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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 526–550 of 823 papers

TitleStatusHype
Learning Invariant Subspaces of Koopman Operators--Part 1: A Methodology for Demonstrating a Dictionary's Approximate Subspace Invariance—0
Learning joint intensity-depth sparse representations—0
Learning Light Field Reconstruction from a Single Coded Image—0
Learning Linear Dynamical Systems with High-Order Tensor Data for Skeleton based Action Recognition—0
Learning Log-Determinant Divergences for Positive Definite Matrices—0
Learning quadrangulated patches for 3D shape parameterization and completion—0
Learning Scalable Discriminative Dictionary with Sample Relatedness—0
Learning Simple Thresholded Features with Sparse Support Recovery—0
Learning Sparse Adversarial Dictionaries For Multi-Class Audio Classification—0
Learning Sparsity-Promoting Regularizers using Bilevel Optimization—0
Learning Stable Multilevel Dictionaries for Sparse Representations—0
Learning zeroth class dictionary for human action recognition—0
Level Set KSVD—0
Lightweight Conceptual Dictionary Learning for Text Classification Using Information Compression—0
Linearization to Nonlinear Learning for Visual Tracking—0
Local identifiability of l_1-minimization dictionary learning: a sufficient and almost necessary condition—0
Local Information with Feedback Perturbation Suffices for Dictionary Learning in Neural Circuits—0
Locality Constrained Analysis Dictionary Learning via K-SVD Algorithm—0
Localized Dictionary design for Geometrically Robust Sonar ATR—0
Local Patch Encoding-Based Method for Single Image Super-Resolution—0
Low-dose spectral CT reconstruction using L0 image gradient and tensor dictionary—0
Low-Rank Embedded Ensemble Semantic Dictionary for Zero-Shot Learning—0
Low-Rank Tensor Approximation With Laplacian Scale Mixture Modeling for Multiframe Image Denoising—0
Majorization Minimization Technique for Optimally Solving Deep Dictionary Learning—0
Making sense of randomness: an approach for fast recovery of compressively sensed signals—0
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