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AEGIS slashes token recovery rates to nearly zero while preserving model performance, tackling all three critical channels of information leakage in federated learning.
Optimizing coflow scheduling in multi-core optical networks can slash completion times for data-intensive jobs, and this algorithm proves it with real-world Facebook workload traces.
