41 citations · 54 across the 3 of their papers we have counts for
3 papers · 1 filter
MCMC-driven learning
Alexandre Bouchard-Côté, Trevor Campbell, Geoff Pleiss +1
This paper is intended to appear as a chapter for the Handbook of Markov Chain Monte Carlo. The goal of this chapter is to unify various problems at the intersection of Markov chai…
An Entropy Search Portfolio for Bayesian Optimization
Bobak Shahriari, Ziyu Wang, Matthew W. Hoffman +2
Bayesian optimization is a sample-efficient method for black-box global optimization. How- ever, the performance of a Bayesian optimization method very much depends on its explorat…
Optimization of Structured Mean Field Objectives
Alexandre Bouchard-Cote, Michael I. Jordan
In intractable, undirected graphical models, an intuitive way of creating structured mean field approximations is to select an acyclic tractable subgraph. We show that the hardness…