Hashing Learning with Hyper-Class Representation. (arXiv:2206.02334v1 [cs.LG])

Existing unsupervised hash learning is a kind of attribute-centered
calculation. It may not accurately preserve the similarity between data. This
leads to low down the performance of hash function learning. In this paper, a
hash algorithm is proposed with a hyper-class representation. It is a two-steps
approach. The first step finds potential decision features and establish
hyper-class. The second step constructs hash learning based on the hyper-class
information in the first step, so that the hash codes of the data …

arxiv hashing learning representation