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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 226–250 of 823 papers

TitleStatusHype
Dictionary learning approach to monitoring of wind turbine drivetrain bearings—0
Denoising Dictionary Learning Against Adversarial Perturbations—0
Dictionary learning based image enhancement for rarity detection—0
Buried object detection using handheld WEMI with task-driven extended functions of multiple instances—0
Dictionary-Learning-Based Reconstruction Method for Electron Tomography—0
Dictionary Learning by Dynamical Neural Networks—0
Dictionary Learning for Adaptive GPR Landmine Classification—0
Dictionary Learning for Blind One Bit Compressed Sensing—0
Denoising and Completion of 3D Data via Multidimensional Dictionary Learning—0
Demystifying overcomplete nonlinear auto-encoders: fast SGD convergence towards sparse representation from random initialization—0
A Benchmark for Sparse Coding: When Group Sparsity Meets Rank Minimization—0
DEMAND: Deep Matrix Approximately Nonlinear Decomposition to Identify Meta, Canonical, and Sub-Spatial Pattern of functional Magnetic Resonance Imaging in the Human Brain—0
Dictionary Learning for Two-Dimensional Kendall Shapes—0
Dictionary Learning from Ambiguously Labeled Data—0
Dictionary Learning from Incomplete Data—0
Dictionary learning -- from local towards global and adaptive—0
Dictionary Learning Improves Patch-Free Circuit Discovery in Mechanistic Interpretability: A Case Study on Othello-GPT—0
Dictionary Learning in Fourier Transform Scanning Tunneling Spectroscopy—0
Dictionary Learning over Distributed Models—0
Deep Transform and Metric Learning Networks—0
Dictionary Learning Strategies for Compressed Fiber Sensing Using a Probabilistic Sparse Model—0
Dictionary Learning Under Generative Coefficient Priors with Applications to Compression—0
Dictionary Learning under Symmetries via Group Representations—0
Dictionary Learning Using Rank-One Atomic Decomposition (ROAD)—0
Boosting Dictionary Learning with Error Codes—0
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