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Differential Privacy in Multi-armed Bandits

Series: Bangalore Theory Seminars

Speaker: Sayak Ray Chowdhury Microsoft Research Bangalore

Date/Time: Aug 18 11:00:00

Location: CSA Seminar Hall (Room No. 254, First Floor)

Abstract:
Differential privacy (DP) has been recently introduced to multi-armed bandits to formally address the privacy concerns in its associated personalized services to participating users (e.g., recommendations). Prior work largely focusses on two trust models of DP ?? the central model, where a central server is responsible for protecting users sensitive data, and the (stronger) local model, where information needs to be protected directly on users side. However, there remains a fundamental gap in the utility achieved by learning algorithms under these two privacy models ?? the regret suffer in the local model is higher than that in the weaker central model.

In this talk, we will focus on a stronger model of trust than the central model, while suffering a smaller regret than the local model by considering recently popular shuffle and distributed model of privacy. We will demonstrate this privacy-regret trade-off for both K-armed bandit problem and linear contextual bandit problem.


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We are grateful to the Kirani family for generously supporting the theory seminar series


Hosts: Rameesh Paul, Rachana Gusain, Rahul Madhavan, KVN Sreenivas