":{\"name\":\"2014 International Conference on Machine Learning and Cybernetics\",\"volume\":\"39 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-07-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 International Conference on Machine Learning and Cybernetics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICMLC.2014.7009117\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 International Conference on Machine Learning and Cybernetics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMLC.2014.7009117","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Weighted grid Principal Component Analysis hashing
Principal Component Analysis (PCA) is one of the most widely used components of hashing. In this paper, we propose three PCA-based hashing methods to improve the performance of the Principal Component Hashing (PCH). Different principal components have different among of variances of data. In the PCH, each principal component corresponds to a hash function. Hence, the PCH treats each principal component to have the same importance which will lead to the loss of much information in constructing hashing table. To deal with this shortage, we propose the weighted PCH (WPCH), the grid PCH (GPCH) and the weighted grid PCH (WGPCH).