Monte-Carlo methods for some challenging parameter estimation problems: intractable normalizing constants and differential privacy
This dissertation studies two statistical problems: Bayesian inference for network models with intractable normalizing constants and differentially private learning with stochastic neural networks.The first project develops noisy Langevin Monte Carlo for exponential random graph models. Auxiliary network simulations es...