Results 41 to 50 of about 135,346 (336)
IET Image Processing, 2022 Benefiting from the good physical interpretations and low computational complexity, non‐negative matrix factorization (NMF) has attracted wide attentions in data representation learning tasks.
Yanfeng Sun +4 more
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Majorization-Minimization Algorithm for Discriminative Non-Negative Matrix Factorization
IEEE Access, 2020 This paper proposes a basis training algorithm for discriminative non-negative matrix factorization (NMF) with applications to single-channel audio source separation.
Li Li, Hirokazu Kameoka, Shoji Makino
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Non-negative Matrix Factorization on Manifold [PDF]
2008 Eighth IEEE International Conference on Data Mining, 2008 Recently non-negative matrix factorization (NMF) has received a lot of attentions in information retrieval, computer vision and pattern recognition. NMF aims to find two non-negative matrices whose product can well approximate the original matrix. The sizes of these two matrices are usually smaller than the original matrix. This results in a compressed
Xiaofei He +3 more
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Ordinal Non-negative Matrix Factorization for Recommendation
, 2020 Accepted for publication at ICML ...
Gouvert, Olivier +2 more
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Bayesian Non-negative Matrix Factorization [PDF]
, 2009 We present a Bayesian treatment of non-negative matrix factorization (NMF), based on a normal likelihood and exponential priors, and derive an efficient Gibbs sampler to approximate the posterior density of the NMF factors. On a chemical brain imaging data set, we show that this improves interpretability by providing uncertainty estimates.
Ole Winther +2 more
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Optimal Recovery of Missing Values for Non-Negative Matrix Factorization
IEEE Open Journal of Signal Processing, 2021 Missing values imputation is often evaluated on some similarity measure between actual and imputed data. However, it may be more meaningful to evaluate downstream algorithm performance after imputation than the imputation itself.
Rebecca Chen Dean, Lav R. Varshney
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Face Recognition Based on Wavelet Kernel Non-Negative Matrix Factorization
Cybernetics and Information Technologies, 2014 In this paper a novel face recognition algorithm, based on wavelet kernel non-negative matrix factorization (WKNMF), is proposed. By utilizing features from multi-resolution analysis, the nonlinear mapping capability of kernel nonnegative matrix ...
Bai, Lin, Li Yanbo, Hui Meng
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MCA-NMF: Multimodal Concept Acquisition with Non-Negative Matrix Factorization. [PDF]
PLoS ONE, 2015 In this paper we introduce MCA-NMF, a computational model of the acquisition of multimodal concepts by an agent grounded in its environment. More precisely our model finds patterns in multimodal sensor input that characterize associations across ...
Olivier Mangin +3 more
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On Rank Selection in Non-Negative Matrix Factorization Using Concordance
Mathematics, 2023 The choice of the factorization rank of a matrix is critical, e.g., in dimensionality reduction, filtering, clustering, deconvolution, etc., because selecting a rank that is too high amounts to adjusting the noise, while selecting a rank that is too low ...
Paul Fogel +3 more
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Robust Adaptive Graph Regularized Non-Negative Matrix Factorization
IEEE Access, 2019 Data clustering, which aims to divide the given samples into several different groups, has drawn much attention in recent years. As a powerful tool, non-negative matrix factorization (NMF) has been applied successfully in clustering tasks. However, there
Xiang He, Qi Wang, Xuelong Li
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