This lecture talks about the multiplicative update rule for learning linear classifiers. In particular, we will look at the Winnow algorithm and some variants.
Links and Resources
Sanjeev Arora, Elad Hazan and Satyen Kale, The Multiplicative Weights Update Method: a Meta Algorithm and Applications
Nick Littlestone, Learning Quickly When Irrelevant Attributes Abound, /Machine Learning/ 1988.
Jyrki Kivinen, Manfred Warmuth and Peter Auer, The Perceptron algorithm versus Winnow: linear versus logarithmic mistake bounds when few input variables are relevant, /Artificial Intelligence/, 1997.