Matches in SemOpenAlex for { <https://semopenalex.org/work/W3097795114> ?p ?o ?g. }
- W3097795114 abstract "Various differentially private algorithms instantiate the exponential mechanism, and require sampling from the distribution $exp(-f)$ for a suitable function $f$. When the domain of the distribution is high-dimensional, this sampling can be computationally challenging. Using heuristic sampling schemes such as Gibbs sampling does not necessarily lead to provable privacy. When $f$ is convex, techniques from log-concave sampling lead to polynomial-time algorithms, albeit with large polynomials. Langevin dynamics-based algorithms offer much faster alternatives under some distance measures such as statistical distance. In this work, we establish rapid convergence for these algorithms under distance measures more suitable for differential privacy. For smooth, strongly-convex $f$, we give the first results proving convergence in Renyi divergence. This gives us fast differentially private algorithms for such $f$. Our techniques and simple and generic and apply also to underdamped Langevin dynamics." @default.
- W3097795114 created "2020-11-09" @default.
- W3097795114 creator A5080065269 @default.
- W3097795114 creator A5089993465 @default.
- W3097795114 date "2020-10-27" @default.
- W3097795114 modified "2023-09-27" @default.
- W3097795114 title "Faster Differentially Private Samplers via R'enyi Divergence Analysis of Discretized Langevin MCMC" @default.
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