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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 351–375 of 823 papers

TitleStatusHype
Generalized Time Warping Invariant Dictionary Learning for Time Series Classification and Clustering—0
Generative Deep Deconvolutional Learning—0
Generic Image Classification Approaches Excel on Face Recognition—0
Geometric Sparse Coding in Wasserstein Space—0
Decomposable Nonlocal Tensor Dictionary Learning for Multispectral Image Denoising—0
Global Identifiability of _1-based Dictionary Learning via Matrix Volume Optimization—0
Discriminatively Trained Sparse Code Gradients for Contour Detection—0
Globally Variance-Constrained Sparse Representation and Its Application in Image Set Coding—0
Discriminative Localized Sparse Representations for Breast Cancer Screening—0
Greedy Deep Dictionary Learning—0
Compressed Dictionary Learning—0
Greedy Optimization of Electrode Arrangement for Epiretinal Prostheses—0
Applications of Online Nonnegative Matrix Factorization to Image and Time-Series Data—0
Group-based Sparse Representation for Image Compressive Sensing Reconstruction with Non-Convex Regularization—0
Hybrid mmWave MIMO Systems under Hardware Impairments and Beam Squint: Channel Model and Dictionary Learning-aided Configuration—0
Group Crosscoders for Mechanistic Analysis of Symmetry—0
Group Invariant Dictionary Learning—0
Group Re-Identification via Unsupervised Transfer of Sparse Features Encoding—0
Optimal Projected Variance Group-Sparse Block PCA—0
Group sparsity and geometry constrained dictionary learning for action recognition from depth maps.—0
Deep Dictionary Learning: A PARametric NETwork Approach—0
Beta Process Joint Dictionary Learning for Coupled Feature Spaces with Application to Single Image Super-Resolution—0
High-speed Millimeter-wave 5G/6G Image Transmission via Artificial Intelligence—0
Deep Dictionary Learning with An Intra-class Constraint—0
Discriminative Feature and Dictionary Learning with Part-aware Model for Vehicle Re-identification—0
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