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MLAE: Masked LoRA Experts for Parameter-Efficient Fine-Tuning
To address these issues, a natural idea is to enhance the independence and diversity of the learning process for the low-rank matrices.
FedCompetitors: Harmonious Collaboration in Federated Learning with Competing Participants
Federated learning (FL) provides a privacy-preserving approach for collaborative training of machine learning models.
MarS-FL: Enabling Competitors to Collaborate in Federated Learning
A key unaddressed scenario is that these FL participants are in a competitive market, where market shares represent their competitiveness.
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