Compressive sensing (CS) is a new approach for the acquisition and recovery of sparse signals that enables sampling rates significantly below the classical Nyquist rate. Based on...
Luisa F. Polania, Rafael E. Carrillo, Manuel Blanc...
Image registration and 3D reconstruction are fundamental computer vision and medical imaging problems. They are particularly challenging when the input data are images of a deform...
A novel framework of compressed sensing, namely statistical compressed sensing (SCS), that aims at efficiently sampling a collection of signals that follow a statistical distribu...
Methods based on 1-relaxation, such as basis pursuit and the Lasso, are very popular for sparse regression in high dimensions. The conditions for success of these methods are now ...
We consider the problem of document indexing and representation. Recently, Locality Preserving Indexing (LPI) was proposed for learning a compact document subspace. Different from...
Deng Cai, Xiaofei He, Wei Vivian Zhang, Jiawei Han