28 citations · 28 across the 1 of their papers we have counts for
2 papers
stat.ML2016
Pruning Random Forests for Prediction on a Budget
Feng Nan, Joseph Wang, Venkatesh Saligrama
We propose to prune a random forest (RF) for resource-constrained prediction. We first construct a RF and then prune it to optimize expected feature cost & accuracy. We pose prunin…
stat.ML2015★ 28 cited
Feature-Budgeted Random Forest
Feng Nan, Joseph Wang, Venkatesh Saligrama
We seek decision rules for prediction-time cost reduction, where complete data is available for training, but during prediction-time, each feature can only be acquired for an addit…