CAM Seminar—Rank Restricted Subspace Segmentation: Theory and Algorithms
Prof. Zhenyue Zhang
2018-05-11 ~ 2018-05-11
Room 1303, Sciences Building No. 1
Subspace learning or segmentation aims to estimate the subspaces based on given data points from a union of several subspace. However the subspaces behind the data samples were not well defined in the literature, especially for intersected subspaces. In this talk, we build a primary frame for learning the complicated subspaces behind samples, and show the solid developments on theoretical bases and algorithms, in including the concept of fine segmentation of samples, uniqueness conditions of the fine segmentation, structures of the subspace detection representation (SDR), a rank-restricted sparse optimization for modeling the detection of fine segmentation, tight sufficient conditions of unique solution, refinement for local optimal solutions. We my also talk about algorithms for solving the optimization problem that is neither convex nor continuous.