We propose an algorithm to construct classification models with a mixture of kernels from labeled and unlabeled data. The derived classifier is a mixture of models, each based o...
Background: With the abundant information produced by microarray technology, various approaches have been proposed to infer transcriptional regulatory networks. However, few appro...
Grace S. Shieh, Chung-Ming Chen, Ching-Yun Yu, Jui...
Background: Constraint-based approaches facilitate the prediction of cellular metabolic capabilities, based, in turn on predictions of the repertoire of enzymes encoded in the gen...
Jacek Sroka, Lukasz Bieniasz-Krzywiec, Szymon Gwoz...
A new hierarchical nonparametric Bayesian model is proposed for the problem of multitask learning (MTL) with sequential data. Sequential data are typically modeled with a hidden M...
Enriching speech recognition output with sentence boundaries improves its human readability and enables further processing by downstream language processing modules. We have const...
Yang Liu, Nitesh V. Chawla, Mary P. Harper, Elizab...