Independent component analysis, a new concept?
Signal Processing - Special issue on higher order statistics
Independent component analysis: algorithms and applications
Neural Networks
Estimation of parameters and eigenmodes of multivariate autoregressive models
ACM Transactions on Mathematical Software (TOMS)
ACM Transactions on Mathematical Software (TOMS)
Estimating Overcomplete Independent Component Bases for Image Windows
Journal of Mathematical Imaging and Vision
SSAP '96 Proceedings of the 8th IEEE Signal Processing Workshop on Statistical Signal and Array Processing (SSAP '96)
Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications
Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications
Variational Bayesian learning of ICA with missing data
Neural Computation
View-Subspace Analysis of Multi-View Face Patterns
RATFG-RTS '01 Proceedings of the IEEE ICCV Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems (RATFG-RTS'01)
Complex independent component analysis of frequency-domain electroencephalographic data
Neural Networks - Special issue: Neuroinformatics
Beyond independent components: trees and clusters
The Journal of Machine Learning Research
ICA using spacings estimates of entropy
The Journal of Machine Learning Research
Image matching using alpha-entropy measures and entropic graphs
Signal Processing - Special section on content-based image and video retrieval
Independent subspace analysis using geodesic spanning trees
ICML '05 Proceedings of the 22nd international conference on Machine learning
Topographic Independent Component Analysis
Neural Computation
Undercomplete Blind Subspace Deconvolution
The Journal of Machine Learning Research
Blind separation of convolutive mixtures using second and fourth order moments
ICASSP '96 Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 05
Undercomplete Blind Subspace Deconvolution Via Linear Prediction
ECML '07 Proceedings of the 18th European conference on Machine Learning
Natural Conjugate Gradient on Complex Flag Manifolds for Complex Independent Subspace Analysis
ICANN '08 Proceedings of the 18th international conference on Artificial Neural Networks, Part I
Complete Blind Subspace Deconvolution
ICA '09 Proceedings of the 8th International Conference on Independent Component Analysis and Signal Separation
Hierarchical Extraction of Independent Subspaces of Unknown Dimensions
ICA '09 Proceedings of the 8th International Conference on Independent Component Analysis and Signal Separation
Non-independent BSS: A Model for Evoked MEG Signals with Controllable Dependencies
ICA '09 Proceedings of the 8th International Conference on Independent Component Analysis and Signal Separation
Fast approximate spectral clustering
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Identification of Recurrent Neural Networks by Bayesian Interrogation Techniques
The Journal of Machine Learning Research
Auto-regressive independent process analysis without combinatorial efforts
Pattern Analysis & Applications
Independent process analysis without a priori dimensional information
ICA'07 Proceedings of the 7th international conference on Independent component analysis and signal separation
Bayesian estimation of overcomplete independent feature subspaces for natural images
ICA'07 Proceedings of the 7th international conference on Independent component analysis and signal separation
Post nonlinear independent subspace analysis
ICANN'07 Proceedings of the 17th international conference on Artificial neural networks
Independent subspace analysis using k-nearest neighborhood distances
ICANN'05 Proceedings of the 15th international conference on Artificial neural networks: formal models and their applications - Volume Part II
Tree-Dependent components of gene expression data for clustering
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part II
Second-Order separation of multidimensional sources with constrained mixing system
ICA'06 Proceedings of the 6th international conference on Independent Component Analysis and Blind Signal Separation
Riemannian optimization method on the flag manifold for independent subspace analysis
ICA'06 Proceedings of the 6th international conference on Independent Component Analysis and Blind Signal Separation
Cross-Entropy optimization for independent process analysis
ICA'06 Proceedings of the 6th international conference on Independent Component Analysis and Blind Signal Separation
Independent subspace analysis on innovations
ECML'05 Proceedings of the 16th European conference on Machine Learning
Source separation in post-nonlinear mixtures
IEEE Transactions on Signal Processing
Complex random vectors and ICA models: identifiability, uniqueness, and separability
IEEE Transactions on Information Theory
Multivariate MIMO FIR inverses
IEEE Transactions on Image Processing
Face recognition by independent component analysis
IEEE Transactions on Neural Networks
On computation of approximate joint block-diagonalization using ordinary AJD
LVA/ICA'12 Proceedings of the 10th international conference on Latent Variable Analysis and Signal Separation
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Independent component analysis (ICA) - the theory of mixed, independent, non-Gaussian sources - has a central role in signal processing, computer vision and pattern recognition. One of the most fundamental conjectures of this research field is that independent subspace analysis (ISA) - the extension of the ICA problem, where groups of sources are independent - can be solved by traditional ICA followed by grouping the ICA components. The conjecture, called ISA separation principle, (i) has been rigorously proven for some distribution types recently, (ii) forms the basis of the state-of-the-art ISA solvers, (iii) enables one to estimate the unknown number and the dimensions of the sources efficiently, and (iv) can be extended to generalizations of the ISA task, such as different linear-, controlled-, post nonlinear-, complex valued-, partially observed problems, as well as to problems dealing with nonparametric source dynamics. Here, we shall review the advances on this field.