Privacy-Aware Collaborative and Distributed Bayesian Optimization
Aditya Rane, Sathwik Yamana, Paritosh Ramanan, Srikanthan Ramesh, Akash Deep
cs.LG stat.ME
Abstract
We propose a collaborative meta-learning framework for distributed Bayesian optimization matching centralized performance without raw-data exchange. We show gradient sharing leaks client observations, with leakage worsening as the search converges and queries concentrate near the optimum. We evaluate a differentially private defense and characterize its privacy-utility trade-off.
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Classified with taxonomy v2 on Wed, 2 Sept 2026.