Background: In the area of protein structure prediction, recently a lot of effort has gone into the development of Model Quality Assessment Programs (MQAPs). MQAPs distinguish hig...
Ingolf Sommer, Stefano Toppo, Oliver Sander, Thoma...
Sparsity-promoting L1-regularization has recently been succesfully used to learn the structure of undirected graphical models. In this paper, we apply this technique to learn the ...
Mark W. Schmidt, Alexandru Niculescu-Mizil, Kevin ...
Background: One of the most powerful methods for the prediction of protein structure from sequence information alone is the iterative construction of profile-type models. Because ...
Abstract. We propose a generative model for automatic query reformulations from an initial query using the underlying subtopic structure of top ranked retrieved documents. We addre...
Debasis Ganguly, Johannes Leveling, Gareth J. F. J...
In this paper we study the problem of classifying chemical compound datasets. We present a sub-structure-based classification algorithm that decouples the sub-structure discovery...
Mukund Deshpande, Michihiro Kuramochi, George Kary...