On the Perceptron's Compression
Machine Learning
2018-06-15 v1 Machine Learning
Abstract
We study and provide exposition to several phenomena that are related to the perceptron's compression. One theme concerns modifications of the perceptron algorithm that yield better guarantees on the margin of the hyperplane it outputs. These modifications can be useful in training neural networks as well, and we demonstrate them with some experimental data. In a second theme, we deduce conclusions from the perceptron's compression in various contexts.
Cite
@article{arxiv.1806.05403,
title = {On the Perceptron's Compression},
author = {Shay Moran and Ido Nachum and Itai Panasoff and Amir Yehudayoff},
journal= {arXiv preprint arXiv:1806.05403},
year = {2018}
}