We address a new learning problem where the goal is to build a predictive model that minimizes prediction time (the time taken to make a prediction) subject to a constraint on mod...
Biswanath Panda, Mirek Riedewald, Johannes Gehrke,...
In this paper, we address the problem of semisupervision in the framework of parametric clustering by using labeled and unlabeled data together. Clustering algorithms can take adv...
Modern classification applications necessitate supplementing the few available labeled examples with unlabeled examples to improve classification performance. We present a new tra...
As system integration evolves and tighter design constraints must be met, it becomes necessary to account for the non-ideal behavior of all the elements in a system. Certain devic...
Carlos P. Coelho, Joel R. Phillips, Luis Miguel Si...
We introduce a temporal model for reasoning on disjunctive metric constraints on intervals and time points in temporal contexts. This temporal model is composed of a labeled tempo...