Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications
Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications
Non-negative Matrix Factorization with Sparseness Constraints
The Journal of Machine Learning Research
Nonnegative features of spectro-temporal sounds for classification
Pattern Recognition Letters
Accelerating the EMML algorithm and related iterative algorithms by rescaled block-iterative methods
IEEE Transactions on Image Processing
Learning Sparse Representations by Non-Negative Matrix Factorization and Sequential Cone Programming
The Journal of Machine Learning Research
Journal of VLSI Signal Processing Systems
Non-negative matrix factorization with α-divergence
Pattern Recognition Letters
Nonnegative matrix factorization with quadratic programming
Neurocomputing
Nonnegative matrix factorization with Gaussian process priors
Computational Intelligence and Neuroscience - Advances in Nonnegative Matrix and Tensor Factorization
Algorithms for sparse nonnegative tucker decompositions
Neural Computation
On α-divergence based nonnegative matrix factorization for clustering cancer gene expression data
Artificial Intelligence in Medicine
Novel Multi-layer Non-negative Tensor Factorization with Sparsity Constraints
ICANNGA '07 Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part II
Regularized Alternating Least Squares Algorithms for Non-negative Matrix/Tensor Factorization
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III
Sparse Super Symmetric Tensor Factorization
Neural Information Processing
Blind Image Separation Using Nonnegative Matrix Factorization with Gibbs Smoothing
Neural Information Processing
Nonnegative Tensor Factorization with Smoothness Constraints
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues
Computational Intelligence and Neuroscience - Advances in Nonnegative Matrix and Tensor Factorization
Minimum Determinant Constraint for Non-negative Matrix Factorization
ICA '09 Proceedings of the 8th International Conference on Independent Component Analysis and Signal Separation
Binary Nonnegative Matrix Factorization Applied to Semi-conductor Wafer Test Sets
ICA '09 Proceedings of the 8th International Conference on Independent Component Analysis and Signal Separation
IEEE Transactions on Signal Processing
Convergence Analysis of Non-Negative Matrix Factorization for BSS Algorithm
Neural Processing Letters
Multichannel nonnegative matrix factorization in convolutive mixtures for audio source separation
IEEE Transactions on Audio, Speech, and Language Processing
Aggregated information representation for technical analysis on stock market with csiszár divergence
KES-AMSTA'10 Proceedings of the 4th KES international conference on Agent and multi-agent systems: technologies and applications, Part II
IEEE Transactions on Neural Networks
Towards unique solutions of non-negative matrix factorization problems by a determinant criterion
Digital Signal Processing
Sparse non-negative tensor factorization using columnwise coordinate descent
Pattern Recognition
Algorithms for nonnegative matrix factorization with the β-divergence
Neural Computation
Nonnegative matrix factorization for motor imagery EEG classification
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part II
Extended SMART algorithms for non-negative matrix factorization
ICAISC'06 Proceedings of the 8th international conference on Artificial Intelligence and Soft Computing
Non-negative matrix factorization with quasi-newton optimization
ICAISC'06 Proceedings of the 8th international conference on Artificial Intelligence and Soft Computing
Bayesian non-negative matrix factorization with learned temporal smoothness priors
LVA/ICA'12 Proceedings of the 10th international conference on Latent Variable Analysis and Signal Separation
Multistability of α-divergence based NMF algorithms
Computers & Mathematics with Applications
Global Minima Analysis of Lee and Seung's NMF Algorithms
Neural Processing Letters
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In this paper we discus a wide class of loss (cost) functions for non-negative matrix factorization (NMF) and derive several novel algorithms with improved efficiency and robustness to noise and outliers. We review several approaches which allow us to obtain generalized forms of multiplicative NMF algorithms and unify some existing algorithms. We give also the flexible and relaxed form of the NMF algorithms to increase convergence speed and impose some desired constraints such as sparsity and smoothness of components. Moreover, the effects of various regularization terms and constraints are clearly shown. The scope of these results is vast since the proposed generalized divergence functions include quite large number of useful loss functions such as the squared Euclidean distance,Kulback-Leibler divergence, Itakura-Saito, Hellinger, Pearson’s chi-square, and Neyman’s chi-square distances, etc. We have applied successfully the developed algorithms to blind (or semi blind) source separation (BSS) where sources can be generally statistically dependent, however they satisfy some other conditions or additional constraints such as nonnegativity, sparsity and/or smoothness.