Fed-TTC: A Pareto-Efficient Hierarchical Federated Learning Framework

Keyphrases

• Hierarchical Federated Learning 100%
• Pareto Efficiency 100%
• Federated Learning Framework 100%
• Strategy-proofness 100%
• Top Trading Cycles 100%
• Deferred Acceptance 66%
• Server Assignment 66%
• Hierarchical FL 66%
• Immediate Acceptance 66%
• Pareto Strategy 66%
• One-round 66%
• Model Accuracy 33%
• Federated Learning 33%
• Blockchain 33%
• Privacy-preserving 33%
• Scalability Issues 33%
• Assignment Problem 33%
• Heuristic-based 33%
• Matching Mechanism 33%
• Smart Contract 33%
• CIFAR-10 33%
• Assignment Strategy 33%
• Client Selection 33%
• Assignment Mechanism 33%
• Final Model 33%
• FedProx 33%
• Non-IID 33%
• Transformative Paradigm 33%
• Doctoral Studies 33%
• Distributed Data Aggregation 33%
• Design Drawings 33%
• Collaborative Machine Learning 33%
• Shapley Value Method 33%
• Contribution Assessment 33%
• Trustless 33%
• Statistical Heterogeneity 33%
• Market Design 33%
• Client Contribution 33%
• Top Trading Cycles Algorithm 33%
• Priority Ranking 33%
• School Choice Problem 33%
• Top Trading Cycles Mechanism 33%
• Multi-server Federated Learning 33%
• Key Matching 33%
• Server Architecture 33%
• Multi-server Architecture 33%

Computer Science

• Learning Framework 100%
• Federated machine learning 100%
• Pareto-optimality 50%
• Client Server 50%
• Server Assignment 50%
• Server Architecture 50%
• Machine Learning 25%
• Learning System 25%
• Approximation (Algorithm) 25%
• Model Accuracy 25%
• Blockchain 25%
• Privacy Preserving 25%
• Assignment Problem 25%
• Smart Contract 25%
• Collaboration 25%