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Dictionary Learning

Dictionary Learning is an important problem in multiple areas, ranging from computational neuroscience, machine learning, to computer vision and image processing. The general goal is to find a good basis for given data. More formally, in the Dictionary Learning problem, also known as sparse coding, we are given samples of a random vector $y\in\mathbb{R}^n$, of the form $y=Ax$ where $A$ is some unknown matrix in $\mathbb{R}^{n×m}$, called dictionary, and $x$ is sampled from an unknown distribution over sparse vectors. The goal is to approximately recover the dictionary $A$.

Source: Polynomial-time tensor decompositions with sum-of-squares

Papers

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Showing 301–325 of 823 papers

TitleStatusHype
Classification of Chinese Handwritten Numbers with Labeled Projective Dictionary Pair Learning—0
Multiscale Sparsifying Transform Learning for Image DenoisingCode0
Fault Handling in Large Water Networks with Online Dictionary LearningCode0
Discriminative Feature and Dictionary Learning with Part-aware Model for Vehicle Re-identification—0
Nonlinear Functional Output Regression: a Dictionary Approach—0
Unsupervised Dictionary Learning for Anomaly Detection—0
Complete Dictionary Learning via _p-norm MaximizationCode1
Sketchformer: Transformer-based Representation for Sketched StructureCode1
Deep Transform and Metric Learning Network: Wedding Deep Dictionary Learning and Neural Networks—0
Unsupervised Adaptive Neural Network Regularization for Accelerated Radial Cine MRI—0
Learning efficient structured dictionary for image classification—0
Learning Deep Analysis Dictionaries -- Part II: Convolutional Dictionaries—0
Finding the Sparsest Vectors in a Subspace: Theory, Algorithms, and Applications—0
Dictionary Learning for Two-Dimensional Kendall Shapes—0
Learning Hybrid Representation by Robust Dictionary Learning in Factorized Compressed Space—0
Convolutional Dictionary Pair Learning Network for Image Representation Learning—0
CORAD: Correlation-Aware Compression of Massive Time Series using Sparse Dictionary CodingCode0
Impulse Denoising From Hyper-Spectral Images: A Blind Compressed Sensing Approach—0
Deep Sparse Coding for Non-Intrusive Load Monitoring—0
Analysis Co-Sparse Coding for Energy Disaggregation—0
Kernel Transform Learning—0
Row-Sparse Discriminative Deep Dictionary Learning for Hyperspectral Image Classification—0
Discriminative Robust Deep Dictionary Learning for Hyperspectral Image Classification—0
Majorization Minimization Technique for Optimally Solving Deep Dictionary Learning—0
Multi-echo Reconstruction from Partial K-space Scans via Adaptively Learnt Basis—0
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