Double-bootstrapping source data selection for instance-based transfer learning
We propose a new method for instance-based transfer learning. It uses double bootstrapping to select source data helpful for transfer. It can handle a wider range of transfer scenarios than TrBagg and TrBoost. It shows much less negative transfer than TrBagg and TrBoost. It improves learning through transfer more than TrBagg and TrBoost.
source data selection instance-based transfer learning transfer learning bagging