Harrington, Edward2008-06-302011-01-042008-06-302011-01-04b22285490http://hdl.handle.net/1885/47147Online learning algorithms have several key advantages compared to their batch learning algorithm counterparts. This thesis investigates several online learning algorithms and their application. The thesis has an underlying theme of the idea of combining several simple algorithms to give better performance. In this thesis we investigate: combining weights, combining hypothesis, and (sort of) hierarchical combining.¶ ...enThe Australian National Universityonline learning algorithmsperceptronlarge margin classifiersBayes point machineBPMonline Bayes point machineOBPMtracking expertsfixed share hierarchy algorithmFSHchannel equalizationequalizerline votingranking algorithms200410.25911/5d7a29e414896