We develop scalable algorithms for regular and non-negative matrix completion. In particular, we base the methods on trace-norm regularization that induces a low rank predicted ma...
In this paper, a new convex matching pursuit scheme is proposed for tackling large-scale sparse coding and subset selection problems. In contrast with current matching pursuit alg...
Mingkui Tan, Ivor W. Tsang, Li Wang, Xinming Zhang
We present a new parallel algorithm to compute an exact triangularization of large square or rectangular and dense or sparse matrices in any field. Using fast matrix multiplicatio...
Due to the nature of an acoustic enclosure, the early part (i.e., direct path and early reflections) of the acoustic echo path is often sparse while the late reverberant part of ...
Pradeep Loganathan, Emanuel A. P. Habets, Patrick ...
We initiate the study of sparse recovery problems under the Earth-Mover Distance (EMD). Specifically, we design a distribution over m × n matrices A such that for any x, given A...