In this paper we survey work being conducted at Imperial College on the use of machine learning to build Systems Biology models of the effects of toxins on biochemical pathways. Se...
We propose the framework of mutual information kernels for learning covariance kernels, as used in Support Vector machines and Gaussian process classifiers, from unlabeled task da...
We propose a hybrid generative/discriminative framework for semantic parsing which combines the hidden vector state (HVS) model and the hidden Markov support vector machines (HMSV...
Background: Protein secondary structure prediction provides insight into protein function and is a valuable preliminary step for predicting the 3D structure of a protein. Dynamic ...
Zafer Aydin, Ajit Singh, Jeff Bilmes, William Staf...
Abstract. Classification of structured data (i.e., data that are represented as graphs) is a topic of interest in the machine learning community. This paper presents a different,...