The matrix computation language and environment MATLAB is extended to include sparse matrix storage and operations. The only change to the outward appearance of the MATLAB language is a pair of commands to create full or sparse matrices. Nearly all the operations of MATLAB now apply equally to full or sparse matrices, without any explicit action by the user. The sparse data structure represents a matrix in space proportional to the number of nonzero entries, and most of the operations compute sparse results in time proportional to the number of arithmetic operations on nonzeros.
In this paper, the term tensor refers simply to a multidimensional or N-way array, and we consider how specially structured tensors allow for efficient storage and computation. ...
We consider the problem of reconstructing a sparse signal x^0\\in{\\bb R}^n from a limited number of linear measurements. Given m randomly selected samples of Ux0, where U is an...
Abstract Suppose we wish to recover a vector x 0 ∈ ℝ 𝓂 (e.g., a digital signal or image) from incomplete and contaminated observations y = A x 0 + e ; A is an 𝓃 × 𝓂 matrix wi...
Recent methods for learning vector space representations of words have succeeded in capturing fine-grained semantic and syntactic regularities using vector arithmetic, but the o...
The problem of computing a small vertex separator in a graph arises in the context of computing a good ordering for the parallel factorization of sparse, symmetric matrices. An ...
Social media, news, blog, policy document mentions