MinMax Sampling: A Near-optimal Global Summary for Aggregation in the Wide Area
Summary: MinMax Sampling enables fast, adaptive WAN-wide aggregation. MinMaxopt achieves optimal accuracy; MinMaxadp trades accuracy for speed/adaptivity, delivering ~8x higher accuracy across federated learning, distributed state, and hierarchical aggregation. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Yikai Zhao
- 2. Yinda Zhang
- 3. Yuanpeng Li
- 4. Yi Zhou
- 5. Chunhui Chen
- 6. Tong Yang
- 7. Bin Cui
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