Learning Bayesian network structure from large-scale data sets, without any expertspecified ordering of variables, remains a difficult problem. We propose systematic improvements ...
Past empirical work has shown that learning multiple related tasks from data simultaneously can be advantageous in terms of predictive performance relative to learning these tasks...
The rapid e-commerce growth has made both business community and customers face a new situation. Due to intense competition on the one hand and the customer's option to choose...
Abstract. We develop a practical, distributed algorithm to detect events, identify measurement errors, and infer missing readings in ecological applications of wireless sensor netw...
This paper argues that proactive behaviour, caused by high engagement and motivation of the learners, may lead to failure of collaborative learning. By examining empirical data fr...