Linear Discriminant Analysis (LDA) is a well-known method for dimensionality reduction and classification. LDA in the binaryclass case has been shown to be equivalent to linear re...
Identifying the appropriate kernel function/matrix for a given dataset is essential to all kernel-based learning techniques. A variety of kernel learning algorithms have been prop...
One model of multithreading gaining popularity on multiprocessor systems is the message-driven model of computation. The message-driven model is a reactive model in which an arriv...
Recent studies have shown that graph-based approaches are effective for semi-supervised learning. The key idea behind many graph-based approaches is to enforce the consistency bet...
Learning from structured data is becoming increasingly important. However, most prior work on kernel methods has focused on learning from attribute-value data. Only recently, rese...
Adam Kowalczyk, Alex J. Smola, Peter A. Flach, Tho...