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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 251–275 of 823 papers

TitleStatusHype
Gaussian Process Convolutional Dictionary Learning—0
Model-based Reconstruction with Learning: From Unsupervised to Supervised and Beyond—0
Exact Sparse Orthogonal Dictionary Learning—0
An unsupervised deep learning framework for medical image denoising—0
PET Image Reconstruction with Multiple Kernels and Multiple Kernel Space Regularizers—0
Online Orthogonal Dictionary Learning Based on Frank-Wolfe Method—0
Coupled Feature Learning for Multimodal Medical Image FusionCode0
Single-Shell NODDI Using Dictionary Learner Estimated Isotropic Volume FractionCode0
Metalearning: Sparse Variable-Structure Automata—0
Cross-domain Joint Dictionary Learning for ECG Inference from PPG—0
Mixed-Features Vectors and Subspace Splitting—0
Frequency Regularized Deep Convolutional Dictionary Learning and Application to Blind Denoising—0
A Simple Sparse Denoising Layer for Robust Deep Learning—0
Reprogramming Language Models for Molecular Representation Learning—0
K-Deep Simplex: Deep Manifold Learning via Local DictionariesCode0
Extraction of Nystagmus Patterns from Eye-Tracker Data with Convolutional Sparse CodingCode0
A Neuro-Inspired Autoencoding Defense Against Adversarial PerturbationsCode0
Discriminative Localized Sparse Representations for Breast Cancer Screening—0
Efficient Consensus Model based on Proximal Gradient Method applied to Convolutional Sparse Problems—0
Applications of Online Nonnegative Matrix Factorization to Image and Time-Series Data—0
Joint Transceiver Design Based on Dictionary Learning Algorithm for SCMA—0
Compressive Sensing and Neural Networks from a Statistical Learning Perspective—0
SAHDL: Sparse Attention Hypergraph Regularized Dictionary Learning—0
DLDL: Dynamic Label Dictionary Learning via Hypergraph Regularization—0
Region-specific Dictionary Learning-based Low-dose Thoracic CT Reconstruction—0
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