Full Papers
Original research contributions with complete methodology, experiments, and analysis.
Machine Learning/CORE Unranked
FedKDD/FedMAS 2026
FedKDD/FedMAS 2026: The 2026 International Joint Workshop on Federated Learning for Multi-agent Systems and Data Mining
FedKDD/FedMAS 2026 is a joint conference focusing on federated learning, privacy-preserving data mining, and multi-agent systems. It brings together researchers and practitioners to present and discuss cutting-edge advancements in decentralized machine learning and collaborative AI systems.
Paper fit
Contribution paths
A strong submission should clearly identify its contribution and evaluate it appropriately.
Short Papers
Concise presentations of early-stage work, position papers, or system demos.
Journal Track
Extended versions of previously published work suitable for journal submission.
Research areas in scope
01
FedKDD Topics
Federated learning algorithmsPrivacy-preserving data miningFederated transfer learningFederated reinforcement learningFederated optimizationFederated model aggregationFederated data augmentationFederated anomaly detectionFederated recommendation systemsFederated learning for healthcareFederated learning for IoTFederated learning for edge computingFederated learning for financeFederated learning for smart citiesFederated learning for natural language processingFederated learning for computer vision
02
FedMAS Topics
Multi-agent systems for federated learningCoordination and communication in federated multi-agent systemsDistributed decision-makingMulti-agent reinforcement learningFederated agent collaborationHeterogeneous agent learningFederated multi-agent optimizationFederated multi-agent negotiationFederated multi-agent resource allocationFederated multi-agent privacyFederated multi-agent securityFederated multi-agent trust and reputationFederated multi-agent learning from human feedbackFederated multi-agent simulation environments
Policies worth checking twice
- Submissions must be anonymized for double-blind review.
- Full papers are limited to 10 pages, short papers to 6 pages, excluding references.
- Dual submission to other conferences or journals is not allowed.
- Author lists and affiliations cannot be changed after the submission deadline.
- All submissions must include a statement on the use of AI-assisted tools in the research process.
Official sources
Compiled from the official call for papers. The organizers’ pages remain authoritative.
Last verified September 9, 2026