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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 701–725 of 823 papers

TitleStatusHype
Deep Convolutional Neural Networks and Data Augmentation for Environmental Sound ClassificationCode0
Multimodal Task-Driven Dictionary Learning for Image ClassificationCode0
Deep Spatial Feature Reconstruction for Partial Person Re-identification: Alignment-Free ApproachCode0
Subspace metrics for multivariate dictionaries and application to EEGCode0
COVID-19 Time-series Prediction by Joint Dictionary Learning and Online NMFCode0
Finding a sparse vector in a subspace: Linear sparsity using alternating directionsCode0
Multiple Instance Dictionary Learning using Functions of Multiple InstancesCode0
Semi-relaxed Gromov-Wasserstein divergence with applications on graphsCode0
On the need for metrics in dictionary learning assessmentCode0
Spatio-Temporal Deep Learning-Based Undersampling Artefact Reduction for 2D Radial Cine MRI with Limited DataCode0
On the Reconstruction Risk of Convolutional Sparse Dictionary LearningCode0
Reduced Kernel Dictionary LearningCode0
Multiscale Sparsifying Transform Learning for Image DenoisingCode0
Towards improving discriminative reconstruction via simultaneous dense and sparse codingCode0
Subtle Data Crimes: Naively training machine learning algorithms could lead to overly-optimistic resultsCode0
Deriving Autism Spectrum Disorder Functional Networks from RS-FMRI Data using Group ICA and Dictionary LearningCode0
Multi-Source Domain Adaptation through Dataset Dictionary Learning in Wasserstein SpaceCode0
Fusing Dictionary Learning and Support Vector Machines for Unsupervised Anomaly DetectionCode0
Convolutional Dictionary Learning: Acceleration and ConvergenceCode0
Understanding approximate and unrolled dictionary learning for pattern recoveryCode0
Dictionary Learning for the Almost-Linear Sparsity RegimeCode0
Sparse dictionary learning recovers pleiotropy from human cell fitness screensCode0
Semi-supervised dictionary learning with graph regularization and active pointsCode0
Sparse Pursuit and Dictionary Learning for Blind Source Separation in Polyphonic Music RecordingsCode0
Convolutional Analysis Operator Learning: Acceleration and ConvergenceCode0
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