## Online Bayes Point Machines

### Cached

### Download Links

- [research.microsoft.com]
- [www.jmlr.org]
- [jmlr.csail.mit.edu]
- [www.ai.mit.edu]
- DBLP

### Other Repositories/Bibliography

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

Citations: | 69 - 3 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 = {}

}

### Years of Citing Articles

### OpenURL

### 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.