Atomic Decomposition by Basis Pursuit
SIAM Journal on Scientific Computing
Dictionary learning algorithms for sparse representation
Neural Computation
Digital Signal Processing
Method of optimal directions for frame design
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 05
Dictionary learning for sparse approximations with the majorization method
IEEE Transactions on Signal Processing
IEEE Transactions on Image Processing
Clustering-based denoising with locally learned dictionaries
IEEE Transactions on Image Processing
Sparse and Redundant Modeling of Image Content Using an Image-Signature-Dictionary
SIAM Journal on Imaging Sciences
Online Learning for Matrix Factorization and Sparse Coding
The Journal of Machine Learning Research
Dictionary identification: sparse matrix-factorization via l1-minimization
IEEE Transactions on Information Theory
SPARLS: the sparse RLS algorithm
IEEE Transactions on Signal Processing
Recursive least squares dictionary learning algorithm
IEEE Transactions on Signal Processing
Sparse nonnegative matrix factorization for protein sequence motif discovery
Expert Systems with Applications: An International Journal
-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation
IEEE Transactions on Signal Processing
An augmented Lagrangian approach to general dictionary learning for image denoising
Journal of Visual Communication and Image Representation
Signal Recovery From Random Measurements Via Orthogonal Matching Pursuit
IEEE Transactions on Information Theory
Image Denoising Via Sparse and Redundant Representations Over Learned Dictionaries
IEEE Transactions on Image Processing
Dictionary learning and similarity regularization based image noise reduction
Journal of Visual Communication and Image Representation
Dictionary learning based impulse noise removal via L1-L1 minimization
Signal Processing
Label Consistent K-SVD: Learning a Discriminative Dictionary for Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
| Hi-index | 12.05 |
We introduce a coefficient update procedure into existing batch and online dictionary learning algorithms. We first propose an algorithm which is a coefficient updated version of the Method of Optimal Directions (MOD) dictionary learning algorithm (DLA). The MOD algorithm with coefficient updates presents a computationally expensive dictionary learning iteration with high convergence rate. Secondly, we present a periodically coefficient updated version of the online Recursive Least Squares (RLS)-DLA, where the data is used sequentially to gradually improve the learned dictionary. The developed algorithm provides a periodical update improvement over the RLS-DLA, and we call it as the Periodically Updated RLS Estimate (PURE) algorithm for dictionary learning. The performance of the proposed DLAs in synthetic dictionary learning and image denoising settings demonstrates that the coefficient update procedure improves the dictionary learning ability.