Sample sizes for multiple-output threshold networks
John S. Shawe-Taylor, Martin Anthony · Network Computation in Neural Systems · 1991
This paper applies the theory of probably approximately correct (PAC) learning to multiple-output feedforward threshold networks. It is shown that the sample size for reliable learning can be bounded above by a quantity independent of the number of outputs of the network.