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Forward Target Propagation: A Forward-Only Approach to Global Error Credit Assignment via Local Losses
Training neural networks has traditionally relied on backpropagation (BP), a gradient-based algorithm that, despite its widespread success, suffers from key limitations in both biological and hardware perspectives. These include backward error propagation by symmetric weights, non-local credit assig
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