Discriminative Sparse Representations

DOI10.1007/978-3-319-61609-4_6zbMath1443.94034OpenAlexW2766239986MaRDI QIDQ4556983

He Zhang, Vishal M. Patel

Publication date: 28 November 2018

Published in: Handbook of Convex Optimization Methods in Imaging Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-319-61609-4_6

Mathematics Subject Classification ID

Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Uses Software

• Matlab
• PDCO
• Multi-PIE

Cites Work

• Proportional response dynamics in the Fisher market
• The Radon transform
• Multiple kernel-based dictionary learning for weakly supervised classification
• Non-linear dictionary learning with partially labeled data
• The cosparse analysis model and algorithms
• Generalized dictionaries for multiple instance learning
• Optimal global rates of convergence for nonparametric regression
• Sparse representations in unions of bases
• Signal Recovery From Random Measurements Via Orthogonal Matching Pursuit
• Sparse and Redundant Representations
• From Sparse Solutions of Systems of Equations to Sparse Modeling of Signals and Images
• Atomic Decomposition by Basis Pursuit
• Kernel Sparse Representation-Based Classifier
• Analysis K-SVD: A Dictionary-Learning Algorithm for the Analysis Sparse Model
• Learning Sparsifying Transforms
• $rm K$-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation
• Multiple Kernel Learning for Sparse Representation-Based Classification
• Coupled Projections for Adaptation of Dictionaries
• DASH-N: Joint Hierarchical Domain Adaptation and Feature Learning
• Efficient Algorithms for Convolutional Sparse Representations
• Laplacian Eigenmaps for Dimensionality Reduction and Data Representation
• Sparse Representations and Compressive Sensing for Imaging and Vision
• In-Plane Rotation and Scale Invariant Clustering Using Dictionaries
• Design of Non-Linear Kernel Dictionaries for Object Recognition
• Nonlinear Dimensionality Reduction
• Optimally sparse representation in general (nonorthogonal) dictionaries via ℓ ¹ minimization

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