@inproceedings{3c05982a3bbb4026844dcd53da92c367,
title = "N-learners Problem: Fusion of Concepts",
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.",
author = "Rao, {N. S.V.} and Oblow, {E. M.} and Glover, {C. W.} and Liepins, {G. E.}",
note = "Publisher Copyright: {\textcopyright} 1992 IEEE.; 1992 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 1992 ; Conference date: 07-07-1992 Through 10-07-1992",
year = "1992",
doi = "10.1109/IROS.1992.594563",
language = "English",
series = "IEEE International Conference on Intelligent Robots and Systems",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1372--1379",
booktitle = "IROS 1992 - Proceedings of the 1992 IEEE/RSJ International Conference on Intelligent Robots and Systems",
}