Nonnegative matrix Factorization (NMF)
Recognition of Nonprototypical Emotions in Reverberated and Noisy Speech by Nonnegative Matrix Factorization
... supervised Nonnegative Matrix Factorization (NMF) has been proposed in automatic speech recognition for enhanced robustness, we introduce and evaluate different kinds of NMF-based features for emotion ...
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Improving knowledge on the activation of bone marrow fibroblasts in MGUS and MM disease through the automatic extraction of genes via a nonnegative matrix factorization approach on gene expression profiles
... NMF: nonnegative matrix factorization; PCA: principal component analysis; MGUS: monoclonal gammopathy of undetermined sig- nificance; PC: plasma cells; HSC: hematopoietic stem cell; BMSCs: stem cells ...
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Robust Near-Separable Nonnegative Matrix Factorization Using Linear Optimization
... Nonnegative matrix factorization (NMF) has been shown recently to be tractable under the separability assumption, under which all the columns of the input data matrix be- long to the convex ...
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A Projected Alternating Least square Approach for Computation of Nonnegative Matrix Factorization
... Nonnegative matrix factorization (NMF) is a common method in data mining that have been used in different applications as a dimension reduction, classification or clustering ...
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Sparse and Unique Nonnegative Matrix Factorization Through Data Preprocessing
... Nonnegative matrix factorization (NMF) has become a very popular technique in machine learning because it automatically extracts meaningful features through a sparse and part-based representa- ...the ...
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Ellipsoidal Rounding for Nonnegative Matrix Factorization Under Noisy Separability
... We present a numerical algorithm for nonnegative matrix factorization (NMF) problems under noisy separability. An NMF problem under separability can be stated as one of finding all vertices of the ...
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A Robust Symmetric Nonnegative Matrix Factorization Framework for Clustering Multiple Heterogeneous Microbiome Data
... data. Nonnegative matrix factorization (NMF), an approach that can be used for signal compression and noise reduction, has aroused widespread attention in the last two ...symmetric nonnegative ...
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A study of blind source separation using nonnegative matrix factorization
... APPLIED INACOUSTIC SOURCE SEPARATION For the acoustic source separation, the conventional multichannel blind source separation algorithm was performing well in multichannel real-world recording data. However, the ...
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Robust Multi Relational Clustering via ℓ1 Norm Symmetric Nonnegative Matrix Factorization
... Traditional clustering aims to partition data points into several groups, such that the data points in the same group can share some commonalities whilst those from different groups are dissimilar. With the recent ...
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Exploiting Nonnegative Matrix Factorization with Mixed Group Sparsity Constraint to Separate Speech Signal from Single-channel Mixture with Unknown Ambient Noise
... combining nonnegative matrix factorization (NMF) with mixed group sparsity constraint that allows exploiting generic noise spectral model to guide the separation ...
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On rationality of nonnegative matrix factorization
... Nonnegative matrix factorization (NMF) is the task of factoring a matrix of nonnegative real numbers M (henceforth a nonnegative matrix) as a product M = W · H such that ...
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Nonnegative Matrix Factorization with Zellner Penalty
... Zellner nonnegative matrix factorization ...Constrained nonnegative matrix factorization (CNMF) [8] and show that it is superior across all selected factorization ...
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Two-hierarchical nonnegative matrix factorization distinguishing the fluorescent targets from autofluorescence for fluorescence imaging
... imaging, nonnegative matrix factorization (NMF) [10, 11] has been used to find the matrices S and C by minimiz- ing the cost function F representable as a difference between D and CS in fluorescence ...
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Fast Nonnegative Matrix Factorization and Its Application for Protein Fold Recognition
... via matrix factorization with nonnegativity constraints is ...explore nonnegative matrix fac- torization in combination with three nearest-neighbor classifiers for protein fold ...typically ...
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Area Correlated Spectral Unmixing Based on Bayesian Nonnegative Matrix Factorization
... To solve the problem of the spatial correlation for adjacent areas in traditional spectral unmixing methods, we propose an area-correlated spectral unmixing method based on Bayesian nonnegative matrix ...
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Determining Patterns in Neural Activity for Reaching Movements Using Nonnegative Matrix Factorization
... In this paper, we propose a model-independent method- ology to study spatiotemporal patterns between neuronal spikes and behavior utilizing nonnegative matrix factoriza- tion (NMF) [9, 10]. In its original ...
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Hierarchical community detection via rank-2 symmetric nonnegative matrix factorization
... of nonnegative data available for extracting critical informa- tion, the NMF has found a wealth of applications in such domains as image, text, and chemical data ...a nonnegative term-document ...the ...
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Nonnegative matrix factorization requires irrationality
... the nonnegative ranks over R and Q are different functions, the computability question ...the nonnegative rank over R is computable, via a reduction to the existential theory of the reals, which in turn can ...
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Bayesian group sparse learning for music source separation
... [1]. Nonnegative matrix factorization (NMF) is designed to find an approximate factorization X ≈ AS for a data matrix X into a basis matrix A and a weight matrix S which ...
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