The Bloom filter provides fast approximate set membership while using little memory.
Engineers often use these filters to avoid slow operations such as disk or network accesses …

Filters, such as Bloom, quotient, and cuckoo, save space by maintaining an approximate
representation of a set and occasionally returning false positives. Filters play a critical role in …

Modern key-value stores typically rely on an LSM-tree in storage (SSD) to handle writes and
Bloom filters in memory (DRAM) to optimize reads. With ongoing advances in SSD …

An efficient implementation of a hash join has been a highly researched problem for
decades. Recently, the radix join has been shown to have superior performance over the …

Filter data structures have been used ubiquitously since the 1970s to answer approximate
set-membership queries in various areas of computer science including architecture …

In this paper we present the derivation of two new forms of the Kalman filter equations; the
first is for a pure lognormally distributed random variable, while the second set of Kalman …

Filter data structures over-approximate a set of hashable keys, ie set membership queries
may incorrectly come out positive. A filter with false positive rate $ f\in (0, 1] $ is known to …

Bloom and cuckoo filters provide fast approximate set membership while using little memory.
Engineers use them to avoid expensive disk and network accesses. The recently introduced …

Hash joins play a critical role in relational data processing and their performance is crucial
for the overall performance of a database system. Due to the hard to predict nature of …

Bloom filters are used to perform approximate membership checking in a wide range of
applications in both computing and networking, but the recently introduced cuckoo filter is …