Probabilistic feature relevance learning (PFRL) is an effective technique for adaptively computing local feature relevance for content-based image retrieval. It however becomes le...
It is well known that how to extract dynamical features is a key issue for video based face analysis. In this paper, we present a novel approach of facial action units (AU) and ex...
We examine the ability to exploit the hierarchical structure of Internet addresses in order to endow network agents with predictive capabilities. Specifically, we consider Suppor...
Following (Blitzer et al., 2006), we present an application of structural correspondence learning to non-projective dependency parsing (McDonald et al., 2005). To induce the corre...
Background: Prediction of catalytic residues is a major step in characterizing the function of enzymes. In its simpler formulation, the problem can be cast into a binary classific...