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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 101–125 of 823 papers

TitleStatusHype
Improving Language Models Trained on Translated Data with Continual Pre-Training and Dictionary Learning Analysis—0
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
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
Parametric PDE Control with Deep Reinforcement Learning and Differentiable L0-Sparse Polynomial PoliciesCode0
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
Interpretable Online Network Dictionary Learning for Inferring Long-Range Chromatin InteractionsCode0
Convergence and complexity of block majorization-minimization for constrained block-Riemannian optimization—0
Learning Interpretable Queries for Explainable Image Classification with Information Pursuit—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
Riemannian stochastic optimization methods avoid strict saddle points—0
A Strictly Bounded Deep Network for Unpaired Cyclic Translation of Medical Images—0
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