In this paper we present a novel, customizable IE paradigm that takes advantage of predicate-argument structures. We also introduce a new way of automatically identifying predicat...
Mihai Surdeanu, Sanda M. Harabagiu, John Williams,...
Abstract A dynamic programming algorithm for constructing optimal dyadic decision trees was recently introduced, analyzed, and shown to be very effective for low dimensional data ...
Sparse graphical models have proven to be a flexible class of multivariate probability models for approximating high-dimensional distributions. In this paper, we propose techniques...
Vincent Y. F. Tan, Sujay Sanghavi, John W. Fisher ...
The Gaussian process latent variable model (GP-LVM) is a powerful approach for probabilistic modelling of high dimensional data through dimensional reduction. In this paper we ext...
We introduce a framework, which we call Divide-by-2 (DB2), for extending support vector machines (SVM) to multi-class problems. DB2 offers an alternative to the standard one-again...