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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 601–625 of 823 papers

TitleStatusHype
Prior-Less Compressible Structure From Motion—0
Saliency Guided Dictionary Learning for Weakly-Supervised Image Parsing—0
Efficient Large-Scale Similarity Search Using Matrix Factorization—0
Sparse Coding for Third-Order Super-Symmetric Tensor Descriptors With Application to Texture Recognition—0
Rain Streak Removal Using Layer Priors—0
TenSR: Multi-Dimensional Tensor Sparse Representation—0
Feuding Families and Former Friends: Unsupervised Learning for Dynamic Fictional Relationships—0
Sparse Coding for Classification via Discrimination Ensemble—0
Sample-Specific SVM Learning for Person Re-Identification—0
Domain Transfer Multi-Instance Dictionary Learning—0
Simultaneous Sparse Dictionary Learning and Pruning—0
Self-expressive Dictionary Learning for Dynamic 3D Reconstruction—0
X-ray image separation via coupled dictionary learning—0
Minimax Lower Bounds for Kronecker-Structured Dictionary Learning—0
Identification of refugee influx patterns in Greece via model-theoretic analysis of daily arrivals—0
Dictionary Learning for Massive Matrix FactorizationCode0
Decentralized Dynamic Discriminative Dictionary Learning—0
Spatially Aware Dictionary Learning and Coding for Fossil Pollen Identification—0
Semi-supervised Dictionary Learning Based on Hilbert-Schmidt Independence Criterion—0
An information theoretic formulation of the Dictionary Learning and Sparse Coding Problems on Statistical Manifolds—0
Identifying global optimality for dictionary learning—0
Efficient Dictionary Learning with Sparseness-Enforcing Projections—0
Joint Projection and Dictionary Learning using Low-rank Regularization and Graph Constraints—0
Buried object detection using handheld WEMI with task-driven extended functions of multiple instances—0
Learning zeroth class dictionary for human action recognition—0
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