We present a supervised learning approach to identification of anaphoric and non-anaphoric noun phrases and show how such information can be incorporated into a coreference resolu...
We propose a formulation of the Decision Tree learning algorithm in the Compression settings and derive tight generalization error bounds. In particular, we propose Sample Compres...
This paper presents a learning theoretical analysis of correlation clustering (Bansal et al., 2002). In particular, we give bounds on the error with which correlation clustering r...
We study the problem of learning using combinations of machines. In particular we present new theoretical bounds on the generalization performance of voting ensembles of kernel ma...
Previous research on program visualization tools has suggested that both static and dynamic aspects of the program shall be shown to novice students. We attempted to expand the st...