Chun-Sheng Chen

Chun-Sheng Chen
Research Scientist

Chun-Sheng Chen, PhD, studied machine learning at the University of Houston. His research in time series sampling for predictive classifiers led to applications that more quickly and accurately predict air pollution in large cities.  Chun-Sheng leads the development of eBay's "bad buying experience" prediction models.

2015 International Conference for Machine Learning (ICML)

Bayesian and Empirical Bayesian Forests

Matt Taddy, Chun-Sheng Chen, Jun Yu, Mitch Wyle

We derive ensembles of decision trees through a nonparametric Bayesian model, allowing us to view random forests as samples from a posterior distribution. This insight provides large gains in interpretability, and motivates a class of Bayesian forest (BF) algorithms that yield small but reliable performance gains.

Based on the BF framework, we are able to show that high-level tree hierarchy is stable in large samples. This leads to an empirical Bayesian forest (EBF) algorithm for building approximate BFs on massive distributed datasets and we show that EBFs outperform subsampling based alternatives by a large margin.