A two-branch symmetric domain adaptation neural network based on Ulam stability theory

DOI10.1016/j.ins.2023.01.096OpenAlexW4317929775MaRDI QIDQ6127140

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Publication date: 10 April 2024

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ins.2023.01.096

zbMATH Keywords

Ulam stabilityfeature fusionunsupervised domain adaptationgeneralized autoencodertwo-branch architecture

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Computing methodologies for image processing (68U10) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08) Systems of functional equations and inequalities (39B72)

Cites Work

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• On the Hyers-Ulam stability of the functional equations that have the quadratic property
• The Barron space and the flow-induced function spaces for neural network models
• Unsupervised Multi-Target Domain Adaptation: An Information Theoretic Approach
• On the Stability of the Linear Functional Equation