8 citations · 13 across the 6 of their papers we have counts for
Showing 2015 · stat.MLShow all
2 papers · 2 filters
stat.ML2015★ 8 cited
Functional Frank-Wolfe Boosting for General Loss Functions
Chu Wang, Yingfei Wang, Weinan E +1
Boosting is a generic learning method for classification and regression. Yet, as the number of base hypotheses becomes larger, boosting can lead to a deterioration of test performa…
stat.ML2015★ 1 cited
The Knowledge Gradient with Logistic Belief Models for Binary Classification
Yingfei Wang, Chu Wang, Warren Powell
We consider sequential decision making problems for binary classification scenario in which the learner takes an active role in repeatedly selecting samples from the action pool an…