Label ranking is the task of inferring a total order over a predefined set of labels for each given instance. We present a general framework for batch learning of label ranking f...
In studying image quality and image preference it is necessary to collect psychophysical data. A variety of methods are used to arrive at interval scale values which indicate the ...
Abstract. Learning ranking functions is crucial for solving many problems, ranging from document retrieval to building recommendation systems based on an individual user’s prefer...
Evaluating rankers using implicit feedback, such as clicks on documents in a result list, is an increasingly popular alternative to traditional evaluation methods based on explici...
While clustering is usually an unsupervised operation, there are circumstances in which we believe (with varying degrees of certainty) that items A and B should be assigned to the...