Convergence radius and sample complexity of ITKM algorithms for dictionary learning

DOI10.1016/j.acha.2016.08.002zbMath1439.94013arXiv1503.07027OpenAlexW2963674172MaRDI QIDQ1748252

Karin Schnass

Publication date: 9 May 2018

Published in: Applied and Computational Harmonic Analysis (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1503.07027

zbMATH Keywords

thresholdingdictionary learningconvergence radiussparse codingK-meanssparse component analysissample complexityalternating optimisation

Mathematics Subject Classification ID

Inequalities; stochastic orderings (60E15) Signal theory (characterization, reconstruction, filtering, etc.) (94A12) Source coding (94A29)

Related Items (6)

Generalization Error in Deep Learning ⋮ Applied harmonic analysis and data processing. Abstracts from the workshop held March 25--31, 2018 ⋮ Learning semidefinite regularizers ⋮ A convex variational model for learning convolutional image atoms from incomplete data ⋮ Compressed dictionary learning ⋮ On the Purity and Entropy of Mixed Gaussian States

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Iterative hard thresholding for compressed sensing
• Iterative thresholding for sparse approximations
• On the identifiability of overcomplete dictionaries via the minimisation principle underlying K-SVD
• On the conditioning of random subdictionaries
• RIPless compressed sensing from anisotropic measurements
• Blind Source Separation by Sparse Decomposition in a Signal Dictionary
• Dictionary Learning and Tensor Decomposition via the Sum-of-Squares Method
• Sparse and Spurious: Dictionary Learning With Noise and Outliers
• Sample Complexity of Dictionary Learning and Other Matrix Factorizations
• Hard Thresholding Pursuit: An Algorithm for Compressive Sensing
• Probability Inequalities for the Sum of Independent Random Variables
• Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information
• Stable recovery of sparse overcomplete representations in the presence of noise
• Dictionary Learning for L1-Exact Sparse Coding
• Dictionary Learning Algorithms for Sparse Representation
• Dictionary Learning for Sparse Approximations With the Majorization Method
• Recursive Least Squares Dictionary Learning Algorithm
• $rm K$-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation
• Recovering Low-Rank Matrices From Few Coefficients in Any Basis
• $K$-Dimensional Coding Schemes in Hilbert Spaces
• Dictionary Identification—Sparse Matrix-Factorization via $\ell_1$-Minimization
• Local Identification of Overcomplete Dictionaries
• An introduction to frames and Riesz bases

This page was built for publication: Convergence radius and sample complexity of ITKM algorithms for dictionary learning