118 citations · 125 across the 4 of their papers we have counts for
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cs.LG2021★ 2 cited
Developing parsimonious ensembles using predictor diversity within a reinforcement learning framework
Ana Stanescu, Gaurav Pandey
Heterogeneous ensembles that can aggregate an unrestricted number and variety of base predictors can effectively address challenging prediction problems. In particular, accurate en…
cs.LG2018★ 1 cited
Developing parsimonious ensembles using ensemble diversity within a reinforcement learning framework
Ana Stanescu, Gaurav Pandey
Heterogeneous ensembles built from the predictions of a wide variety and large number of diverse base predictors represent a potent approach to building predictive models for probl…
cs.LG2013
A Comparative Analysis of Ensemble Classifiers: Case Studies in Genomics
Sean Whalen, Gaurav Pandey
The combination of multiple classifiers using ensemble methods is increasingly important for making progress in a variety of difficult prediction problems. We present a comparative…