Learning to converge to an efficient, i.e., Pareto-optimal Nash equilibrium of the repeated game is an open problem in multiagent learning. Our goal is to facilitate the learning ...
This paper shows how to formally characterize language learning in a finite parameter space as a Markov structure, hnportant new language learning results follow directly: explici...
Active and semi-supervised learning are important techniques when labeled data are scarce. Recently a method was suggested for combining active learning with a semi-supervised lea...
In many data mining applications, online labeling feedback is only available for examples which were predicted to belong to the positive class. Such applications include spam filt...
Abstract a paradigm of modern Machine Learning (ML) which uses rewards and punishments to guide the learning process. One of the central ideas of RL is learning by “direct-online...