杂役
发表于 2025-3-28 17:00:30
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我还要背着他
发表于 2025-3-28 19:48:47
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询问
发表于 2025-3-29 02:25:58
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implore
发表于 2025-3-29 04:32:26
Consultants and Consultancy in Education,t-FD sets of data blocks satisfy FD-Combine induction condition. With our strategy, each single-node FD discovery algorithm can be directly parallelized without modification in distributed environments. In the evaluation, with . threads, the speedups of FD discovery algorithm FastFDs exceed . in mos
PHIL
发表于 2025-3-29 10:17:34
Estuardo Alpirez Bock,Alexander Treffal sampling technique value perturbation in the framework of LDP. Then we combine the BiSample mechanism with users’ privacy preferences for missing data perturbation. Theoretical analysis and experiments on a set of datasets confirm the effectiveness of the proposed mechanisms.
Suppository
发表于 2025-3-29 15:07:44
BiSample: Bidirectional Sampling for Handling Missing Data with Local Differential Privacyal sampling technique value perturbation in the framework of LDP. Then we combine the BiSample mechanism with users’ privacy preferences for missing data perturbation. Theoretical analysis and experiments on a set of datasets confirm the effectiveness of the proposed mechanisms.
Inoperable
发表于 2025-3-29 15:54:09
0302-9743activities in database systems and their applications. It provides a forum for technical presentations and discussions among database researchers, developers and users from academia, business and industry..978-3-030-59409-1978-3-030-59410-7Series ISSN 0302-9743 Series E-ISSN 1611-3349
Infirm
发表于 2025-3-29 20:34:23
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半球
发表于 2025-3-30 00:57:15
Guido Marco Bertoni,Francesco Regazzoni window functions. WFApprox uses Machine Learning models instead of massive data for query answering. Our experimental evaluation shows that WFApprox significantly outperforms the mainstream database systems over TPC-H benchmark.
cringe
发表于 2025-3-30 04:44:03
https://doi.org/10.1007/978-3-030-68773-1gressive pruning techniques to eliminate the dissimilar results as well as enable early termination of the computation. We conduct extensive experiments on three real world datasets. The results show that our method achieves an order of magnitude performance gain than state-of-the-art approaches.