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...
Recently, there has been increasing interest in the issues of cost-sensitive learning and decision making in a variety of applications of data mining. A number of approaches have ...
Many problems in computer vision involving recognition and/or classification can be posed in the general framework of supervised learning. There is however one aspect of image dat...
Arunava Banerjee, Santhosh Kodipaka, Baba C. Vemur...
Learning a sequence classifier means learning to predict a sequence of output tags based on a set of input data items. For example, recognizing that a handwritten word is "ca...
Information empowers those who make sense from its successful interpretation; this is especially true on the subject of weather where the recipient is required to have prior forms...
Raymond Koon Chuan Koh, Henry Xin Liong Tan, Henry...