A Smooth Perceptron Algorithm
Negar Soheili, Javier Peña · SIAM Journal on Optimization · 2012
The perceptron algorithm, introduced in the late 1950s in the machine learning community, is a simple greedy algorithm for finding a solution to a finite set of linear inequalities. The algorithm's main advantages are its simplicity and noise tolerance. The algorithm's main disadvantage is its slow convergence rate. We propose a modified version of the perceptron algorithm that retains the algorithm's original simplicity but has a substantially improved convergence rate.