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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 251–275 of 823 papers

TitleStatusHype
Conformal and Low-Rank Sparse Representation for Image Restoration—0
Dictionary Learning with Almost Sure Error Constraints—0
Dictionary Learning with Convex Update (ROMD)—0
Dictionary Learning with Equiprobable Matching Pursuit—0
Alternative Learning Paradigms for Image Quality Transfer—0
使用字典學習法於強健性語音辨識(The Use of Dictionary Learning Approach for Robustness Speech Recognition) [In Chinese]—0
Confident Kernel Sparse Coding and Dictionary Learning—0
Concave losses for robust dictionary learning—0
A Resolution Independent Neural Operator—0
Archetypal SAE: Adaptive and Stable Dictionary Learning for Concept Extraction in Large Vision Models—0
DLDL: Dynamic Label Dictionary Learning via Hypergraph Regularization—0
Compressive Scanning Transmission Electron Microscopy—0
Alternating minimization for dictionary learning with random initialization—0
Dynamically Hierarchy Revolution: DirNet for Compressing Recurrent Neural Network on Mobile Devices—0
On Distributed Non-convex Optimization: Projected Subgradient Method For Weakly Convex Problems in Networks—0
Distributed dictionary learning over a sensor network—0
Compressive hyperspectral imaging via adaptive sampling and dictionary learning—0
Distributed Dictionary Learning—0
Compressive Electron Backscatter Diffraction Imaging—0
Approximate Guarantees for Dictionary Learning—0
Alternating minimization for dictionary learning: Local Convergence Guarantees—0
DLIMD: Dictionary Learning based Image-domain Material Decomposition for spectral CT—0
Computational Intractability of Dictionary Learning for Sparse Representation—0
DNF: Unconditional 4D Generation with Dictionary-based Neural Fields—0
Discriminative Robust Deep Dictionary Learning for Hyperspectral Image Classification—0
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