Neural networks learn via sparse retrospective updates triggered internally when prediction error exceeds a threshold derived from recent error statistics, leading to stepwise parameter changes in simulations.
A Lagrange Programming Neural Network Approach for Nuclear Norm Optimization
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Internally triggered retrospective learning in neural networks
Neural networks learn via sparse retrospective updates triggered internally when prediction error exceeds a threshold derived from recent error statistics, leading to stepwise parameter changes in simulations.