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Found 2 papers, 1 papers with code
A Critical Analysis of Classifier Selection in Learned Bloom Filters
Learned Bloom Filters, i. e., models induced from data via machine learning techniques and solving the approximate set membership problem, have recently been introduced with the aim of enhancing the performance of standard Bloom Filters, with special focus on space occupancy.
On the Choice of General Purpose Classifiers in Learned Bloom Filters: An Initial Analysis Within Basic Filters
Bloom Filters are a fundamental and pervasive data structure.
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