DEEPlearningNesterov’sACCELERATEDgradientalgorithmNonnegative Matrix Factorization(NMF)is a powerful technique to perform dimension reduction and pattern recognition through single-layer data representation learning.However,deep learning networks,with their carefully designed hierarchical structure,can combine hidden...
nmfLS2: Non-negative Matrix Factorization with sparse matrix(Ji and Eisenstein, 2013)website Semi-NMF: Semi Non-negative Matrix Factorization Deep-Semi-NMF: Deep Semi Non-negative Matrix Factorization(Trigeorgis et al. 2014)website iNMF: Incremental Subspace Learning via NMF(Bucak and Gunsel, 20...
julia high-performance-computing differential-equations factorization nonlinear-equations sparse-matrix sparse-matrices newton-raphson steady-state bracketing equilibrium newton-method scientific-machine-learning sciml newton-krylov deep-equilibrium-models Updated Apr 7, 2025 Julia rico...
Graphical representation for Poisson–Gamma Bayesian nonnegative matrix factorization. (5.118)Ψ={αmkb,βmkb,αknw,βknw}. As addressed in Section 3.7.3, variational Bayesian (VB) inference procedure can be introduced to estimate the hyperparameters Ψ by maximizing the marginal likelihood p(X|Ψ...
Li. Hyperspectral image super- resolution via non-local sparse tensor factorization. The IEEE Conference on Computer Vision and Pattern Recog- nition (CVPR), pages 5344–5353, 2017. [9] C. Dong, C. C. Loy, K. He, and X. Tang. Image super-resolution using deep convolutional networks. ...
wheres(·) is a non-linear activation function, e.g. tanh or rectified linear unit. MatrixWconsists of weights andbis a bias vector. Several encoding steps can be performed sequentially, resulting into a deep encoder. The latent representationycan be decoded / mapped back via ...
[6] employs nonnegative matrix factorization (NMF) to delineate shared and dataset-specific features of cells across biosamples. Harmony [9] integrates scRNA-seq data by projecting cells into a shared embedding. Scanorama [13] leverages the matches of cells with similar transcriptional profiles ...
Feature selection and multi-kernel learning for adaptive graph regularized nonnegative matrix factorization 2015, Expert Systems with Applications Show abstract Feature selection and multi-kernel learning for sparse representation on a manifold 2014, Neural Networks Show abstract A systematic review on seawee...
Cai D, He X, Han J, Huang TS (2010) Graph regularized nonnegative matrix factorization for data representation. IEEE Trans Pattern Anal Mach Intell 33:1548–1560 Google Scholar Lu X, Wang Y, Yuan Y (2013) Graph-regularized low-rank representation for destriping of hyperspectral images. IEE...
Robust latent nonnegative matrix factorization with automatic sparse reconstruction for unsupervised feature extraction 2023, Information Sciences Show abstract Noise-related face image recognition based on double dictionary transform learning 2023, Information Sciences Show abstract Robust dual-graph discriminative...