We present a new approach to preconditioning for very large, sparse, non-symmetric, linear systems. We explicitly compute an approximate inverse to our original matrix that can be...
This paper presents a new compiler optimization algorithm that parallelizes applications for symmetric, sharedmemory multiprocessors. The algorithm considers data locality, parall...
Recent work has demonstrated that using a carefully designed sensing matrix rather than a random one, can improve the performance of compressed sensing. In particular, a welldesign...
Kevin Rosenblum, Lihi Zelnik-Manor, Yonina C. Elda...
In this paper, we present a model for unsupervised pattern discovery using non-negative matrix factorization (NMF) with graph regularization. Though the regularization can be appl...
There has been a significant interest in the recovery of low-rank matrices from an incomplete of measurements, due to both theoretical and practical developments demonstrating th...
S. Derin Babacan, Martin Luessi, Rafael Molina, Ag...