A Smooth Perceptron Algorithm

@article{Soheili2012ASP,
  title={A Smooth Perceptron Algorithm},
  author={Negar Soheili and Javier Pe{\~n}a},
  journal={SIAM Journal on Optimization},
  year={2012},
  volume={22},
  pages={728-737}
}
The perceptron algorithm, introduced in the late fifties 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. 
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