On the Perceptron’s Compression

Shay Moran, Ido Nachum, Itai Panasoff, Amir Yehudayoff

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


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.

Original languageEnglish
Title of host publicationBeyond the Horizon of Computability - 16th Conference on Computability in Europe, CiE 2020, Proceedings
EditorsMarcella Anselmo, Gianluca Della Vedova, Florin Manea, Arno Pauly
Number of pages16
ISBN (Print)9783030514655
StatePublished - 2020
Externally publishedYes
Event16th Conference on Computability in Europe, CiE 2020 - Fisciano, Italy
Duration: 29 Jun 20203 Jul 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12098 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference16th Conference on Computability in Europe, CiE 2020

Bibliographical note

Publisher Copyright:
© 2020, Springer Nature Switzerland AG.


  • Compression
  • Convex separation
  • Machine learning

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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