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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 476–500 of 823 papers

TitleStatusHype
Improving Language Models Trained on Translated Data with Continual Pre-Training and Dictionary Learning Analysis—0
Improving Neuron-level Interpretability with White-box Language Models—0
Impulse Denoising From Hyper-Spectral Images: A Blind Compressed Sensing Approach—0
Integrating Neural Networks and Dictionary Learning for Multidimensional Clinical Characterizations from Functional Connectomics Data—0
Interpretable Neural Embeddings with Sparse Self-Representation—0
Jitter-Adaptive Dictionary Learning - Application to Multi-Trial Neuroelectric Signals—0
Joint Dictionaries for Zero-Shot Learning—0
Joint Dictionary Learning for Example-based Image Super-resolution—0
Joint DOA Estimation and Array Calibration Using Multiple Parametric Dictionary Learning—0
Joint Learning of Discriminative Low-dimensional Image Representations Based on Dictionary Learning and Two-layer Orthogonal Projections—0
Jointly Learning Non-negative Projection and Dictionary with Discriminative Graph Constraints for Classification—0
Jointly Learning Structured Analysis Discriminative Dictionary and Analysis Multiclass Classifier—0
Joint Projection and Dictionary Learning using Low-rank Regularization and Graph Constraints—0
Joint Representation of Multiple Geometric Priors via a Shape Decomposition Model for Single Monocular 3D Pose Estimation—0
Joint Sensing Matrix and Sparsifying Dictionary Optimization for Tensor Compressive Sensing—0
Joint space-time wind field data extrapolation and uncertainty quantification using nonparametric Bayesian dictionary learning—0
Joint Sparse Representations and Coupled Dictionary Learning in Multi-Source Heterogeneous Image Pseudo-color Fusion—0
Joint Subspace Recovery and Enhanced Locality Driven Robust Flexible Discriminative Dictionary Learning—0
Joint Transceiver Design Based on Dictionary Learning Algorithm for SCMA—0
Kernel Coding: General Formulation and Special Cases—0
Kernelized Supervised Dictionary Learning—0
Kernel Task-Driven Dictionary Learning for Hyperspectral Image Classification—0
Kernel Transform Learning—0
Koopman-Based Methods for EV Climate Dynamics: Comparing eDMD Approaches—0
l0 Norm Based Dictionary Learning by Proximal Methods with Global Convergence—0
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