A Constructive RBF Network for Writer Adaptation

NeurIPS 1996 pp. 765-771

/neurips/1996/platt1996neurips-constructive/

Abstract

This paper discusses a fairly general adaptation algorithm which augments a standard neural network to increase its recognition ac(cid:173) curacy for a specific user. The basis for the algorithm is that the output of a neural network is characteristic of the input, even when the output is incorrect. We exploit this characteristic output by using an Output Adaptation Module (OAM) which maps this out(cid:173) put into the correct user-dependent confidence vector. The OAM is a simplified Resource Allocating Network which constructs ra(cid:173) dial basis functions on-line. We applied the OAM to construct a writer-adaptive character recognition system for on-line hand(cid:173) printed characters. The OAM decreases the word error rate on a test set by an average of 45%, while creating only 3 to 25 basis functions for each writer in the test set.

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Cite

Text

Platt and Matic. "A Constructive RBF Network for Writer Adaptation." Neural Information Processing Systems, 1996.

Markdown

[Platt and Matic. "A Constructive RBF Network for Writer Adaptation." Neural Information Processing Systems, 1996.](https://mlanthology.org/neurips/1996/platt1996neurips-constructive/)

BibTeX

@inproceedings{platt1996neurips-constructive,
  title     = {{A Constructive RBF Network for Writer Adaptation}},
  author    = {Platt, John C. and Matic, Nada},
  booktitle = {Neural Information Processing Systems},
  year      = {1996},
  pages     = {765-771},
  url       = {https://mlanthology.org/neurips/1996/platt1996neurips-constructive/}
}