Unique sampling of datasets

One or more non-transitory computer-readable media storing instructions that, when executed by one or more processors, cause the one or more processors to perform the steps of:

• determining a plurality of embeddings for a plurality of data points included in a dataset;
• populating a tree structure with the plurality of embeddings by:
• generating a first node that stores a first set of embeddings included in the plurality of embeddings;
• and
• generating a first plurality of nodes as children of the first node, wherein each node included in the first plurality of nodes stores a different subset of embeddings included in the first set of embeddings;
• sampling a subset of embeddings from the plurality of embeddings via a traversal of the tree structure;
• and
• generating a sampled dataset that includes a subset of data points corresponding to the subset of embeddings.

A system, comprising:

• one or more memories that store instructions, and
• one or more processors that are coupled to the one or more memories and, when executing the instructions, are configured to perform the steps of:
• determining a plurality of embeddings for a plurality of data points included in a dataset;
• populating a tree structure with the plurality of embeddings by:
• generating a first node that stores a first set of embeddings included in the plurality of embeddings;
• and
• generating a first plurality of nodes as children of the first node, wherein each node included in the first plurality of nodes stores a different subset of embeddings included in the first set of embeddings;
• sampling a subset of embeddings from the plurality of embeddings via a traversal of the tree structure;
• and
• causing a training dataset that includes a subset of data points corresponding to the subset of embeddings and a set of labels for the subset of data points to be generated.