In this paper, we propose a new semi-supervised training method for Gaussian Mixture Models. We add a conditional entropy minimizer to the maximum mutual information criteria, whi...
Visual search is an important part of human-computer interaction. It is critical that we build theory about how people visually search displays in order to better support the user...
We combine two complementary ideas for learning supertaggers from highly ambiguous lexicons: grammar-informed tag transitions and models minimized via integer programming. Each st...
Hidden Markov Models (HMMs) are an useful and widely utilized approach to the modeling of data sequences. One of the problems related to this technique is finding the optimal stru...
The recent availability of large collections of text such as the Google 1T 5-gram corpus (Brants and Franz, 2006) and the Gigaword corpus of newswire (Graff, 2003) have made it po...