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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
Measuring Progress in Dictionary Learning for Language Model Interpretability with Board Game ModelsCode1
Online Multi-Source Domain Adaptation through Gaussian Mixtures and Dataset Dictionary Learning—0
A Model for Combinatorial Dictionary Learning and Inference—0
Subgraph Clustering and Atom Learning for Improved Image Classification—0
GroupCDL: Interpretable Denoising and Compressed Sensing MRI via Learned Group-Sparsity and Circulant AttentionCode1
A Resolution Independent Neural Operator—0
Compressive Electron Backscatter Diffraction Imaging—0
Dataset Dictionary Learning in a Wasserstein Space for Federated Domain Adaptation—0
Variational Learning ISTA—0
Unmixing Noise from Hawkes Process to Model Learned Physiological Events—0
A Concept-Based Explainability Framework for Large Multimodal ModelsCode1
Unsupervised learning of Data-driven Facial Expression Coding System (DFECS) using keypoint tracking—0
CREIMBO: Cross-Regional Ensemble Interactions in Multi-view Brain Observations—0
Improving Language Models Trained on Translated Data with Continual Pre-Training and Dictionary Learning Analysis—0
Identifying Functionally Important Features with End-to-End Sparse Dictionary LearningCode2
Towards Principled Evaluations of Sparse Autoencoders for Interpretability and Control—0
Efficient Matrix Factorization Via Householder Reflections—0
Lightweight Conceptual Dictionary Learning for Text Classification Using Information Compression—0
Improving Dictionary Learning with Gated Sparse AutoencodersCode3
Lighter, Better, Faster Multi-Source Domain Adaptation with Gaussian Mixture Models and Optimal TransportCode0
Dynamic fault detection and diagnosis of industrial alkaline water electrolyzer process with variational Bayesian dictionary learning—0
Multibranch Generative Models for Multichannel Imaging with an Application to PET/CT Synergistic Reconstruction—0
Fusing Dictionary Learning and Support Vector Machines for Unsupervised Anomaly DetectionCode0
Decentralized Collaborative Learning Framework with External Privacy Leakage Analysis—0
Image Deraining via Self-supervised Reinforcement Learning—0
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