Abstract
Ensemble learning of K simple perceptrons, which determine their outputs by sign functions, is discussed within the framework of online learning and statistical mechanics. Hebbian, perceptron and AdaTron learning show different characteristics in their affinity for ensemble learning, that is maintaining variety among students. Results show that AdaTron learning is superior to the other two rules.
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