Tag: neural network training

Researchers have identified riddled basin geometry as a dynamical mechanism causing deep neural networks to produce divergent training outcomes despite ...

A new study shows that automated metaheuristic hyper-parameter optimization substantially boosts the accuracy of Hinton's memory-efficient Forward-Forward training algorithm across ...

A rigorous cross-domain benchmark finds no detectable advantage for quantum-inspired optimizers over well-tuned classical methods in neural-network training.

A new tensor decomposition framework dynamically compresses and decompresses neural network layers during training, achieving 95.81 percent accuracy in 12 ...