PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

A New Perspective on an Old Perceptron Algorithm
Shai Shalev-Shwartz and Yoram Singer
In: COLT 2005, June 27-30, 2005, Bertinoro, Italy.


We present a generalization of the Perceptron algorithm. The new algorithm performs a Perceptron-style update whenever the margin of an example is smaller than a predefined value. We derive worst case mistake bounds for our algorithm. As a byproduct we obtain a new mistake bound for the Perceptron algorithm in the inseparable case. We describe a multiclass extension of the algorithm. This extension is used in an experimental evaluation in which we compare the proposed algorithm to the Perceptron algorithm.

PDF - Requires Adobe Acrobat Reader or other PDF viewer.
EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Theory & Algorithms
ID Code:1058
Deposited By:Shai Shalev-Shwartz
Deposited On:26 August 2005