Sciweavers

Share
ICML
2010
IEEE

Boosting for Regression Transfer

9 years 3 months ago
Boosting for Regression Transfer
The goal of transfer learning is to improve the learning of a new target concept given knowledge of related source concept(s). We introduce the first boosting-based algorithms for transfer learning that apply to regression tasks. First, we describe two existing classification transfer algorithms, ExpBoost and TrAdaBoost, and show how they can be modified for regression. We then introduce extensions of these algorithms that improve performance significantly on controlled experiments in a wide range of test domains.
David Pardoe, Peter Stone
Added 09 Nov 2010
Updated 09 Nov 2010
Type Conference
Year 2010
Where ICML
Authors David Pardoe, Peter Stone
Comments (0)
books