6 citations · 6 across the 2 of their papers we have counts for
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Quantitative Error Bounds for Scaling Limits of Stochastic Iterative Algorithms
Xiaoyu Wang, Mikolaj J. Kasprzak, Jeffrey Negrea +2
Stochastic iterative algorithms, including stochastic gradient descent (SGD) and stochastic gradient Langevin dynamics (SGLD), are widely utilized for optimization and sampling in…
A Targeted Accuracy Diagnostic for Variational Approximations
Yu Wang, Mikołaj Kasprzak, Jonathan H. Huggins
Variational Inference (VI) is an attractive alternative to Markov Chain Monte Carlo (MCMC) due to its computational efficiency in the case of large datasets and/or complex models w…
Detailed Derivations of Small-Variance Asymptotics for some Hierarchical Bayesian Nonparametric Models
Jonathan H. Huggins, Ardavan Saeedi, Matthew J. Johnson
In this note we provide detailed derivations of two versions of small-variance asymptotics for hierarchical Dirichlet process (HDP) mixture models and the HDP hidden Markov model (…