Evolutionary multiple instance boosting framework for weakly supervised learning

Abstract Multiple instance boosting (MILBoost) is a framework which uses multiple instance learning (MIL) with boosting technique to solve the problems regarding weakly labeled inexact data. This paper proposes an enhanced multiple boosting framework—evolutionary MILBoost (EMILBoost) which utilizes ... View More