BACE-Pipe is a bandwidth-aware and cost-efficient pipeline scheduling framework for geo-distributed LLM training that reduces average JCT by 27.9-64.7% and electricity cost by 12.6-30.6% in simulations versus baselines.
Fedimpro: Measuring and improv- ing client update in federated learning.arXiv preprint arXiv:2402.07011
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FedHD is a federated learning framework for whole slide images that distills one-to-one synthetic features aligned via Gaussian mixtures and progressively integrates cross-site features through curriculum learning to handle institutional heterogeneity.
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Bandwidth-Aware and Cost-Efficient Pipeline Parallel Scheduling in Geo-Distributed LLM Training
BACE-Pipe is a bandwidth-aware and cost-efficient pipeline scheduling framework for geo-distributed LLM training that reduces average JCT by 27.9-64.7% and electricity cost by 12.6-30.6% in simulations versus baselines.
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Federated Distillation for Whole Slide Image via Gaussian-Mixture Feature Alignment and Curriculum Integration
FedHD is a federated learning framework for whole slide images that distills one-to-one synthetic features aligned via Gaussian mixtures and progressively integrates cross-site features through curriculum learning to handle institutional heterogeneity.