most citedDeveloping parsimonious ensembles using predictor diversity within a reinforcement learning framework

2 citations · 2 across the 1 of their papers we have counts for

collaborators

2 papers

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

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…