Near-optimal hashing algorithms for approximate nearest neighbor in high dimensions

Abstract
In this article, we give an overview of efficient algorithms for the approximate and exact nearest neighbor problem. The goal is to preprocess a dataset of objects (e.g., images) so that later, given a new query object, one can quickly return the dataset object that is most similar to the query. The problem is of significant interest in a wide variety of areas.
Funding Information
  • National Science Foundation (CCR-0133849)

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