In this paper, we propose a post randomization technique to learn a Bayesian network (BN) from distributed heterogeneous data, in a privacy sensitive fashion. In this case, two or ...
Virtually all methods of learning dynamic systems from data start from the same basic assumption: the learning algorithm will be given a sequence of data generated from the dynami...
We consider the problem of identifying the consensus ranking for the results of a query, given preferences among those results from a set of individual users. Once consensus ranki...
Paul N. Bennett, David Maxwell Chickering, Anton M...
Abstract. Mining of data streams must balance three evaluation dimensions: accuracy, time and memory. Excellent accuracy on data streams has been obtained with Naive Bayes Hoeffdi...
Albert Bifet, Geoffrey Holmes, Bernhard Pfahringer...
Geographic information has spawned many novel Web applications where global positioning system (GPS) plays important roles in bridging the applications and end users. Learning kno...