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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
Simple Deep Random Model Ensemble—0
Simultaneous Detection of Multiple Appliances from Smart-meter Measurements via Multi-Label Consistent Deep Dictionary Learning and Deep Transform Learning—0
Simultaneous Sparse Dictionary Learning and Pruning—0
Simultaneous Super-Resolution and Cross-Modality Synthesis of 3D Medical Images using Weakly-Supervised Joint Convolutional Sparse Coding—0
Sketching Algorithms for Sparse Dictionary Learning: PTAS and Turnstile Streaming—0
Sparse and spurious: dictionary learning with noise and outliers—0
Sparse Bayesian Dictionary Learning with a Gaussian Hierarchical Model—0
Sparse Coding and Autoencoders—0
Sparse Coding and Dictionary Learning With Linear Dynamical Systems—0
Sparse Coding for Classification via Discrimination Ensemble—0
Sparse coding for multitask and transfer learning—0
Sparse Coding for Third-Order Super-Symmetric Tensor Descriptors With Application to Texture Recognition—0
Sparse Coding of Shape Trajectories for Facial Expression and Action Recognition—0
Sparse Coding on Cascaded Residuals—0
Sparse Coding on Symmetric Positive Definite Manifolds using Bregman Divergences—0
Sparse Coding with Fast Image Alignment via Large Displacement Optical Flow—0
Sparse Dictionary-based Attributes for Action Recognition and Summarization—0
Sparse Dictionary Learning by Dynamical Neural Networks—0
Sparse Dictionary Learning for Edit Propagation of High-Resolution Images—0
Sparse Dictionary Learning for Image Recovery by Iterative Shrinkage—0
Sparse Dynamic 3D Reconstruction From Unsynchronized Videos—0
Sparse Factor Analysis for Learning and Content Analytics—0
Sparse Factorization Layers for Neural Networks with Limited Supervision—0
Sparse, Geometric Autoencoder Models of V1—0
Sparse Hierachical Extrapolated Parametric Methods for Cortical Data Analysis—0
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