#training-strategy News & Analysis

SmartMixed: A Two-Phase Training Strategy for Adaptive Activation Function Learning in Neural Networks

SmartMixed introduces a two-phase training strategy enabling neural networks to learn optimal per-neuron activation functions dynamically, then fix them for efficient inference. The approach allows different neurons to select from six candidate activation functions based on learned preferences, demonstrating that layer-specific activation choices improve network performance compared to uniform activation function architectures.