Towards understanding sparse filtering: a theoretical perspective

DOI10.1016/j.neunet.2017.11.010zbMath1434.68483arXiv1603.08831OpenAlexW2328604275WikidataQ47323844 ScholiaQ47323844MaRDI QIDQ2179299

Fabio M. Zennaro, Ke Chen

Publication date: 12 May 2020

Published in: Neural Networks (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1603.08831

zbMATH Keywords

soft clusteringinformation preservationcosine metricfeature distribution learningintrinsic structuresparse filtering

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Related Items

Sparse filtering under bounded exogenous disturbances

Uses Software

• PDCO
• darch
• CIFAR
• PRMLT

Cites Work

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• Information geometry and its applications
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• $rm K$-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation
• Matching pursuits with time-frequency dictionaries
• Comparing Measures of Sparsity
• Information Theoretic Learning
• A Fast Learning Algorithm for Deep Belief Nets