Fairness and Privacy Guarantees in Federated Contextual Bandits

no code implementations • 5 Feb 2024 • Sambhav Solanki, Shweta Jain, Sujit Gujar

We design a novel communication protocol that allows for (i) Sub-linear theoretical bounds on fairness regret for Fed-FairX-LinUCB and comparable bounds for the private counterpart, Priv-FairX-LinUCB (relative to single-agent learning), (ii) Effective use of privacy budget in Priv-FairX-LinUCB.

Fairness Federated Learning +1

Differentially Private Federated Combinatorial Bandits with Constraints

no code implementations • 27 Jun 2022 • Sambhav Solanki, Samhita Kanaparthy, Sankarshan Damle, Sujit Gujar

There is a rapid increase in the cooperative learning paradigm in online learning settings, i. e., federated learning (FL).

Federated Learning Privacy Preserving