Learning to hash with semantic similarity metrics and empirical KL divergence

Heikki Arponen, Tom E. Bishop

Learning to hash is an efficient paradigm for exact and approximate nearest neighbor search from massive databases. Binary hash codes are typically extracted from an image by round…