The application of statistical methods to natural language processing has been remarkably successful over the past two decades. But, to deal with recent problems arising in this ...
In this paper we propose a new information-theoretic divisive algorithm for word clustering applied to text classification. In previous work, such "distributional clustering&...
Inderjit S. Dhillon, Subramanyam Mallela, Rahul Ku...
We propose a family of kernels between images, defined as kernels between their respective segmentation graphs. The kernels are based on soft matching of subtree-patterns of the r...
We describe an efficient learning algorithm for aligning a symbolic representation of a musical piece with its acoustic counterpart. Our method employs a supervised learning appr...
Information distillation is the task that aims to extract relevant passages of text from massive volumes of textual and audio sources, given a query. In this paper, we investigate...