Abstract:The performance of large neural networks can be judged not only by their storage capacity but also by the time required for learning. A polynomial learning algorithm with learning time ∼ N 2 in a network with N units might be practical whereas a learning time ∼ e N would allow rather small networks only. The question of absolute storage capacity α c and capacity for polynomial learning rules α p is discussed for several feed-forward architectures, the perceptron, the binary perceptron, the committee machine an… Show more
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