Conventional subspace learning or recent feature extraction methods consider globality as the key criterion to design discriminative algorithms for image classification. We demonst...
Yun Fu, Zhu Li, Junsong Yuan, Ying Wu, Thomas S. H...
Our ability to numerically model natural systems has progressed enormously over the last 10e20 years. During the last decade computational power has increased to the stage where w...
Motivation is well-known for its importance in learning and its influence on cognitive processes. Adaptive systems would greatly benefit from having a user model of the learner’s...
Abstract— Learning inverse kinematics has long been fascinating the robot learning community. While humans acquire this transformation to complicated tool spaces with ease, it is...
Recently there has been increasing interest in the problem of transfer learning, in which the typical assumption that training and testing data are drawn from identical distributi...