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CEDD-optimizer: Enabling Cost-Efficient Dataset Distillation on Geographically Distributed Edge Systems
Centralized learning is a fundamental paradigm in modern AI, in which data are collected from distributed edge devices and aggregated at a central host for model training. However, this pipeline is often bottlenecked by the substantial communication overhead of data collection. Dataset Distillation
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