We introduce several generalizations of classical computer science problems obtained by replacing simpler objective functions with general submodular functions. The new problems i...
This paper demonstrates how unsupervised techniques can be used to learn models of deep linguistic structure. Determining the semantic roles of a verb's dependents is an impo...
We study graph estimation and density estimation in high dimensions, using a family of density estimators based on forest structured undirected graphical models. For density estim...
Anupam Gupta, John D. Lafferty, Han Liu, Larry A. ...
We present a polynomial update time algorithm for the inductive inference of a large class of context-free languages using the paradigm of positive data and a membership oracle. W...
This paper focuses on the problem of generating coalition structures for task allocation via coalition formation. It provides a unified formal framework for constructing those co...