We consider the problem of the binary classification on imbalanced data, in which nearly all the instances are labelled as one class, while far fewer instances are labelled as the...
Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. ...
Abstract. This paper presents a machine-learning approach to the interactive classification of suspected liver metastases in fMRI images. The method uses fMRI-based statistical mod...
Motivation Protein remote homology prediction and fold recognition are central problems in computational biology. Supervised learning algorithms based on support vector machines a...
A new class of evolutionary computation processes is presented, called Learnable Evolution Model or LEM. In contrast to Darwinian-type evolution that relies on mutation, recombinat...
This paper proposes a state based approach to gesture learning and recognition. Using spatial clustering and temporal alignment, each gesture is defined to be an ordered sequence ...