基于双向自举蒸馏的异质云-端医疗对话联邦

刘宇鹏,林明豪,张江,姚登举

Heterogeneous cloud-end medical dialogue federation based on bi-directional bootstrapping distillation

Yupeng LIU,Minghao LIN,Jiang ZHANG,Dengju YAO

表 1 不同联邦学习方法在2个数据集上的性能比较

Tab.1 Performance comparison of different federated leaning methods in two datasets

方法 ReMeDi MedDG BLEU-1 BLEU-4 ROGUE-1 ROGUE-2 Distinct-1 Distinct-2 BLEU-1 BLEU-4 ROGUE-1 ROGUE-2 Distinct-1 Distinct-2 中心化训练 27.86 6.59 50.36 32.25 0.72 8.59 30.47 14.21 53.97 35.73 0.87 10.92 FedAvg 18.37 4.83 38.64 22.45 0.50 5.32 19.89 9.62 39.71 25.87 0.58 7.06 FedMD 21.41 5.79 41.92 26.93 0.63 7.54 23.74 11.84 43.76 30.21 0.63 9.14 FedDF 21.68 5.46 40.45 26.64 0.62 8.06 24.26 11.03 43.89 29.51 0.77 9.25 FedGen 24.08 6.38 42.64 27.68 0.65 7.92 26.10 13.05 46.17 32.04 0.69 9.87 FedBiD 25.01 6.32 45.76 28.19 0.68 8.32 26.75 13.16 46.83 31.63 0.78 9.98