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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 151–175 of 823 papers

TitleStatusHype
Deriving Autism Spectrum Disorder Functional Networks from RS-FMRI Data using Group ICA and Dictionary LearningCode0
A Deep Cascade of Convolutional Neural Networks for MR Image ReconstructionCode0
Deep Spatial Feature Reconstruction for Partial Person Re-identification: Alignment-Free ApproachCode0
Fault Handling in Large Water Networks with Online Dictionary LearningCode0
Understanding approximate and unrolled dictionary learning for pattern recoveryCode0
CORAD: Correlation-Aware Compression of Massive Time Series using Sparse Dictionary CodingCode0
Distributed Convolutional Dictionary Learning (DiCoDiLe): Pattern Discovery in Large Images and SignalsCode0
Deep Interpretable Non-Rigid Structure from MotionCode0
Deep Network Classification by Scattering and Homotopy Dictionary LearningCode0
Deep Convolutional Neural Networks and Data Augmentation for Environmental Sound ClassificationCode0
A Deep Cascade of Convolutional Neural Networks for Dynamic MR Image ReconstructionCode0
COVID-19 Time-series Prediction by Joint Dictionary Learning and Online NMFCode0
Convolutional dictionary learning based auto-encoders for natural exponential-family distributionsCode0
Information Assisted Dictionary Learning for fMRI data analysisCode0
Interpreting Large Text-to-Image Diffusion Models with Dictionary LearningCode0
Deep Residual Autoencoders for Expectation Maximization-inspired Dictionary LearningCode0
Complete Dictionary Recovery over the SphereCode0
Learning Dictionaries from Physical-Based Interpolation for Water Network Leak LocalizationCode0
Deep Convolutional Neural Networks and Data Augmentation for Environmental Sound ClassificationCode0
Learning Mixtures of Separable Dictionaries for Tensor Data: Analysis and AlgorithmsCode0
Single-Shell NODDI Using Dictionary Learner Estimated Isotropic Volume FractionCode0
Learning Priors in High-frequency Domain for Inverse Imaging ReconstructionCode0
Linearized Kernel Dictionary LearningCode0
Locality Constraint Dictionary Learning with Support Vector for Pattern ClassificationCode0
Hiding Data Helps: On the Benefits of Masking for Sparse CodingCode0
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