Boosting Fairness and Robustness in Over-the-Air Federated Learning: Conclusion and References
27 Oct 2024
This paper presents a federated learning algorithm using Over-the-Air computation for fairness and robustness, optimizing performance in decentralized networks.
Boosting Fairness and Robustness in Over-the-Air Federated Learning: Numerical Example
27 Oct 2024
This paper presents a federated learning algorithm using Over-the-Air computation for fairness and robustness, optimizing performance in decentralized networks.
Boosting Fairness and Robustness in Over-the-Air Federated Learning: Convergence Properties
27 Oct 2024
This paper presents a federated learning algorithm using Over-the-Air computation for fairness and robustness, optimizing performance in decentralized networks.
Boosting Fairness and Robustness in Over-the-Air Federated Learning: FedAir Algorithm
27 Oct 2024
This paper presents a federated learning algorithm using Over-the-Air computation for fairness and robustness, optimizing performance in decentralized networks.
Boosting Fairness and Robustness in Over-the-Air Federated Learning: Problem Setup
27 Oct 2024
This paper presents a federated learning algorithm using Over-the-Air computation for fairness and robustness, optimizing performance in decentralized networks.
Boosting Fairness and Robustness in Over-the-Air Federated Learning: Abstract and Introduction
27 Oct 2024
This paper presents a federated learning algorithm using Over-the-Air computation for fairness and robustness, optimizing performance in decentralized networks.
Extending GNN Learning: 11 Additional Framework Applications
22 Oct 2024
Discover a framework that enhances GNN learning, enabling fair k-shot learning and fairness constraint for equitable predictive performance in structural groups
Comprehensive Overview of GNN Experiments: Hardware, Hyperparameters, and Findings
22 Oct 2024
This appendix details the experimental setup, hardware, hyperparameters, and additional results confirming GNN performance and findings across datasets.
Optimizing GNNs: A Sampling-Based Solution to the k-Center Problem
22 Oct 2024
Modified greedy and sampling algorithms solve Eq. (6) in GNNs for the k-center problem, with a running time complexity of O(k) and O(kn) respectively.