FLSys 2020 : Federated Learning Systems: Towards Next-generation AI

Our topics of interest include but not limited to:

• Differential Privacy Techniques
• Latency-minimal Federated Learning Applications
• Bandwidth-Optimization Techniques for Efficient Data Communication
• Local and Global Model Personalization
• Decentralized Model Training
• Fine-grained Federated Learning
• Incentive Mechanisms for Large-scale Data Providers
• Trust Models in Federated Learning Systems
• Reputation Models in Federated Learning Systems
• Active Monitoring for Secure and Quality Model Aggregation
• Heterogeneity-Awareness Across Federated Learning Systems
• Context-Awareness for Data Collection, Model Training, and Aggregation
• Model Compression
• Adaptive Model Aggregation
• Fairness (Algorithmic, Systematic)