Online Bayes Point Machines

Online Bayes Point Machines

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by Edward Harrington , Ralf Herbrich , Jyrki Kivinen , John C. Platt , Robert C. Williamson

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55 - 2 self

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@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.

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