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Whiting, Stephen's Publications (detailed list) |
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THIS PAGE IS NO LONGER MAINTAINED. Click here for our new publications list, which is more up-to-date.
This page contains the titles and abstracts of papers written by author Whiting, Stephen, a member of the BYU Neural Networks and Machine Learning (NNML) Research Group. Postscript files are available for most papers. A more concise list is available.
To view the entire list in one page, click here.
Learning Multiple Correct Classifications from Incomplete Data using Weakened Implicit Negatives
- Authors: Stephen Whiting and Dan Ventura
- Abstract:
Classification problems with output class overlap create problems for standard neural network approaches. We present a modification of a simple feedforward neural network that is capable of learning problems with output overlap, including problems exhibiting hierarchical class structures in the output. Our method of applying weakened implicit negatives to address overlap and ambiguity allows the algorithm to learn a large portion of the hierarchical structure from very incomplete data. Our results show an improvement of approximately 58% over a standard backpropagation network on the hierarchical problem.
- Reference: In Proceedings of the International Joint Conference on Neural Networks, pages 2953–2958, July 2004.
- BibTeX
- Download the file: pdf
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