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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 176–200 of 823 papers

TitleStatusHype
Deep Spatial Feature Reconstruction for Partial Person Re-identification: Alignment-Free ApproachCode0
A Zero-Shot Physics-Informed Dictionary Learning Approach for Sound Field ReconstructionCode0
Complete Dictionary Recovery over the SphereCode0
Towards improving discriminative reconstruction via simultaneous dense and sparse codingCode0
Fast Low-rank Shared Dictionary Learning for Image ClassificationCode0
Optimal Projections for Discriminative Dictionary Learning using the JL-lemmaCode0
Complete Dictionary Recovery over the Sphere II: Recovery by Riemannian Trust-region Method—0
An unsupervised deep learning framework for medical image denoising—0
Complete Dictionary Learning via ^4-Norm Maximization over the Orthogonal Group—0
Community-Level Anomaly Detection for Anti-Money Laundering—0
A Lightweight Randomized Nonlinear Dictionary Learning Method using Random Vector Functional Link—0
A Linearly Convergent Method for Non-Smooth Non-Convex Optimization on the Grassmannian with Applications to Robust Subspace and Dictionary Learning—0
Collaborative Representation for Classification, Sparse or Non-sparse?—0
A Novel Tensor-Based Video Rain Streaks Removal Approach via Utilizing Discriminatively Intrinsic Priors—0
Coding Kendall's Shape Trajectories for 3D Action Recognition—0
Clustering Inductive Biases with Unrolled Networks—0
Anomaly-Sensitive Dictionary Learning for Unsupervised Diagnostics of Solid Media—0
Alignment Distances on Systems of Bags—0
Adaptive Spatial-Spectral Dictionary Learning for Hyperspectral Image Denoising—0
Cloud K-SVD: A Collaborative Dictionary Learning Algorithm for Big, Distributed Data—0
CLEANN: Accelerated Trojan Shield for Embedded Neural Networks—0
Class specific or shared? A cascaded dictionary learning framework for image classification—0
An information theoretic formulation of the Dictionary Learning and Sparse Coding Problems on Statistical Manifolds—0
A High-Performance Accelerator for Super-Resolution Processing on Embedded GPU—0
An Inequality with Applications to Structured Sparsity and Multitask Dictionary Learning—0
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