Abstract: Conventional non-negative matrix factorization algorithms suffer from slow convergence in high-dimensional data dimensionality reduction. In this paper, a novel algorithm is proposed to ...
Matrix factorization techniques have become pivotal in data mining, enabling the extraction of latent structures from large-scale data matrices. These methods decompose complex datasets into ...
Abstract: For the low-rank matrix recovery problem, algorithms that directly manipulate the low-rank matrix typically require computing the top singular values/vectors of the matrix and thus are ...
Let $C$ be a simple closed Liapounov contour in the complex plane and $A$ an invertible $n \times n$ matrix-valued function on $C$ with bounded measurable entries ...
SIAM Journal on Applied Mathematics, Vol. 30, No. 4 (Jun., 1976), pp. 732-738 (7 pages) The explicit Wiener-Hopf factorization of the dispersion matrix Λ(z) is obtained for two scattering models which ...
HYLU is a general-purpose parallel solver designed for efficiently solving sparse linear systems ($\bf{Ax}=\bf b$) on multi-core shared-memory machines. It employs an innovative parallel up-looking LU ...
A new technical paper titled “Towards An Approach to Identify Divergences in Hardware Designs for HPC Workloads” was ...
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