Engagement Detection on EngageNet 2023 (test)
0.66F1 (weighted)FedProx
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| FedProxLearning Setting=Federated, Model=bi-LSTM2026.02 | 0.66 | 0.66 | 0.703 | |
| FedAdamLearning Setting=Federated, Model=bi-LSTM2026.02 | 0.65 | 0.662 | 0.688 | |
| non-FL bagging bootstrapLearning Setting=Non-Federated, Model=Bagging Bootstrap2026.02 | 0.642 | 0.674 | 0.7 | |
| FedAvgLearning Setting=Federated, Model=bi-LSTM2026.02 | 0.641 | 0.638 | 0.694 | |
| TurboSVMLearning Setting=Federated, Model=bi-LSTM2026.02 | 0.634 | 0.642 | 0.666 | |
| FedAwSLearning Setting=Federated, Model=bi-LSTM2026.02 | 0.633 | 0.637 | 0.707 | |
| non-FL bi-LSTMLearning Setting=Non-Federated, Model=bi-LSTM2026.02 | 0.615 | 0.633 | 0.7 | |
| MOONLearning Setting=Federated, Model=bi-LSTM2026.02 | 0.595 | 0.602 | 0.68 |