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Federated Learning as a Network Effects Game
Federated Learning (FL) aims to foster collaboration among a population of clients to improve the accuracy of machine learning without directly sharing local data.
Incentivizing Combinatorial Bandit Exploration
The users are free to choose other actions and need to be incentivized to follow the algorithm's recommendations.
Improved Regret for Differentially Private Exploration in Linear MDP
We study privacy-preserving exploration in sequential decision-making for environments that rely on sensitive data such as medical records.
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