α-divergence is unique, belonging to both f-divergence and Bregman divergence classes
IEEE Transactions on Information Theory
Linear and nonlinear projective nonnegative matrix factorization
IEEE Transactions on Neural Networks
A nonnegative blind source separation model for binary test data
IEEE Transactions on Circuits and Systems Part I: Regular Papers
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
Factorizing three-way binary data with triadic formal concepts
KES'10 Proceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part I
Divergence based online learning in vector quantization
ICAISC'10 Proceedings of the 10th international conference on Artificial intelligence and soft computing: Part I
Sequential coordinate-wise DNMF for face recognition
ICAISC'10 Proceedings of the 10th international conference on Artificial intelligence and soft computing: Part I
Probabilistic latent tensor factorization
LVA/ICA'10 Proceedings of the 9th international conference on Latent variable analysis and signal separation
LVA/ICA'10 Proceedings of the 9th international conference on Latent variable analysis and signal separation
Automatic rank determination in projective nonnegative matrix factorization
LVA/ICA'10 Proceedings of the 9th international conference on Latent variable analysis and signal separation
LVA/ICA'10 Proceedings of the 9th international conference on Latent variable analysis and signal separation
LVA/ICA'10 Proceedings of the 9th international conference on Latent variable analysis and signal separation
Novel alternating least squares algorithm for nonnegative matrix and tensor factorizations
ICONIP'10 Proceedings of the 17th international conference on Neural information processing: theory and algorithms - Volume Part I
A survey of multilinear subspace learning for tensor data
Pattern Recognition
Divergence-based vector quantization
Neural Computation
Computing the polyadic decomposition of nonnegative third order tensors
Signal Processing
PARAFAC algorithms for large-scale problems
Neurocomputing
The noise identification method based on divergence analysis in ensemble methods context
ICANNGA'11 Proceedings of the 10th international conference on Adaptive and natural computing algorithms - Volume Part II
About nonnegative matrix factorization: on the posrank approximation
ICANNGA'11 Proceedings of the 10th international conference on Adaptive and natural computing algorithms - Volume Part II
IWANN'11 Proceedings of the 11th international conference on Artificial neural networks conference on Advances in computational intelligence - Volume Part II
Compressed sensing of astronomical images: orthogonal wavelets domains
Proceedings of the 12th International Conference on Computer Systems and Technologies
Kullback-Leibler divergence for nonnegative matrix factorization
ICANN'11 Proceedings of the 21th international conference on Artificial neural networks - Volume Part I
Uni-orthogonal nonnegative tucker decomposition for supervised image classification
ICIAP'11 Proceedings of the 16th international conference on Image analysis and processing: Part I
Extracting insights from social media with large-scale matrix approximations
IBM Journal of Research and Development
NOLISP'11 Proceedings of the 5th international conference on Advances in nonlinear speech processing
Theoretical Analysis of Bayesian Matrix Factorization
The Journal of Machine Learning Research
A multilevel approach for nonnegative matrix factorization
Journal of Computational and Applied Mathematics
Quadratic nonnegative matrix factorization
Pattern Recognition
Three-way analysis of structural health monitoring data
Neurocomputing
Proceedings of the fifth ACM international conference on Web search and data mining
The mathematics of divergence based online learning in vector quantization
ANNPR'10 Proceedings of the 4th IAPR TC3 conference on Artificial Neural Networks in Pattern Recognition
Hybrid clustering of multiple information sources via HOSVD
ISNN'10 Proceedings of the 7th international conference on Advances in Neural Networks - Volume Part II
ISNN'10 Proceedings of the 7th international conference on Advances in Neural Networks - Volume Part II
Algorithms for probabilistic latent tensor factorization
Signal Processing
Informed source separation through spectrogram coding and data embedding
Signal Processing
ICONIP'11 Proceedings of the 18th international conference on Neural Information Processing - Volume Part II
A two stage algorithm for K-mode convolutive nonnegative tucker decomposition
ICONIP'11 Proceedings of the 18th international conference on Neural Information Processing - Volume Part II
Multiway canonical correlation analysis for frequency components recognition in SSVEP-Based BCIs
ICONIP'11 Proceedings of the 18th international conference on Neural Information Processing - Volume Part I
An automatic music transcription based on translation of spectrum and sound path estimation
ICONIP'11 Proceedings of the 18th international conference on Neural Information Processing - Volume Part I
Factorizing three-way ordinal data using triadic formal concepts
FQAS'11 Proceedings of the 9th international conference on Flexible Query Answering Systems
ACM Transactions on Graphics (TOG) - SIGGRAPH 2012 Conference Proceedings
Block component analysis, a new concept for blind source separation
LVA/ICA'12 Proceedings of the 10th international conference on Latent Variable Analysis and Signal Separation
Nonnegative matrix factorization via generalized product rule and its application for classification
LVA/ICA'12 Proceedings of the 10th international conference on Latent Variable Analysis and Signal Separation
On connection between the convolutive and ordinary nonnegative matrix factorizations
LVA/ICA'12 Proceedings of the 10th international conference on Latent Variable Analysis and Signal Separation
On revealing replicating structures in multiway data: a novel tensor decomposition approach
LVA/ICA'12 Proceedings of the 10th international conference on Latent Variable Analysis and Signal Separation
LVA/ICA'12 Proceedings of the 10th international conference on Latent Variable Analysis and Signal Separation
