6 citations · 6 across the 3 of their papers we have counts for
3 papers
Alpha-Trimming: Locally Adaptive Tree Pruning for Random Forests
Nikola Surjanovic, Andrew Henrey, Thomas M. Loughin
We demonstrate that adaptively controlling the size of individual regression trees in a random forest can improve predictive performance, contrary to the conventional wisdom that t…
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…
Pigeons.jl: Distributed Sampling From Intractable Distributions
Nikola Surjanovic, Miguel Biron-Lattes, Paul Tiede +3
We introduce a software package, Pigeons.jl, that provides a way to leverage distributed computation to obtain samples from complicated probability distributions, such as multimoda…