Targeted clustering using meta-buckets

One or more tangible, nontransitory computer-readable storage media having stored thereon executable instructions to classify a target sample, wherein the target sample is a computer object having a feature vector, the instructions to:

• create n sorted containers, comprising sorting a universe of samples based on feature vector distances from the samples to n vantage points, wherein n is a positive integer;
• bucketize the n sorted containers;
• for the n vantage points, select, from the n bucketized sorted containers, n meta- buckets of that the target sample belongs to;
• create an intersection container, comprising samples that appear in all n meta- buckets;
• select, as a target cluster, samples from the intersection container that have a feature vector distance from the target sample less than a threshold;
• and
• act on the target cluster.

A computing apparatus, comprising:

• one or more hardware platforms, comprising one or more processor circuits and one or more memories;
• and
• instructions encoded within the one or more memories to instruct the one or more processor circuits to:
• create n sorted containers, comprising sorting a universe of samples based on feature vector distances from the samples to n vantage points, wherein n is a positive integer;
• bucketize the n sorted containers;
• for the n vantage points, select, from the n bucketized sorted containers, n meta-buckets that a target sample belongs to;
• create an intersection container, comprising samples that appear in all n meta-buckets;
• select, as a target cluster, samples from the intersection container that have a feature vector distance from the target sample less than a threshold;
• and
• act on the target cluster.