CoCoGen+ models each federated learning round as a weighted potential game with strategic synthetic data generation and payoff redistribution incentives, showing improved efficiency over baselines under non-IID data and competition.
Machine intelligence at the edge with learning centric power allocation
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
A robot navigation method jointly optimizes movement, wireless data transmission, and AI model training by using region-specific signal models and a non-point-mass robot representation.
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Cooperate to Compete: Strategic Data Generation and Incentivization Framework for Coopetitive Cross-Silo Federated Learning
CoCoGen+ models each federated learning round as a weighted potential game with strategic synthetic data generation and payoff redistribution incentives, showing improved efficiency over baselines under non-IID data and competition.
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Towards Edge Intelligence via Autonomous Navigation: A Robot-Assisted Data Collection Approach
A robot navigation method jointly optimizes movement, wireless data transmission, and AI model training by using region-specific signal models and a non-point-mass robot representation.