In this paper, we present a general machine learning approach to the problem of deciding when to share probabilistic beliefs between agents for distributed monitoring. Our approac...
—Structure learning is a crucial component of a multivariate Estimation of Distribution algorithm. It is the part which determines the interactions between variables in the proba...
Alexander E. I. Brownlee, John A. W. McCall, Siddh...
Abstract: We study the average-case learnability of DNF formulas in the model of learning from uniformly distributed random examples. We define a natural model of random monotone ...
This paper reports on a UK ESRC-funded project studying representations of practice, in video clips and voice annotations, for professional collaborative learning in distributed o...
: This paper presents the modular training system MTS, the PLATINUM1 -Net, a worldwide network for innovative learning and advanced training, and distributed collaborative training...