Using the Perceptron Algorithm to Find Consistent Hypotheses
Anthony, M. and Shawe-Taylor, J. (1993) Using the Perceptron Algorithm to Find Consistent Hypotheses. Combinatorics, Probability and Computing, 2, 385-387.
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Description/Abstract
The perceptron learning algorithm yields quite naturally an algorithm for finding a linearly separable boolean function consistent with a sample of such a function. Using the idea of a specifying sample, we give a simple proof that this algorithm is not efficient, in general.
| Item Type: | Article |
|---|---|
| ISSNs: | 0963548314692163 |
| Divisions: | Faculty of Physical and Applied Science > Electronics and Computer Science |
| Item ID: | 259818 |
| Date Deposited: | 24 Aug 2004 |
| Last Modified: | 02 Mar 2012 11:58 |
| Contributors: | Anthony, M. (Author) Shawe-Taylor, J. (Author) |
| Date: | 1993 |
| Status: | Published |
| Publisher: | Cambridge Journals |
| Further Information: | Google Scholar |
| URI: | http://eprints.soton.ac.uk/id/eprint/259818 |
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