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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 276–300 of 823 papers

TitleStatusHype
Dictionary Learning with Low-rank Coding Coefficients for Tensor Completion—0
Online nonnegative CP-dictionary learning for Markovian dataCode0
Semi-supervised dictionary learning with graph regularization and active pointsCode0
ECG Beats Fast Classification Base on Sparse DictionariesCode0
CLEANN: Accelerated Trojan Shield for Embedded Neural Networks—0
Spatial Transformer Point Convolution—0
Deep sr-DDL: Deep Structurally Regularized Dynamic Dictionary Learning to Integrate Multimodal and Dynamic Functional Connectomics data for Multidimensional Clinical Characterizations—0
ECG beats classification via online sparse dictionary and time pyramid matchingCode0
Unidentified Floating Object detection in maritime environment using dictionary learning—0
Sparsifying Dictionary Learning for Beamspace Channel Representation and Estimation in Millimeter-Wave Massive MIMO—0
Group Invariant Dictionary Learning—0
Data-driven geophysics: from dictionary learning to deep learning—0
Efficient and Parallel Separable Dictionary LearningCode0
High-speed Millimeter-wave 5G/6G Image Transmission via Artificial Intelligence—0
Novel min-max reformulations of Linear Inverse Problems—0
Integrating Neural Networks and Dictionary Learning for Multidimensional Clinical Characterizations from Functional Connectomics Data—0
A Deep-Generative Hybrid Model to Integrate Multimodal and Dynamic Connectivity for Predicting Spectrum-Level Deficits in AutismCode0
Provable Online CP/PARAFAC Decomposition of a Structured Tensor via Dictionary LearningCode0
Functional connectome fingerprinting: Identifying individuals and predicting cognitive function via deep learning—0
Towards improving discriminative reconstruction via simultaneous dense and sparse codingCode0
On the Preservation of Spatio-temporal Information in Machine Learning Applications—0
Recovery and Generalization in Over-Realized Dictionary Learning—0
Supervised Learning of Sparsity-Promoting Regularizers for Denoising—0
Evolutionary Simplicial Learning as a Generative and Compact Sparse Framework for Classification—0
Learned Multi-layer Residual Sparsifying Transform Model for Low-dose CT Reconstruction—0
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