Efficient Anchor Graph Hashing with Data-Dependent Anchor Selection
Hiroaki Takebe, Yusuke Uehara, Seiichi Uchida · IEICE Transactions on Information and Systems · 2015
Anchor graph hashing (AGH) is a promising hashing method for nearest neighbor (NN) search. AGH realizes efficient search by generating and utilizing a small number of points that are called anchors. In this paper, we propose a method for improving AGH, which considers data distribution in a similarity space and selects suitable anchors by performing principal component analysis (PCA) in the similarity space.