Statistical Features in Learning
| dc.creator | Stamatescu, Ion-Olimpiu | |
| dc.date | 1998-09-09 | |
| dc.date | 1998-09-30 | |
| dc.date.accessioned | 2026-07-07T03:11:30Z | |
| dc.date.available | 2026-07-07T03:11:30Z | |
| dc.description | We study some features of learning models based on "delayed" and undifferentiated reinforcement and realized by simple algorithms which may be considered of a very elementary nature. We show that a modification of the Hebb-rule works well for this problem in a neural network realization and study numerically its convergence properties. An illustration for a more "concrete" situation is provided. | |
| dc.description | 13 pages, 7 figures; LEARNING'98 Madrid; 2 notations, 1 typo corrected | |
| dc.identifier | https://arxiv.org/abs/cond-mat/9809135 | |
| dc.identifier | http://arxiv.org/abs/cond-mat/9809135 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/28597 | |
| dc.subject | Condensed Matter | |
| dc.subject | Adaptation and Self-Organizing Systems | |
| dc.title | Statistical Features in Learning | |
| dc.type | text |