35 citations · 79 across the 8 of their papers we have counts for
Showing 2018Show all
3 papers · 1 filter
cs.LG2018
Differentially Private Bayesian Inference for Exponential Families
Garrett Bernstein, Daniel Sheldon
The study of private inference has been sparked by growing concern regarding the analysis of data when it stems from sensitive sources. We present the first method for private Baye…
cs.LG2018
Importance Weighting and Variational Inference
Justin Domke, Daniel Sheldon
Recent work used importance sampling ideas for better variational bounds on likelihoods. We clarify the applicability of these ideas to pure probabilistic inference, by showing the…
stat.ML2018
Learning in Integer Latent Variable Models with Nested Automatic Differentiation
Daniel Sheldon, Kevin Winner, Debora Sujono
We develop nested automatic differentiation (AD) algorithms for exact inference and learning in integer latent variable models. Recently, Winner, Sujono, and Sheldon showed how to…