Image Classification on MNIST (test) (Performance by Client Class Count)
99.05Acc (3 Classes/Client)QuPeD
Evaluation Results
| Method | Links | ||
|---|---|---|---|
| QuPeDPrecision=FP, Backbone=CNN12021.07 | 99.05 | 98.89 | |
| Federated MLPrecision=FP, Backbone=CNN12021.07 | 99 | 98.84 | |
| pFedMePrecision=FP, Backbone=CNN12021.07 | 98.98 | 98.82 | |
| QuPeDPrecision=2 Bits, Backbone=CNN12021.07 | 98.96 | 98.67 | |
| QuPeLPrecision=2 Bits, Backbone=CNN12021.07 | 98.95 | 98.61 | |
| Per-FedAvgPrecision=FP, Backbone=CNN12021.07 | 98.82 | 98.93 | |
| Local TrainingPrecision=FP, Backbone=CNN12021.07 | 98.79 | 98.66 | |
| FedAvgPrecision=FP, Backbone=CNN12021.07 | 98.64 | 98.65 | |
| QuPeDPrecision=1 Bit, Backbone=CNN12021.07 | 98.57 | 98.25 | |
| Local TrainingPrecision=2 Bits, Backbone=CNN12021.07 | 98.53 | 98.37 | |
| Local TrainingPrecision=1 Bit, Backbone=CNN12021.07 | 98.41 | 97.95 | |
| QuPeLPrecision=1 Bit, Backbone=CNN12021.07 | 98.33 | 98.11 |