With suitable architecture, gradient-based learning can form decision surfaces that classify high-dimensional patterns such as handwritten characters with minimal preprocessing.

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• Multilayer neural networks trained with backpropagation are the best example of successful gradient-based learning. YBYoshua Bengio1 Jan 1998
• Pre-trained representations reduce the need for many heavily-engineered task-specific architectures. JDJacob Devlin11 Oct 2018
• Gradient descent finds a solution to the problems a model has seen; nothing in the algorithm makes it pick the one that generalises well. RSRichard Sutton26 Sept 2025
• Graph transformer networks allow multimodule document recognition systems to be trained globally with gradient methods to minimize overall performance. YBYoshua Bengio1 Jan 1998
• AI text detection through pattern recognition is prone to errors because LLM text may defy patterns or human text may mirror AI patterns. JWJohn Warner9 Aug 2026

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