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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 726–750 of 823 papers

TitleStatusHype
Generalized Adaptive Dictionary Learning via Domain Shift Minimization—0
Generalized Conditional Gradient for Sparse Estimation—0
Reconstructive Sparse Code Transfer for Contour Detection and Semantic Labeling—0
Proceedings of the second "international Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST'14)—0
Active Dictionary Learning in Sparse Representation Based Classification—0
On the need for metrics in dictionary learning assessmentCode0
Kernel Coding: General Formulation and Special Cases—0
Sparse Coding on Symmetric Positive Definite Manifolds using Bregman Divergences—0
_1-K-SVD: A Robust Dictionary Learning Algorithm With Simultaneous Update—0
Dependent Nonparametric Bayesian Group Dictionary Learning for online reconstruction of Dynamic MR images—0
A fast patch-dictionary method for whole image recovery—0
Sparse and spurious: dictionary learning with noise and outliers—0
Subspace metrics for multivariate dictionaries and application to EEGCode0
Dictionary Learning and Tensor Decomposition via the Sum-of-Squares Method—0
Estimating the distribution of Galaxy Morphologies on a continuous space—0
A Fully Automated Latent Fingerprint Matcher with Embedded Self-learning Segmentation Module—0
Learning computationally efficient dictionaries and their implementation as fast transforms—0
Structured Dictionary Learning for Classification—0
Learning Scalable Discriminative Dictionary with Sample Relatedness—0
Latent Dictionary Learning for Sparse Representation based Classification—0
l0 Norm Based Dictionary Learning by Proximal Methods with Global Convergence—0
Semi-Supervised Coupled Dictionary Learning for Person Re-identification—0
Multivariate General Linear Models (MGLM) on Riemannian Manifolds with Applications to Statistical Analysis of Diffusion Weighted Images—0
Decomposable Nonlocal Tensor Dictionary Learning for Multispectral Image Denoising—0
Sparse Dictionary Learning for Edit Propagation of High-Resolution Images—0
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