We initiate the study of incentives in a general machine learning framework. We focus on a game-theoretic regression learning setting where private information is elicited from mu...
Graph-based semi-supervised learning has recently emerged as a promising approach to data-sparse learning problems in natural language processing. All graph-based algorithms rely ...
Learning tasks from a single demonstration presents a significant challenge because the observed sequence is inherently an incomplete representation of the procedure that is speci...
Hyuckchul Jung, James F. Allen, Nathanael Chambers...
Abstract. Studying and analysing the collaborative behaviour of online learning teams and how this behaviour is related and affects task performance is a complex process. This pap...
Thanasis Daradoumis, Fatos Xhafa, Joan Manuel Marq...
We exploit some useful properties of Gaussian process (GP) regression models for reinforcement learning in continuous state spaces and discrete time. We demonstrate how the GP mod...