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Nonnegative matrix factorization (NMF) is a powerful matrix decomposition technique that approximates a nonnegative matrix by the product of two low-rank nonnegative matrix factors. It has been widely applied to signal processing, computer vision, and data mining. Traditional NMF solvers include the multiplicative update rule (MUR), the projected gradient(More)
Nonnegative matrix factorization (NMF) has become a popular data-representation method and has been widely used in image processing and pattern-recognition problems. This is because the learned bases can be interpreted as a natural parts-based representation of data and this interpretation is consistent with the psychological intuition of combining parts to(More)
Nonnegative matrix factorization (NMF) has become a popular dimension-reduction method and has been widely applied to image processing and pattern recognition problems. However, conventional NMF learning methods require the entire dataset to reside in the memory and thus cannot be applied to large-scale or streaming datasets. In this paper, we propose an(More)
Non-negative matrix factorization (NMF) approximates a non-negative matrix X by a product of two non-negative low-rank factor matrices W and H . NMF and its extensions minimize either the Kullback-Leibler divergence or the Euclidean distance between X and WH to model the Poisson noise or the Gaussian noise. In practice, when the noise distribution is heavy(More)
In this paper, we present a non-negative patch alignment framework (NPAF) to unify popular non-negative matrix factorization (NMF) related dimension reduction algorithms. It offers a new viewpoint to better understand the common property of different NMF algorithms. Although multiplicative update rule (MUR) can solve NPAF and is easy to implement, it(More)
UNLABELLED Inhibitor of growth 1 (ING1) is a type II tumor suppressor that affects cell function by altering chromatin structure and regulating transcription. Recently, three ING1 splice variants have been cloned, but their roles in apoptosis and p53 regulation in human hepatocellular carcinoma (HCC) have not been fully elucidated. The present study found(More)
Chemotherapeutics in the taxane and vinca-alkaloid classes sometimes produce a painful peripheral neuropathy for which there is no validated treatment. Experiments with rat models of paclitaxel- and vincristine-evoked pain suggest that these conditions may not respond to all of the analgesics that have efficacy in other models of painful peripheral(More)
Gene expression data are the representation of nonlinear interactions among genes and environmental factors. Computing analysis of these data is expected to gain knowledge of gene functions and disease mechanisms. Clustering is a classical exploratory technique of discovering similar expression patterns and function modules. However, gene expression data(More)
This study was conducted to demonstrate myocardial protective effects and possible underlying mechanisms of vitexin on myocardial ischemia/reperfusion (I/R) injury in rats. Occluding the anterior descending artery for 30 min and restoring blood perfusion for 60 min in rat established a model of myocardial I/R. The elevation of the ST segment of(More)
Non-negative matrix factorization (NMF) approximates a non-negative matrix by the product of two low-rank matrices and achieves good performance in clustering. Recently, semi-supervised NMF (SS-NMF) further improves the performance by incorporating part of the labels of few samples into NMF. In this paper, we proposed a novel graph based SS-NMF (GSS-NMF).(More)