The cuckoo filter data structure of Fan, Andersen, Kaminsky, and Mitzenmacher (CoNEXT 2014) performs the same approximate set operations as a Bloom filter in less memory, with better locality of reference, and adds the ability to delete elements as well as to insert them. However, until now it has lacked theoretical guarantees on its performance. We describe a simplified version of the cuckoo filter using fewer hash function calls per query. With this simplification, we provide the first theoretical performance guarantees on cuckoo filters, showing that they succeed with high probability whenever their fingerprint length is large enough
Cuckoo hashing holds great potential as a high-performance hashing scheme for real appli-cations. Up...
International audienceCuckoo hashing is a common hashing technique, guaranteeing constant-time looku...
Many applications of approximate membership query data structures, or filters, require only an incre...
We introduce the adaptive cuckoo filter (ACF), a data structure for approximate set membership that ...
In recent years, approximate matching algorithms have become an important component in digital foren...
In many networking systems, Bloom filters are used for high-speed set membership tests. They permit ...
Presented on November 26, 2018 at 12:15 p.m. in the Marcus Nanotechnology Building, Room 1116.Michae...
Cuckoo hashing is a powerful primitive that enables storing items using small space with efficient q...
Bloom filters and cuckoo filters are used in many applications to reduce the amount of memory needed...
Bloom filters are used to perform approximate membership checking in a wide range of applications in...
In this paper, we study the feasibility of applying the recently proposed cuckoo filters to improve ...
Cuckoo filters (CFs) are an alternative to Bloom filters (BFs) that supports deletions and can often...
Part 7: EmeringInternational audienceThe emergence of large-scale dynamic sets in real applications ...
Abstract Cyberthreats continue their expansion, becoming more and more complex and varied. However, ...
Bloom Filter BF is a simple but powerful data structure that can check membership to a static set ...
Cuckoo hashing holds great potential as a high-performance hashing scheme for real appli-cations. Up...
International audienceCuckoo hashing is a common hashing technique, guaranteeing constant-time looku...
Many applications of approximate membership query data structures, or filters, require only an incre...
We introduce the adaptive cuckoo filter (ACF), a data structure for approximate set membership that ...
In recent years, approximate matching algorithms have become an important component in digital foren...
In many networking systems, Bloom filters are used for high-speed set membership tests. They permit ...
Presented on November 26, 2018 at 12:15 p.m. in the Marcus Nanotechnology Building, Room 1116.Michae...
Cuckoo hashing is a powerful primitive that enables storing items using small space with efficient q...
Bloom filters and cuckoo filters are used in many applications to reduce the amount of memory needed...
Bloom filters are used to perform approximate membership checking in a wide range of applications in...
In this paper, we study the feasibility of applying the recently proposed cuckoo filters to improve ...
Cuckoo filters (CFs) are an alternative to Bloom filters (BFs) that supports deletions and can often...
Part 7: EmeringInternational audienceThe emergence of large-scale dynamic sets in real applications ...
Abstract Cyberthreats continue their expansion, becoming more and more complex and varied. However, ...
Bloom Filter BF is a simple but powerful data structure that can check membership to a static set ...
Cuckoo hashing holds great potential as a high-performance hashing scheme for real appli-cations. Up...
International audienceCuckoo hashing is a common hashing technique, guaranteeing constant-time looku...
Many applications of approximate membership query data structures, or filters, require only an incre...