Real-Time speech separation by semi-supervised nonnegative matrix factorization
LVA/ICA'12 Proceedings of the 10th international conference on Latent Variable Analysis and Signal Separation
Nesterov's iterations for NMF-Based supervised classification of texture patterns
LVA/ICA'12 Proceedings of the 10th international conference on Latent Variable Analysis and Signal Separation
LVA/ICA'12 Proceedings of the 10th international conference on Latent Variable Analysis and Signal Separation
NIMFA: a python library for nonnegative matrix factorization
The Journal of Machine Learning Research
Towards mobile intelligence: Learning from GPS history data for collaborative recommendation
Artificial Intelligence
A combination of parallel factor and independent component analysis
Signal Processing
Fast bregman divergence NMF using taylor expansion and coordinate descent
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Fast Nonnegative Matrix Factorization: An Active-Set-Like Method and Comparisons
SIAM Journal on Scientific Computing
SIAM Journal on Matrix Analysis and Applications
Initialization of nonnegative matrix factorization with vertices of convex polytope
ICAISC'12 Proceedings of the 11th international conference on Artificial Intelligence and Soft Computing - Volume Part I
Tensor based sparse decomposition of 3D shape for visual detection of mirror symmetry
Computer Methods and Programs in Biomedicine
Journal of Signal Processing Systems
KI'12 Proceedings of the 35th Annual German conference on Advances in Artificial Intelligence
Pairwise clustering with t-PLSI
ICANN'12 Proceedings of the 22nd international conference on Artificial Neural Networks and Machine Learning - Volume Part II
Selecting β-divergence for nonnegative matrix factorization by score matching
ICANN'12 Proceedings of the 22nd international conference on Artificial Neural Networks and Machine Learning - Volume Part II
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
On solving biquadratic optimization via semidefinite relaxation
Computational Optimization and Applications
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part I
Linked PARAFAC/CP tensor decomposition and its fast implementation for multi-block tensor analysis
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part III
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part III
Adaptive multiplicative updates for projective nonnegative matrix factorization
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part III
Online projective nonnegative matrix factorization for large datasets
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part III
Joint training of non-negative Tucker decomposition and discrete density hidden Markov models
Computer Speech and Language
A Tensor Factorization Approach to Generalization in Multi-agent Reinforcement Learning
WI-IAT '12 Proceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology - Volume 02
Focus 3D: Compressive accommodation display
ACM Transactions on Graphics (TOG)
Sparse and unique nonnegative matrix factorization through data preprocessing
The Journal of Machine Learning Research
LDA-based online topic detection using tensor factorization
Journal of Information Science
Nonnegative Least-Squares Methods for the Classification of High-Dimensional Biological Data
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Multi-dimensional causal discovery
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Non-negative multiple matrix factorization
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Subtractive clustering for seeding non-negative matrix factorizations
Information Sciences: an International Journal
Temporal QoS-aware web service recommendation via non-negative tensor factorization
Proceedings of the 23rd international conference on World wide web
A time-based collective factorization for topic discovery and monitoring in news
Proceedings of the 23rd international conference on World wide web
Journal of Global Optimization
Global convergence of modified multiplicative updates for nonnegative matrix factorization
Computational Optimization and Applications
Hi-index | 0.07 |
This book provides a broad survey of models and efficient algorithms for Nonnegative Matrix Factorization (NMF). This includes NMFs various extensions and modifications, especially Nonnegative Tensor Factorizations (NTF) and Nonnegative Tucker Decompositions (NTD). NMF/NTF and their extensions are increasingly used as tools in signal and image processing, and data analysis, having garnered interest due to their capability to provide new insights and relevant information about the complex latent relationships in experimental data sets. It is suggested that NMF can provide meaningful components with physical interpretations; for example, in bioinformatics, NMF and its extensions have been successfully applied to gene expression, sequence analysis, the functional characterization of genes, clustering and text mining. As such, the authors focus on the algorithms that are most useful in practice, looking at the fastest, most robust, and suitable for large-scale models. Key features: Acts as a single source reference guide to NMF, collating information that is widely dispersed in current literature, including the authors own recently developed techniques in the subject area. Uses generalized cost functions such as Bregman, Alpha and Beta divergences, to present practical implementations of several types of robust algorithms, in particular Multiplicative, Alternating Least Squares, Projected Gradient and Quasi Newton algorithms. Provides a comparative analysis of the different methods in order to identify approximation error and complexity. Includes pseudo codes and optimized MATLAB source codes for almost all algorithms presented in the book. The increasing interest in nonnegative matrix and tensor factorizations, as well as decompositions and sparse representation of data, will ensure that this book is essential reading for engineers, scientists, researchers, industry practitioners and graduate students across signal and image processing; neuroscience; data mining and data analysis; computer science; bioinformatics; speech processing; biomedical engineering; and multimedia.