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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 801–823 of 823 papers

TitleStatusHype
Sparse Factor Analysis for Learning and Content Analytics—0
Learning Stable Multilevel Dictionaries for Sparse Representations—0
Multiple Kernel Sparse Representations for Supervised and Unsupervised Learning—0
Metrics for Multivariate DictionariesCode0
Bayesian Nonparametric Dictionary Learning for Compressed Sensing MRI—0
Sample Complexity of Bayesian Optimal Dictionary Learning—0
Jitter-Adaptive Dictionary Learning - Application to Multi-Trial Neuroelectric Signals—0
Dictionary Subselection Using an Overcomplete Joint Sparsity Model—0
Semi-blind Source Separation via Sparse Representations and Online Dictionary Learning—0
Online L1-Dictionary Learning with Application to Novel Document Detection—0
Discriminatively Trained Sparse Code Gradients for Contour Detection—0
Sparse coding for multitask and transfer learning—0
Kernelized Supervised Dictionary Learning—0
Poisson noise reduction with non-local PCA—0
Learning joint intensity-depth sparse representations—0
Nonnegative dictionary learning in the exponential noise model for adaptive music signal representation—0
On the Analysis of Multi-Channel Neural Spike Data—0
Learning Hierarchical Sparse Representations using Iterative Dictionary Learning and Dimension Reduction—0
Task-Driven Dictionary Learning—0
Non-Parametric Bayesian Dictionary Learning for Sparse Image Representations—0
Structured Sparse Principal Component Analysis—0
Supervised Dictionary Learning—0
ANALYSIS OF CALIBRATED SEA CLUTTER AND BOAT REFLECTIVITY DATA AT C- AND X-BAND IN SOUTH AFRICAN COASTAL WATERS—0
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