Naive Bayes models have been widely used for clustering and classification. However, they are seldom used for general probabilistic learning and inference (i.e., for estimating an...
We present a method for constructing ensembles from libraries of thousands of models. Model libraries are generated using different learning algorithms and parameter settings. For...
Rich Caruana, Alexandru Niculescu-Mizil, Geoff Cre...
: Current learning modelling languages do not allow formalization of scripts where generic tools are required. This limitation is especially relevant on remote courses when using c...
We present a discriminative method for learning selectional preferences from unlabeled text. Positive examples are taken from observed predicate-argument pairs, while negatives ar...
Author identification models fall into two major categories according to the way they handle the training texts: profile-based models produce one representation per author while in...