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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 426–450 of 823 papers

TitleStatusHype
Fast and robust tensor decomposition with applications to dictionary learning—0
Fast and Scalable Distributed Deep Convolutional Autoencoder for fMRI Big Data Analytics—0
Fast Convolutional Dictionary Learning off the Grid—0
Fast greedy algorithms for dictionary selection with generalized sparsity constraints—0
Fast Multi-class Dictionaries Learning with Geometrical Directions in MRI Reconstruction—0
Fast Orthonormal Sparsifying Transforms Based on Householder Reflectors—0
Fast Rotational Sparse Coding—0
Fast Structured Orthogonal Dictionary Learning using Householder Reflections—0
Features that Make a Difference: Leveraging Gradients for Improved Dictionary Learning—0
Federated Dataset Dictionary Learning for Multi-Source Domain Adaptation—0
Feuding Families and Former Friends: Unsupervised Learning for Dynamic Fictional Relationships—0
Finding GEMS: Multi-Scale Dictionaries for High-Dimensional Graph Signals—0
Finding the Sparsest Vectors in a Subspace: Theory, Algorithms, and Applications—0
First and Second Order Methods for Online Convolutional Dictionary Learning—0
Flexible Multi-layer Sparse Approximations of Matrices and Applications—0
Frame-based Sparse Analysis and Synthesis Signal Representations and Parseval K-SVD—0
Frequency Regularized Deep Convolutional Dictionary Learning and Application to Blind Denoising—0
FRIST - Flipping and Rotation Invariant Sparsifying Transform Learning and Applications—0
From Attention to Atoms: Spectral Dictionary Learning for Fast, Interpretable Language Models—0
Functional connectome fingerprinting: Identifying individuals and predicting cognitive function via deep learning—0
Gaussian Process Convolutional Dictionary Learning—0
Compressive Sensing and Neural Networks from a Statistical Learning Perspective—0
Generalization Error Bounds for Iterative Recovery Algorithms Unfolded as Neural Networks—0
Generalized Adaptive Dictionary Learning via Domain Shift Minimization—0
Generalized Conditional Gradient for Sparse Estimation—0
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