The Minimum Description Length Principle and Its Application to Online Learning of Handprinted Characters
Proceedings of the Eleventh International Joint Conference on Artificial Intelligence. Machine Learning. Pages 843-847.
Abstract
Our objective is to introduce Rissanen's Minimum Description Length (MDL) Principle as a useful tool for character recognition and present a first application. Using MDL principle, a learning system has been implemented which. after simple training, is able to online recognize th trainer's handwriting in English and Chinese (including several thousand characters) with high success rate. The experimental results conform with the theoretical predictions. We will also try to give an elegant explanation of Rissanen's minimum description length principle (MDLP).
@inproceedings{ijcai1989p135,
title = {The Minimum Description Length Principle and Its Application to Online Learning of Handprinted Characters},
author = {Gao, Qiong and Li, Ming},
booktitle = {Proceedings of the Eleventh International Joint Conference on
Artificial Intelligence, {IJCAI-89}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {N. S. Sridharan},
pages = {843--847},
year = {1989},
month = {8},
note = {Machine Learning},
url = {https://ijcai.org/proceedings/1989/135},
}
TY - CPAPER TI - The Minimum Description Length Principle and Its Application to Online Learning of Handprinted Characters AU - Gao, Qiong AU - Li, Ming T2 - Proceedings of the Eleventh International Joint Conference on Artificial Intelligence, IJCAI-89 PB - International Joint Conferences on Artificial Intelligence PY - 1989 SP - 843 EP - 847 UR - https://ijcai.org/proceedings/1989/135 ER -Copied
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