Privacy-sensitive federated learning for cross-domain adaptation: The Mamba-MoE approach

Privacy-sensitive federated learning for cross-domain adaptation: The Mamba-MoE approach

Domain adaptation in decentralized environments poses significant challenges, particularly in privacy-sensitive and resource-constrained scenarios. Conventional approaches, such as Domain-Adversarial Neural Networks (DANN) and Maximum Mean Discrepancy (MMD), rely on large datasets and centralized pr...

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Bibliographic Details
Main Authors: Muhammad Kashif Jabbar, Huang Jianjun, Ayesha Jabbar, Zaka Ur Rehman
Format: Article
Language:English
Published: Elsevier 2025-09-01
Series:Results in Engineering
Subjects:
Federated Learning (FL)
Mamba-MoE
MoE
Adaptive routing
Privacy-preserving AI
Feature fusion
Online Access:http://www.sciencedirect.com/science/article/pii/S2590123025025010
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