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.
Original language | English |
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Title of host publication | Beyond the Horizon of Computability - 16th Conference on Computability in Europe, CiE 2020, Proceedings |
Editors | Marcella Anselmo, Gianluca Della Vedova, Florin Manea, Arno Pauly |
Publisher | Springer |
Pages | 310-325 |
Number of pages | 16 |
ISBN (Print) | 9783030514655 |
DOIs | |
State | Published - 2020 |
Externally published | Yes |
Event | 16th Conference on Computability in Europe, CiE 2020 - Fisciano, Italy Duration: 29 Jun 2020 → 3 Jul 2020 |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 12098 LNCS |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | 16th Conference on Computability in Europe, CiE 2020 |
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Country/Territory | Italy |
City | Fisciano |
Period | 29/06/20 → 3/07/20 |
Bibliographical note
Publisher Copyright:© 2020, Springer Nature Switzerland AG.
Keywords
- Compression
- Convex separation
- Machine learning
ASJC Scopus subject areas
- Theoretical Computer Science
- General Computer Science