N. Cristianini, C. Campbell, and J. Shawe–Taylor (1998)
Multiplicative Updatings for Support-Vector Learning
Royal Holloway College, NeuroCOLT Technical Report(NC-TR-98-016), University of London, UK.
A Multiplicative-Updating algorithm for learning Support Vector machines is presented which exploits the particular structure of high-generalization hypotheses, by achieving fast rate of convergence just in those situations where high generalization can be obtained, namely small number of support vectors or large margin.