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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 126–150 of 823 papers

TitleStatusHype
Sketching Algorithms for Sparse Dictionary Learning: PTAS and Turnstile Streaming—0
MRI brain tumor segmentation using informative feature vectors and kernel dictionary learning—0
Joint Sparse Representations and Coupled Dictionary Learning in Multi-Source Heterogeneous Image Pseudo-color Fusion—0
Enhancing Predictive Capabilities in Data-Driven Dynamical Modeling with Automatic Differentiation: Koopman and Neural ODE Approaches—0
Uncovering hidden geometry in Transformers via disentangling position and contextCode0
Uncovering Model Processing Strategies with Non-Negative Per-Example Fisher Factorization—0
Unsupervised Complex Semi-Binary Matrix Factorization for Activation Sequence Recovery of Quasi-Stationary Sources—0
Wave-informed dictionary learning for high-resolution imaging in complex media—0
Global Identifiability of _1-based Dictionary Learning via Matrix Volume Optimization—0
Global Identifiability of _1-based Dictionary Learning via Matrix Volume Optimization—0
Multi-Source Domain Adaptation meets Dataset Distillation through Dataset Dictionary Learning—0
Federated Dataset Dictionary Learning for Multi-Source Domain Adaptation—0
Bayesian sparsity and class sparsity priors for dictionary learning and coding—0
Optimal Projections for Discriminative Dictionary Learning using the JL-lemmaCode0
Sparse Models for Machine Learning—0
Quantitative MR Image Reconstruction using Parameter-Specific Dictionary Learning with Adaptive Dictionary-Size and Sparsity-Level Choice—0
Exploring the Effect of Sparse Recovery on the Quality of Image Superresolution—0
On the Transition from Neural Representation to Symbolic Knowledge—0
The Decimation Scheme for Symmetric Matrix Factorization—0
Learning a Common Dictionary for CSI Feedback in FDD Massive MU-MIMO-OFDM Systems—0
Multi-Source Domain Adaptation through Dataset Dictionary Learning in Wasserstein SpaceCode0
Anomaly Detection with Selective Dictionary LearningCode0
Classification with Incoherent Kernel Dictionary LearningCode0
Reduced Kernel Dictionary LearningCode0
Subsampling Methods for Fast Electron Backscattered Diffraction Analysis—0
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