Vector quantization and signal compression
Vector quantization and signal compression
Atomic Decomposition by Basis Pursuit
SIAM Journal on Scientific Computing
Journal of Optimization Theory and Applications
Multi-frame compression: theory and design
Signal Processing - Special section on signal processing technologies for short burst wireless communications
Journal of Global Optimization
Dictionary learning algorithms for sparse representation
Neural Computation
Blind Source Separation by Sparse Decomposition in a Signal Dictionary
Neural Computation
Learning Overcomplete Representations
Neural Computation
Algorithms for simultaneous sparse approximation: part I: Greedy pursuit
Signal Processing - Sparse approximations in signal and image processing
Algorithms for simultaneous sparse approximation: part II: Convex relaxation
Signal Processing - Sparse approximations in signal and image processing
Separation of a subspace-sparse signal: Algorithms and conditions
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
Block-sparsity: Coherence and efficient recovery
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
Dictionary learning for sparse approximations with the majorization method
IEEE Transactions on Signal Processing
Sparse representation of deformable 3D organs
ISBI'09 Proceedings of the Sixth IEEE international conference on Symposium on Biomedical Imaging: From Nano to Macro
Two improved sparse decomposition methods for blind source separation
ICA'07 Proceedings of the 7th international conference on Independent component analysis and signal separation
In vivo tracking of 3D organs using spherical harmonics and subspace clustering
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Under-Determined source separation: comparison of two approaches based on sparse decompositions
ICA'06 Proceedings of the 6th international conference on Independent Component Analysis and Blind Signal Separation
-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation
IEEE Transactions on Signal Processing
Blind separation of speech mixtures via time-frequency masking
IEEE Transactions on Signal Processing
Performance measurement in blind audio source separation
IEEE Transactions on Audio, Speech, and Language Processing
Sparse and shift-Invariant representations of music
IEEE Transactions on Audio, Speech, and Language Processing
A Bayesian Approach for Blind Separation of Sparse Sources
IEEE Transactions on Audio, Speech, and Language Processing
Sparse representation of deformable 3D organs with spherical harmonics and structured dictionary
Journal of Biomedical Imaging - Special issue on Machine Learning in Medical Imaging
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In this paper, we introduce the iterative subspace identification (ISI) algorithm for learning subspaces in which the data may live. Our subspace identification method differs from currently available method in its ability to infer the dimension of the subspaces from the data without prior knowledge. The learned subspaces can be combined to produce a data driven overcomplete dictionary with good sparseness and generalizability qualities, or can be directly exploited in applications where block sparseness is needed. We describe the ISI algorithm and a complementary optimization method. We demonstrate the ability of the proposed method to produce sparse representations comparable to those achieved with the K-SVD algorithm, but with less than one eighth the training time. Furthermore, the computation savings allows us to develop a shift-tolerant training procedure. We also illustrate its benefits in underdetermined blind source separation of audio,where performance is directly impacted by the sparseness of the representation.