The prediction of protein secondary structure is a classical problem in bioinformatics, and in the past few years several machine learning techniques have been proposed to t. From...
Conditional log-linear models are a commonly used method for structured prediction. Efficient learning of parameters in these models is therefore an important problem. This paper ...
Amir Globerson, Terry Koo, Xavier Carreras, Michae...
In many retrieval tasks, one important goal involves retrieving a diverse set of results (e.g., documents covering a wide range of topics for a search query). First of all, this r...
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...
RNA structure prediction, or folding, is a computeintensive task that lies at the core of several search applications in bioinformatics. We begin to address the need for high-thro...
Arpith C. Jacob, Jeremy Buhler, Roger D. Chamberla...