arXiv Machine Learning June 10, 2026 By Tudor Pistol

Learning Doubly Sparse Explicitly Conditioned Transforms

Read the original on arXiv Machine Learning →

arXiv:2606. 10975v1 Announce Type: new Abstract: Finding convenient spaces in which certain hypotheses regarding an assumed sparse structure of natural signals hold true has become a desirable result in recent research, its implications being reflected in areas such as data compression, noise reduction and feature extraction.

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arXiv Machine Learning

Jul 16

Multi-Dictionary Learning for Low Rank Sparse Coding

arXiv:2509. 10033v2 Announce Type: replace Abstract: Sparse dictionary coding represents signals as linear combinations of a few dictionary atoms.

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arXiv Machine Learning

Aug 14

Sparse Orthogonal Regression Technique: A Spectral Framework for Equation Discovery, Approximation, and Integration

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By Sabin Roman, Ljupco Todorovski, Saso Dzeroski

arXiv Computer Vision

Aug 24

A Dual-domain Refinement Network with FBP-based Jacobian Learning for Sparse-view Dual-Energy CT Material Decomposition

arXiv:2606.30159v2 Announce Type: replace Abstract: Dual-energy CT (DECT) exploits attenuation differences across different X-ray spectra to provide richer material information and has been widely us...

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A Dual-domain Refinement Network with FBP-based Jacobian Learning for Sparse-view Dual-Energy CT Material Decomposition

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arXiv Machine Learning

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Sparse Weight Decomposition for Efficient Circuit Extraction

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