Humans Learn Using Manifolds, Reluctantly

no code implementations • NeurIPS 2010 • Tim Rogers, Chuck Kalish, Joseph Harrison, Jerry Zhu, Bryan R. Gibson

When the distribution of unlabeled data in feature space lies along a manifold, the information it provides may be used by a learner to assist classification in a semi-supervised setting.

BIG-bench Machine Learning General Classification

Human Rademacher Complexity

no code implementations • NeurIPS 2009 • Jerry Zhu, Bryan R. Gibson, Timothy T. Rogers

We propose to use Rademacher complexity, originally developed in computational learning theory, as a measure of human learning capacity.

Generalization Bounds Learning Theory