We present a discriminative method for learning selectional preferences from unlabeled text. Positive examples are taken from observed predicate-argument pairs, while negatives ar...
We study the problem of learning regular tree languages from text. We show that the framework of function distinguishability as introduced by the author in Theoretical Computer Sc...
A critical problem in developing information agents for the Web is accessing data that is formatted for human use. We have developed a set of tools for extracting data from web si...
Craig A. Knoblock, Kristina Lerman, Steven Minton,...
Due to the increased speed in modern designs, testing for delay faults has become an important issue in the postproduction test of manufactured chips. A high fault coverage is nee...
In this paper, we present a novel framework for asynchronous Web-based training. The proposed system has two distinguishing features. Firstly, it is based on P2P architecture for ...