Online Bayes Point Machines
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by
Edward Harrington
,
Ralf Herbrich
,
Jyrki Kivinen
,
John C. Platt
,
Robert C. Williamson
| Citations: | 55 - 2 self |
BibTeX
@MISC{Harrington_onlinebayes,
author = {Edward Harrington and Ralf Herbrich and Jyrki Kivinen and John C. Platt and Robert C. Williamson},
title = {Online Bayes Point Machines},
year = {}
}
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Abstract
We present a new and simple algorithm for learning large margin classi ers that works in a truly online manner. The algorithm generates a linear classi er by averaging the weights associated with several perceptron-like algorithms run in parallel in order to approximate the Bayes point. A random subsample of the incoming data stream is used to ensure diversity in the perceptron solutions. We experimentally study the algorithm's performance on online and batch learning settings.







