There has been considerable success in automated reconstruction for image sequences where small baseline algorithms can be used to establish matches across a number of images. In c...
Compressed sensing (CS) is a new technique for simultaneous data sampling and compression. In this paper, we propose and study block compressed sensing for natural images, where i...
The problem of learning a sparse conic combination of kernel functions or kernel matrices for classification or regression can be achieved via the regularization by a block 1-norm...
Francis R. Bach, Romain Thibaux, Michael I. Jordan
In this paper we study the problem of finding maximally sized subsets of binary strings (codes) of equal length that are immune to a given number r of repetitions, in the sense th...
The goal of this paper is to offer a framework for image classification "by type". For example, one may want to classify an image of a certain office as man-made ? as op...