N-learners Problem: Fusion of Concepts

N. S.V. Rao, E. M. Oblow, C. W. Glover, G. E. Liepins

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

1 Scopus citations

Abstract

Given N learners each capable of learning concepts (subsets) of a domain set X in the sense of Valiant [19], we are interested in obtaining a composite system constituted by the fuser and the individual learners. We consider two cases: open and closed fusion. In open fusion the fuser is given the sample and the hypotheses of the individual learners; we show that the fusion rule can be obtained by formulating this problem as another learning problem. For the case all individual learners are trained with the same sample, we show sufficiency conditions that ensure the composite system to be better than the best of the individual. Second, in closed fusion the fuser does not have an access to either the training sample or the hypotheses of the individual learners. By suitably designing a linear threshold function of the outputs of individual learners, we show that the composite system can be made better than the best of the learners.

Original languageEnglish
Title of host publicationIROS 1992 - Proceedings of the 1992 IEEE/RSJ International Conference on Intelligent Robots and Systems
Subtitle of host publicationSensor-Based Robotics and Opportunties for its Industrial Applications
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1372-1379
Number of pages8
ISBN (Electronic)0780307372
DOIs
StatePublished - 1992
Externally publishedYes
Event1992 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 1992 - Raleigh, United States
Duration: Jul 7 1992Jul 10 1992

Publication series

NameIEEE International Conference on Intelligent Robots and Systems
Volume2
ISSN (Print)2153-0858
ISSN (Electronic)2153-0866

Conference

Conference1992 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 1992
Country/TerritoryUnited States
CityRaleigh
Period07/7/9207/10/92

Funding

The authors gratefully acknowledge the continuing financial support of this learning research by Oscar Manley of the Basic Energy Sciences Program in the Department of Energy and Teresa McMullen in the Intelligent Systems Program of the Office of Naval Research in the Department of Defense. Also, the first author is funded by National Science Foundation under grant #IRI-9108610, Oak Ridge National Laboratory operated by Martin Marietta under contracts #19X-SE043V and #SOXSJ433V, Old Dominion University Summer Faculty Fellowship for 1991 and Virginia's Center for Innovative Technology under contract # INF-90-015.

FundersFunder number
Office of Naval Research
Oak Ridge National Laboratory19X-SE043V, SOXSJ433V
National Science FoundationIRI-9108610

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