Private Stochastic Convex Optimization: Efficient Algorithms for Non-smooth Objectives

22 Feb 2020 Raman Arora Teodor V. Marinov Enayat Ullah

In this paper, we revisit the problem of private stochastic convex optimization. We propose an algorithm based on noisy mirror descent, which achieves optimal rates both in terms of statistical complexity and number of queries to a first-order stochastic oracle in the regime when the privacy parameter is inversely proportional to the number of samples...

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