Condusion Conclusion o Hashing can significantly improve retrieval speed and reduce storage cost. o It has become a hot research topic in big learning with wide applications. o We have proposed a series of hashing methods,including unsupervised,supervised,and multimodal methods.Furthermore, some quantization strategies(Kong and Li,2012a;Kong et al.,2012) are also designed. In particular,the details of SGH with feature transformation(Jiang and Li,2015)are introduced in this talk. +日卡+得￥。三元互双0 Li (http://cs.nju.edu.cn/lwj) Learning to Hash LAMDA,CS.NJU 40/43Conclusion Conclusion Hashing can significantly improve retrieval speed and reduce storage cost. It has become a hot research topic in big learning with wide applications. We have proposed a series of hashing methods, including unsupervised, supervised, and multimodal methods. Furthermore, some quantization strategies (Kong and Li, 2012a; Kong et al., 2012) are also designed. In particular, the details of SGH with feature transformation (Jiang and Li, 2015) are introduced in this talk. Li (http://cs.nju.edu.cn/lwj) Learning to Hash LAMDA, CS, NJU 40 / 43