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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 526–550 of 823 papers

TitleStatusHype
Fast and robust tensor decomposition with applications to dictionary learning—0
Robust Sonar ATR Through Bayesian Pose Corrected Sparse Classification—0
Alignment Distances on Systems of Bags—0
Online Convolutional Dictionary Learning for Multimodal Imaging—0
Multiple Instance Dictionary Learning for Beat-to-Beat Heart Rate Monitoring from Ballistocardiograms—0
Personalized Age Progression with Bi-level Aging Dictionary Learning—0
Multi-Focus Image Fusion Using Sparse Representation and Coupled Dictionary Learning—0
Local Information with Feedback Perturbation Suffices for Dictionary Learning in Neural Circuits—0
Convolutional Dictionary Learning via Local ProcessingCode0
Cross-label Suppression: A Discriminative and Fast Dictionary Learning with Group Regularization—0
Simultaneous Super-Resolution and Cross-Modality Synthesis of 3D Medical Images using Weakly-Supervised Joint Convolutional Sparse Coding—0
Classification and Representation via Separable Subspaces: Performance Limits and Algorithms—0
Optimal Projected Variance Group-Sparse Block PCA—0
Regularized Residual Quantization: a multi-layer sparse dictionary learning approach—0
Discriminative Nonlinear Analysis Operator Learning: When Cosparse Model Meets Image Classification—0
Sparse Hierachical Extrapolated Parametric Methods for Cortical Data Analysis—0
Group-based Sparse Representation for Image Compressive Sensing Reconstruction with Non-Convex Regularization—0
Model-based Iterative Restoration for Binary Document Image Compression with Dictionary Learning—0
A Deep Cascade of Convolutional Neural Networks for Dynamic MR Image ReconstructionCode0
Learning a collaborative multiscale dictionary based on robust empirical mode decomposition—0
Robust Kronecker-Decomposable Component Analysis for Low-Rank ModelingCode0
Face Recognition using Multi-Modal Low-Rank Dictionary Learning—0
Local Patch Encoding-Based Method for Single Image Super-Resolution—0
Online Multilinear Dictionary Learning—0
A Deep Cascade of Convolutional Neural Networks for MR Image ReconstructionCode0
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