Many modern natural language-processing applications utilize search engines to locate large numbers of Web documents or to compute statistics over the Web corpus. Yet Web search e...
—One common approach to active learning is to iteratively train a single classifier by choosing data points based on its uncertainty, but it is nontrivial to design uncertainty ...
In this paper we present a variational Bayes (VB) framework for learning continuous hidden Markov models (CHMMs), and we examine the VB framework within active learning. Unlike a ...
In an environment of distributed text collections, the first step in the information retrieval process is to identify which of all available collections are more relevant to a giv...
We apply a new active learning formulation to the problem of learning medical concepts from unstructured text. The new formulation is based on maximizing the mutual information th...