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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 51–75 of 823 papers

TitleStatusHype
Interpreting Large Text-to-Image Diffusion Models with Dictionary LearningCode0
Towards Privacy-Preserving Fine-Grained Visual Classification via Hierarchical Learning from Label Proportions—0
Modeling Musical Genre Trajectories through Pathlet LearningCode0
From Attention to Atoms: Spectral Dictionary Learning for Fast, Interpretable Language Models—0
Optimizing Hard Thresholding for Sparse Model Discovery—0
Unveiling Hidden Collaboration within Mixture-of-Experts in Large Language Models—0
Recognition of Geometrical Shapes by Dictionary Learning—0
Mixture-of-Shape-Experts (MoSE): End-to-End Shape Dictionary Framework to Prompt SAM for Generalizable Medical Segmentation—0
Koopman-Based Methods for EV Climate Dynamics: Comparing eDMD Approaches—0
Decentralized Federated Dataset Dictionary Learning for Multi-Source Domain Adaptation—0
Topological Dictionary LearningCode0
Sparse Dictionary Learning for Image Recovery by Iterative Shrinkage—0
Online multidimensional dictionary learning—0
Weakly Supervised Convolutional Dictionary Learning for Multi-Label ClassificationCode0
Personalized Convolutional Dictionary Learning of Physiological Time SeriesCode0
Unraveling the Localized Latents: Learning Stratified Manifold Structures in LLM Embedding Space with Sparse Mixture-of-Experts—0
Archetypal SAE: Adaptive and Stable Dictionary Learning for Concept Extraction in Large Vision Models—0
Dictionary-Learning-Based Data Pruning for System Identification—0
Inversion of Magnetic Data using Learned Dictionaries and Scale SpaceCode0
Boosting Adversarial Robustness and Generalization with Structural Prior—0
Exploring the Limitations of Structured Orthogonal Dictionary Learning—0
Multi-field Visualization: Trait design and trait-induced merge trees—0
MIRE: Matched Implicit Neural Representations—0
A Zero-Shot Physics-Informed Dictionary Learning Approach for Sound Field ReconstructionCode0
Towards scientific discovery with dictionary learning: Extracting biological concepts from microscopy foundation models—0
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