Most recent research of scalable inductive learning on very large dataset, decision tree construction in particular, focuses on eliminating memory constraints and reducing the num...
Our goal is to identify the features that predict the occurrence and placement of discourse cues in tutorial explanations in order to aid in the automatic generation of explanatio...
Barbara Di Eugenio, Johanna D. Moore, Massimo Paol...
Recent years have seen a significant increase in our understanding of high-dimensional nearest neighbor search (NNS) for distances like the 1 and 2 norms. By contrast, our underst...
In this article, we propose a special type of decision tree, called a decision cascade, for binarizing document images. Such images are produced by cameras, resulting in varying de...
We develop the theory of regular cost functions over finite trees: a quantitative extension to the notion of regular languages of trees: Cost functions map each input (tree) to a v...