N. Kutz, "Randomized nonnegative matrix factorization," Pattern Recognition Letters, vol. 104, pp. 1 - 7, 2018.Erichson NB, Mendible A, Wihlborn S, Kutz JN (2018). "Randomized Nonnegative Matrix Factorization."
In order to address the challenges, we propose randomized singular value decomposition (RSVD) for integrative clustering using Non-negative Matrix Factorization: intNMF-rsvd. The method utilizes RSVD to reduce the dimensionality by projecting the data into eigen vector space with user specified lower ...
(2) always exists, is unique, is a nonnegative function G : D \times D \rightarrow \mathbb {R}^+ \cup \{\infty \} such that \begin{aligned} u(x) =\int _D G(x,y)f(y)d y, \qquad f \in \mathcal {C}_c^\infty (D), \end{aligned} and for each y\in \Omega and ...
Orthogonal nonnegative matrix factorization (ONMF) is widely used in blind image separation problem, document classification, and human face recognition. The model of ONMF can be efficiently solved by the alternating direction method of multipliers and hierarchical alternating least squares method. When...
Fast Parallel Randomized Algorithm for Nonnegative Matrix Factorization with KL Divergence for Large Sparse DatasetsMathematics - Optimization and Controldoi:10.18178/IJMLC.2016.6.2.583Duy Khuong NguyenTu Bao HoarXiv
Linear programming (LP) is used in many machine learning applications, such as `1-regularized SVMs, basis pursuit, nonnegative matrix factorization, etc. Interior Point Methods (IPMs) are one of the most popular methods to solve LPs both in theory and in practice. Their underlying complexity ...
In particular, we prove that the base- $$2$$ logarithm of the nonnegative rank of any nonnegative matrix equals the minimum complexity of a randomized communication protocol computing the matrix in expectation. Using Yannakakis' factorization theorem, this implies that the base- $$2$$ ...
For the localization problem of receiver failure in reverberant environments, a matrix completion algorithm that relies on the low-rank characteristic is developed for the Hankel matrices of received signals [18]. The non-negative matrix factorization (NMF) algorithm is utilized to calculate the low-...