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Efficient Algorithms for Kernel Aggregation Queries
Chan, Tsz Nam1; Hou, U. Leong2; Cheng, Reynold1; Yiu, Man Lung3; Mittal, Shivansh1
Source PublicationIEEE Transactions on Knowledge and Data Engineering

Kernel functions support a broad range of applications that require tasks like density estimation, classification, regression or outlier detection. For these tasks, a common online operation is to compute the weighted aggregation of kernel function values with respect to a set of points. However, scalable aggregation methods are still unknown for typical kernel functions (e.g., Gaussian kernel, polynomial kernel, sigmoid kernel and additive kernels) and weighting schemes. In this paper, we propose a novel and effective bounding technique, by leveraging index structures, to speed up the computation of kernel aggregation. In addition, we extend our technique to additive kernel functions, including $\chi ^2$χ2, intersection, JS and Hellinger kernels, which are widely used in different communities, e.g., computer vision, medical science, Geoscience etc. To handle the additive kernel functions, we further develop the novel and effective bound functions to efficiently evaluate the kernel aggregation. Experimental studies on many real datasets reveal that our proposed solution KARL achieves at least one order of magnitude speedup over the state-of-the-art for different types of kernel functions.

KeywordKarl Kernel Functions Lower And Upper Bounds
URLView the original
Indexed BySCIE
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Information Systems ; Engineering, Electrical & Electronic
WOS IDWOS:000789003800014
Scopus ID2-s2.0-85129504212
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Document TypeJournal article
CollectionFaculty of Science and Technology
Corresponding AuthorChan, Tsz Nam
Affiliation1.Department of Computer Science, University of Hong Kong, 999077, Hong Kong
2.State Key Laboratory of Internet of Things for Smart City, Department of Computer and Information Science, University of Macau, Taipa, Macau, 999078, Macao
3.Department of Computing, Hong Kong Polytechnic Univertiy, 999077, Hong Kong
Recommended Citation
GB/T 7714
Chan, Tsz Nam,Hou, U. Leong,Cheng, Reynold,et al. Efficient Algorithms for Kernel Aggregation Queries[J]. IEEE Transactions on Knowledge and Data Engineering,2022,34(6):2726-2739.
APA Chan, Tsz Nam,Hou, U. Leong,Cheng, Reynold,Yiu, Man Lung,&Mittal, Shivansh.(2022).Efficient Algorithms for Kernel Aggregation Queries.IEEE Transactions on Knowledge and Data Engineering,34(6),2726-2739.
MLA Chan, Tsz Nam,et al."Efficient Algorithms for Kernel Aggregation Queries".IEEE Transactions on Knowledge and Data Engineering 34.6(2022):2726-2739.
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