no code implementations • 22 Mar 2019 • Chen Qin, Bibo Shi, Rui Liao, Tommaso Mansi, Daniel Rueckert, Ali Kamen
The proposed registration approach is then built on the factorized latent shape code, with the assumption that the intrinsic shape deformation existing in original image domain is preserved in this latent space.
no code implementations • 12 May 2018 • Zhewei Wang, Bibo Shi, Charles D. Smith, Jundong Liu
In this paper, we propose a nonlinear distance metric learning scheme based on the fusion of component linear metrics.
no code implementations • ICLR 2018 • Pin Zhang, Bibo Shi, JundongLiu
In this paper, we propose a nonlinear unsupervised metric learning framework to boost of the performance of clustering algorithms.
no code implementations • 6 Aug 2015 • Bibo Shi, Jundong Liu
In recent years, research efforts to extend linear metric learning models to handle nonlinear structures have attracted great interests.