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On-line Learning of Perceptron from Noisy Data by One and Two Teachers
2006
Journal of the Physical Society of Japan
We analyze the on-line learning of a Perceptron from signals produced by a single Perceptron suffering from external noise or by two independent Perceptrons without noise. We adopt typical three learning rules in both single-teacher and two-teacher cases. For the single-teacher case, we treat the input and output noises and for the two-teacher case, we assume that signals are given by two teachers with a definite probability. In the single-teacher case, in order to improve the learning when it
doi:10.1143/jpsj.75.114007
fatcat:owuo4bnlf5aofkcotmoxu2xsvm