In this paper, we propose a general framework for sparse semi-supervised learning, which concerns using a small portion of unlabeled data and a few labeled data to represent targe...
We present a probabilistic ranking-driven classifier for the detection of video semantic concept, such as airplane, building, etc. Most existing concept detection systems utilize ...
Background: This paper considers the problem of identifying pathways through metabolic networks that relate to a specific biological response. Our proposed model, HME3M, first ide...
Background: Alternative splicing is a major contributor to the diversity of eukaryotic transcriptomes and proteomes. Currently, large scale detection of alternative splicing using...
Rileen Sinha, Michael Hiller, Rainer Pudimat, Ulri...
Incorporation of prior knowledge into the learning process can significantly improve low-sample classification accuracy. We show how to introduce prior knowledge into linear supp...