BICompFL applies minimal random coding to both uplink and downlink in stochastic federated learning, cutting measured communication cost by 5-32x on MNIST, Fashion-MNIST, and CIFAR-10.
QSGD : Communication-efficient SGD via gradient quantization and encoding
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BICompFL: Stochastic Federated Learning with Bi-Directional Compression
BICompFL applies minimal random coding to both uplink and downlink in stochastic federated learning, cutting measured communication cost by 5-32x on MNIST, Fashion-MNIST, and CIFAR-10.