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Researchers Developed A BackPropagation-Free Supervised Learning Framework Based on Artificial Neural Network That Facilitates The Transition From a Monadic Pavlovian Single Input–Teacher Association on an AMLE to any Arbitrary n Input–Teacher Associ
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Current AI models are heavily based on backpropagation-based learning, where an estimate of the ground truth is outputted by the model from input data in forward propagation. The model learns by updating the model parameters based on the backpropagation of the deviation between the estimate and the actual ground truth. However, this type of learning […]
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