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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
Dictionary-Learning-Based Data Pruning for System Identification—0
Dictionary learning based image enhancement for rarity detection—0
Dictionary Learning Based on Sparse Distribution Tomography—0
Dictionary-Learning-Based Reconstruction Method for Electron Tomography—0
Alternative Learning Paradigms for Image Quality Transfer—0
Dictionary Learning for Adaptive GPR Landmine Classification—0
Dictionary Learning for Blind One Bit Compressed Sensing—0
CLEANN: Accelerated Trojan Shield for Embedded Neural Networks—0
Dictionary learning for fast classification based on soft-thresholding—0
Cloud K-SVD: A Collaborative Dictionary Learning Algorithm for Big, Distributed Data—0
Dictionary Learning for Robotic Grasp Recognition and Detection—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
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
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
Confident Kernel Sparse Coding and Dictionary Learning—0
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