| GLASU: A Communication-Efficient Algorithm for Federated Learning with Vertically Distributed Graph Data | Mar 16, 2023 | Federated LearningGraph Neural Network | CodeCode Available | 0 |
| A Survey on Contribution Evaluation in Vertical Federated Learning | May 3, 2024 | Federated LearningSurvey | CodeCode Available | 0 |
| Feature Reconstruction Attacks and Countermeasures of DNN training in Vertical Federated Learning | Oct 13, 2022 | Federated LearningReconstruction Attack | CodeCode Available | 0 |
| Achieving Model Fairness in Vertical Federated Learning | Sep 17, 2021 | BIG-bench Machine LearningFairness | CodeCode Available | 0 |
| A Framework for Evaluating Privacy-Utility Trade-off in Vertical Federated Learning | Sep 8, 2022 | Federated LearningPrivacy Preserving | CodeCode Available | 0 |
| Vertical Federated Learning with Missing Features During Training and Inference | Oct 29, 2024 | Federated LearningVertical Federated Learning | CodeCode Available | 0 |
| Constructing Adversarial Examples for Vertical Federated Learning: Optimal Client Corruption through Multi-Armed Bandit | Aug 8, 2024 | Federated LearningThompson Sampling | CodeCode Available | 0 |
| Coresets for Vertical Federated Learning: Regularized Linear Regression and K-Means Clustering | Oct 26, 2022 | ClusteringFederated Learning | CodeCode Available | 0 |
| Communication-efficient Vertical Federated Learning via Compressed Error Feedback | Jun 20, 2024 | Federated LearningVertical Federated Learning | CodeCode Available | 0 |
| Improving Privacy-Preserving Vertical Federated Learning by Efficient Communication with ADMM | Jul 20, 2022 | DenoisingFederated Learning | CodeCode Available | 0 |
