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...
In this paper, we present a graphical model for protein secondary structure prediction. This model extends segmental semi-Markov models (SSMM) to exploit multiple sequence alignme...
Protein-protein interactions (PPI) play a key role in many biological systems. Over the past few years, an explosion in availability of functional biological data obtained from hi...
Inference tasks in Markov random fields (MRFs) are closely related to the constraint satisfaction problem (CSP) and its soft generalizations. In particular, MAP inference in MRF i...
Relational world models that can be learned from experience in stochastic domains have received significant attention recently. However, efficient planning using these models rema...