Scalable Graph Hashing with Feature Transformation Motivation Motivation However,it is difficult to design effective algorithms because both the memory and time complexity are at least O(n2). SH (Weiss et al.,2008):Use an eigenfunction solution of 1-D Laplacian with uniform assumption BRE(Kulis and Darrell,2009):Subsample a small subset for training AGH (Liu et al.,2011).DGH (Liu et al.,2014):Use anchor graph to approximate the similarity graph 日卡三4元，互Q0 Li (http://cs.nju.edu.cn/lwj) Learning to Hash LAMDA,CS.NJU 20/43Scalable Graph Hashing with Feature Transformation Motivation Motivation However, it is difficult to design effective algorithms because both the memory and time complexity are at least O(n 2 ). SH (Weiss et al., 2008): Use an eigenfunction solution of 1-D Laplacian with uniform assumption BRE (Kulis and Darrell, 2009): Subsample a small subset for training AGH (Liu et al., 2011), DGH (Liu et al., 2014): Use anchor graph to approximate the similarity graph Li (http://cs.nju.edu.cn/lwj) Learning to Hash LAMDA, CS, NJU 20 / 43