This paper provides an algorithmic framework for learning statistical models involving directed spanning trees, or equivalently non-projective dependency structures. We show how p...
Terry Koo, Amir Globerson, Xavier Carreras, Michae...
In this paper, we propose a modular cascaded approach to data driven dependency parsing. Each module or layer leading to the complete parse produces a linguistically valid partial...
Quantizer design for lossy compression with mismatched side information (SI) at the decoder is investigated. The statistical dependency between the source and SI is assumed to be ...
In this paper, we propose a methodology to predict the popularity of online contents. More precisely, rather than trying to infer the popularity of a content itself, we infer the l...
Abstract—This paper describes an efficient image transformation method based on histogram information and some prior knowledge of tissue expression in different modalities for r...