Neural Networks for Optimization and Signal Processing
Neural Networks for Optimization and Signal Processing
A New Matrix-Free Algorithm for the Large-Scale Trust-Region Subproblem
SIAM Journal on Optimization
Introducing a weighted non-negative matrix factorization for image classification
Pattern Recognition Letters
Convex Optimization
Non-negative matrix factorization based methods for object recognition
Pattern Recognition Letters
CSB '04 Proceedings of the 2004 IEEE Computational Systems Bioinformatics Conference
Non-negative Matrix Factorization with Sparseness Constraints
The Journal of Machine Learning Research
Nonsmooth Nonnegative Matrix Factorization (nsNMF)
IEEE Transactions on Pattern Analysis and Machine Intelligence
Document clustering using nonnegative matrix factorization
Information Processing and Management: an International Journal
Learning Image Components for Object Recognition
The Journal of Machine Learning Research
Fast nonnegative matrix factorization and its application for protein fold recognition
EURASIP Journal on Applied Signal Processing
Csiszár’s divergences for non-negative matrix factorization: family of new algorithms
ICA'06 Proceedings of the 6th international conference on Independent Component Analysis and Blind Signal Separation
Nonnegative matrix factor 2-d deconvolution for blind single channel source separation
ICA'06 Proceedings of the 6th international conference on Independent Component Analysis and Blind Signal Separation
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
Accelerating the EMML algorithm and related iterative algorithms by rescaled block-iterative methods
IEEE Transactions on Image Processing
Sparse Super Symmetric Tensor Factorization
Neural Information Processing
Data Clustering with Semi-binary Nonnegative Matrix Factorization
ICAISC '08 Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing
Quadratic nonnegative matrix factorization
Pattern Recognition
Spectral signal unmixing with interior-point nonnegative matrix factorization
ICANN'12 Proceedings of the 22nd international conference on Artificial Neural Networks and Machine Learning - Volume Part I
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Nonnegative matrix factorization (NMF) solves the following problem: find such nonnegative matrices A@?R"+^I^x^J and X@?R"+^J^x^K that Y@?AX, given only Y@?R^I^x^K and the assigned index J (K@?I=J). Basically, the factorization is achieved by alternating minimization of a given cost function subject to nonnegativity constraints. In the paper, we propose to use quadratic programming (QP) to solve the minimization problems. The Tikhonov regularized squared Euclidean cost function is extended with a logarithmic barrier function (which satisfies nonnegativity constraints), and then using second-order Taylor expansion, a QP problem is formulated. This problem is solved with some trust-region subproblem algorithm. The numerical tests are performed on the blind source separation problems.