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...
Sensor-based statistical models promise to support a variety of advances in human-computer interaction, but building applications that use them is currently difficult and potentia...
— Machine learning has made great progress during the last decades and is being deployed in a wide range of applications. However, current machine learning techniques are far fro...
Abstract. A crucial problem in machine learning is to choose an appropriate representation of data, in a way that emphasizes the relations we are interested in. In many cases this ...
This paper describes ongoing research into the application of machine learning techniques for improving access to governmental information in complex digital libraries. Under the ...
Miles Efron, Jonathan L. Elsas, Gary Marchionini, ...