Probabilistic Filters By Example Probablistic filters are high-speed, space-efficient data structures that support set-membership tests with a one-sided error. These filters can claim that a given entry is definitely not represented in a set of entries, or might be represented in the set. That is, negative responses are conclusive, whereas positive responses incur a small false positive probability (FPP). The trade-off for this one-sided error is space-efficiency. Cuckoo Filters and Bloom Filter...