Derives tractable optimal fair multi-class classifier and supplies in-processing and post-processing algorithms that converge to the accuracy-fairness Pareto frontier.
Federated learning of a mixture of global and local models,
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
pFedCKKS derives CKKS parameter constraints for PFL under 128-bit security reducing choices to inner and outer ciphertext primes and evaluates precision-cost trade-offs on FEMNIST, CelebA and Sentiment140.
citing papers explorer
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Exploring CKKS Parameter Trade-offs for Privacy-Preserving Personalized Federated Learning
pFedCKKS derives CKKS parameter constraints for PFL under 128-bit security reducing choices to inner and outer ciphertext primes and evaluates precision-cost trade-offs on FEMNIST, CelebA and Sentiment140.