Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is perfor...
Gert R. G. Lanckriet, Nello Cristianini, Peter L. ...
Kernel methods have been applied successfully in many data mining tasks. Subspace kernel learning was recently proposed to discover an effective low-dimensional subspace of a kern...
Jianhui Chen, Shuiwang Ji, Betul Ceran, Qi Li, Min...
Interface designers normally strive for a design that minimises the user's effort. However, when the design's objective is to train users to interact with interfaces tha...
Andy Cockburn, Per Ola Kristensson, Jason Alexande...
Trust learning is a crucial aspect of information exchange, negotiation, and any other kind of social interaction among autonomous agents in open systems. But most current probabil...
: In our department we have a long history of developing interfaces for learning, which are framed by constructivist and constructionist theories of learning. Thus we try to create...