| dc.contributor.advisor | Nir Shavit. | en_US |
| dc.contributor.author | Rosenfeld, Jonathan S.(Jonathan Shmuel) | en_US |
| dc.contributor.other | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. | en_US |
| dc.date.accessioned | 2019-11-04T19:54:08Z | |
| dc.date.available | 2019-11-04T19:54:08Z | |
| dc.date.copyright | 2019 | en_US |
| dc.date.issued | 2019 | en_US |
| dc.identifier.uri | https://hdl.handle.net/1721.1/122703 | |
| dc.description | This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. | en_US |
| dc.description | Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2019 | en_US |
| dc.description | Cataloged from student-submitted PDF version of thesis. | en_US |
| dc.description | Includes bibliographical references (pages 57-58). | en_US |
| dc.description.abstract | Artificial Neural Networks (NN) are notorious for their size requirements and for the effort involved in developing well performing network models. This thesis uncovers a fundamental relationship that ties model size and performance in a predictable manner. This relationship enables a well-founded development of networks at small scale while producing insight into their large-scale behavior. | en_US |
| dc.description.statementofresponsibility | by Jonathan S. Rosenfeld. | en_US |
| dc.format.extent | 58 pages | en_US |
| dc.language.iso | eng | en_US |
| dc.publisher | Massachusetts Institute of Technology | en_US |
| dc.rights | MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission. | en_US |
| dc.rights.uri | http://dspace.mit.edu/handle/1721.1/7582 | en_US |
| dc.subject | Electrical Engineering and Computer Science. | en_US |
| dc.title | On the relation between neural network size and performance | en_US |
| dc.type | Thesis | en_US |
| dc.description.degree | S.M. | en_US |
| dc.contributor.department | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science | en_US |
| dc.identifier.oclc | 1124957898 | en_US |
| dc.description.collection | S.M. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science | en_US |
| dspace.imported | 2019-11-04T19:54:07Z | en_US |
| mit.thesis.degree | Master | en_US |
| mit.thesis.department | EECS | en_US |
