Learning Internal Representations by Error Propagation
At a glance
Explained how networks learn internal representations by passing errors backward through layers.
In one paragraph
Explained how networks could learn useful internal representations by passing prediction errors backward through their layers, adjusting connections instead of relying on manually designed features.
