A probabilistic algorithm to quickly find points in a high dimensional space near a query point. Preprocessing: put every point in multiple hash tables. Each table has its own locality-sensitive hash function and uses buckets (or chaining) since many collisions are expected. The hash functions come from a family of functions. Finding: look up the query point in each hash table, and compute the distance from the query point of every point in the bucket.