We consider a natural framework of learning from correlated data, in which successive examples used for learning are generated according to a random walk over the space of possibl...
Ariel Elbaz, Homin K. Lee, Rocco A. Servedio, Andr...
We consider learning in situations where the function used to classify examples may switch back and forth between a small number of different concepts during the course of learnin...
k. The model we study can be interpreted as a broad, abstract extension of the well-studied on-line prediction model to a general decision-theoretic setting. We show that the multi...
Abstract-- In this paper we investigate the effects of individual learning on an evolving population of situated agents. We work with a novel type of system where agents can decide...
Games for learning cannot take the same design approach as games when targeting audiences. While players of entertainment games have the luxury of choosing games that suit them, s...
Brian Magerko, Carrie Heeter, Joe Fitzgerald, Ben ...