Optimal supervised learning with two teachers

Marco A.P Idiart and Emerson L.de Santa Helena

Physica A: Statistical Mechanics and its Applications, 1998, vol. 253, issue 1, 333-346

Abstract: We study Hebbian supervised learning of a linearly separable function in the presence of two instructing perceptrons: The teacher (B) that carries the correct function, or rule to be learned, and the assistant teacher (T) that is itself in the process of learning the rule. In the assistant teacher’s training set only the teacher perceptron is used. In the student’s training set, on the other hand, the answers are linear combinations of the answers coming from the teacher and the answers coming from the assistant teacher σB+aσT. We demonstrate through analytical results that the generalization gain per example can be improved beyond the typical Hebbian α−1/2 dependence by adjusting the attention parameter “a”. The optimal result, that corresponds to the case where a≃−12, and the assistant teacher and the student have the same training questions, gives us generalization error decaying with α−3/4.

Date: 1998
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437197006407
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:253:y:1998:i:1:p:333-346

DOI: 10.1016/S0378-4371(97)00640-7

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().