An approximate membership data structure is a randomized data
structure for representing a set which supports membership
queries. It allows for a small false positive error rate but has
no false negative errors. Such data structures were first
introduced by Bloom in the 1970's, and have since had numerous
applications, ... more >>>

Consider graphs of n nodes and use a Bloom filter of length 2 log3 n bits. An edge between nodes i and j, with i < j, turns on a certain bit of the Bloom filter according to a hash function on i and j. Pick a set of log ... more >>>