ArticleDavid E. Rumelhart, Geoffrey E. Hinton & Ronald J. WilliamsResearch
The paper provides the foundational training algorithm for multi-layer neural networks, serving as an essential milestone in machine learning research.
The authors define how backpropagation solves the credit assignment problem in multi-layer architectures. By iteratively shifting weights to reduce error, hidden units automatically derive relevant feature representations, addressing the structural limitations of early perceptrons.
Summary generated by AI (Gemini 3.8 Flash, 27 September 2026). It may contain errors – the original source is authoritative.
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