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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 226–250 of 823 papers

TitleStatusHype
Semi-relaxed Gromov-Wasserstein divergence with applications on graphsCode0
Extended dynamic mode decomposition with dictionary learning using neural ordinary differential equations—0
Semi-relaxed Gromov-Wasserstein divergence and applications on graphs—0
Dictionary Learning Under Generative Coefficient Priors with Applications to Compression—0
Patchwise Sparse Dictionary Learning from pre-trained Neural Network Activation Maps for Anomaly Detection in Images—0
Subtle Data Crimes: Naively training machine learning algorithms could lead to overly-optimistic resultsCode0
Statistical limits of dictionary learning: random matrix theory and the spectral replica method—0
Extended Successive Convex Approximation for Phase Retrieval with Dictionary Learning—0
CIM: Class-Irrelevant Mapping for Few-Shot Classification—0
Robust Event Detection based on Spatio-Temporal Latent Action Unit using Skeletal Information—0
Deep learning based dictionary learning and tomographic image reconstruction—0
Online Dictionary Learning Based Fault and Cyber Attack Detection for Power Systems—0
Wave-Informed Matrix Factorization with Global Optimality Guarantees—0
Semi-supervised 3D Hand-Object Pose Estimation via Pose Dictionary Learning—0
Low-rank Dictionary Learning for Unsupervised Feature SelectionCode0
Recovery under Side Constraints—0
Understanding approximate and unrolled dictionary learning for pattern recoveryCode0
Deriving Autism Spectrum Disorder Functional Networks from RS-FMRI Data using Group ICA and Dictionary LearningCode0
Stable and Interpretable Unrolled Dictionary LearningCode0
Optimal Spectral Recovery of a Planted Vector in a Subspace—0
Locality Constrained Analysis Dictionary Learning via K-SVD Algorithm—0
Deep Transform and Metric Learning Networks—0
Learning Log-Determinant Divergences for Positive Definite Matrices—0
Blind Primed Supervised (BLIPS) Learning for MR Image ReconstructionCode0
Deep Multi-Resolution Dictionary Learning for Histopathology Image Analysis—0
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