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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 76–100 of 823 papers

TitleStatusHype
Classification of dry age-related macular degeneration and diabetic macular edema from optical coherence tomography images using dictionary learning—0
Class specific or shared? A cascaded dictionary learning framework for image classification—0
Analysis of Fast Alternating Minimization for Structured Dictionary Learning—0
ANALYSIS OF CALIBRATED SEA CLUTTER AND BOAT REFLECTIVITY DATA AT C- AND X-BAND IN SOUTH AFRICAN COASTAL WATERS—0
A fast patch-dictionary method for whole image recovery—0
A Batchwise Monotone Algorithm for Dictionary Learning—0
Active Deep Learning for Classification of Hyperspectral Images—0
Boosting Dictionary Learning with Error Codes—0
A Benchmark for Sparse Coding: When Group Sparsity Meets Rank Minimization—0
Automatic Identification of Epileptic Seizures from EEG Signals using Sparse Representation-based Classification—0
Automated Multiscale 3D Feature Learning for Vessels Segmentation in Thorax CT Images—0
A variational autoencoder-based nonnegative matrix factorisation model for deep dictionary learning—0
Analysis Dictionary Learning: An Efficient and Discriminative Solution—0
A Fast Dictionary Learning Method for Coupled Feature Space Learning—0
Bayesian Nonparametric Dictionary Learning for Compressed Sensing MRI—0
Bayesian sparsity and class sparsity priors for dictionary learning and coding—0
Beta Process Joint Dictionary Learning for Coupled Feature Spaces with Application to Single Image Super-Resolution—0
Beyond Codebook-Based Analog Beamforming at mmWave: Compressed Sensing and Machine Learning Methods—0
Beyond Label Attention: Transparency in Language Models for Automated Medical Coding via Dictionary Learning—0
Binary Matrix Factorization via Dictionary Learning—0
Analysis of Fast Structured Dictionary Learning—0
BINDy -- Bayesian identification of nonlinear dynamics with reversible-jump Markov-chain Monte-Carlo—0
Blind Denoising Autoencoder—0
Analysis Co-Sparse Coding for Energy Disaggregation—0
A Tree-based Dictionary Learning Framework—0
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