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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 76–100 of 823 papers

TitleStatusHype
Parametric PDE Control with Deep Reinforcement Learning and Differentiable L0-Sparse Polynomial PoliciesCode0
SINDy-RL: Interpretable and Efficient Model-Based Reinforcement LearningCode2
Dictionary Learning Improves Patch-Free Circuit Discovery in Mechanistic Interpretability: A Case Study on Othello-GPT—0
A Lightweight Randomized Nonlinear Dictionary Learning Method using Random Vector Functional Link—0
Seismic Traveltime Tomography with Label-free LearningCode0
Learning a Gaussian Mixture for Sparsity Regularization in Inverse Problems—0
Learning Interpretable Queries for Explainable Image Classification with Information Pursuit—0
Interpretable Online Network Dictionary Learning for Inferring Long-Range Chromatin InteractionsCode0
Convergence and complexity of block majorization-minimization for constrained block-Riemannian optimization—0
Explainable Trajectory Representation through Dictionary Learning—0
Clustering Inductive Biases with Unrolled Networks—0
SenseAI: Real-Time Inpainting for Electron Microscopy—0
Orthogonally weighted _2,1 regularization for rank-aware joint sparse recovery: algorithm and analysisCode0
Level Set KSVD—0
A Strictly Bounded Deep Network for Unpaired Cyclic Translation of Medical Images—0
Riemannian stochastic optimization methods avoid strict saddle points—0
SC-MIL: Sparsely Coded Multiple Instance Learning for Whole Slide Image ClassificationCode1
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 Model Processing Strategies with Non-Negative Per-Example Fisher Factorization—0
Uncovering hidden geometry in Transformers via disentangling position and contextCode0
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
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