Epsilon focusing - A strategy for active example selection

Abstract

In most classical formulations of learning from examples, a passive learner is presented with examples randomly drawn. Here we discuss an ∈-focusing strategy that actively chooses examples for concept learning. We describe the local focused property that functions must have for such a strategy to work. Finally, we develop an example selection heuristic, motivated by ∈-focusing, for training a computer vision system to perform a human face detection task. © 1998 Elsevier Science B.V. All rights reserved.