A cost-sensitive extension of boosting, denoted as asymmetric boosting, is presented. Unlike previous proposals, the new algorithm is derived from sound decision-theoretic princip...
The Virtual Math Teams (VMT) project investigates the innovative use of online collaborative environments to support effective mathematical problem-solving by small groups of lear...
Boosting constructs a weighted classifier out of possibly weak learners by successively concentrating on those patterns harder to classify. While giving excellent results in many ...
We investigate the role of presence in a serious game for intercultural communication and negotiation skills by comparing two interfaces: a 3D version with animated virtual humans ...
H. Chad Lane, Matthew J. Hays, Daniel Auerbach, Ma...
We describe a novel family of PAC model algorithms for learning linear threshold functions. The new algorithms work by boosting a simple weak learner and exhibit complexity bounds...