Signal modeling lies at the core of numerous signal and image processing applications. A recent approach that has drawn considerable attention is sparse representation modeling, in...
We present a new approach to multiple instance learning (MIL) that is particularly effective when the positive bags are sparse (i.e. contain few positive instances). Unlike other ...
Face recognition (FR) is an active yet challenging topic in computer vision applications. As a powerful tool to represent high dimensional data, recently sparse representation bas...
Reduced rank regression (RRR) has found application in various fields of signal processing. In this paper we propose a novel extension of the RRR model which we call sparse varia...
Sparse sampling with coprime lattice arrays was introduced recently in the literature. It has been shown that a dense coarray can be constructed from such a pair of arrays, and is...