Deep Learning Gradient Flow

SIGNAL ANALYSIS

Derivation of explicit equations for cumulative biases and weights in Deep Learning with ReLU activation, impacting training data efficiency. This approach differs from prior work by providing a dynamical truncation of training data based on gradient descent for Euclidean loss. The industry bottleneck of inefficient training data utilization is addressed, with labs racing to optimize training processes, rendering traditional static data processing methods obsolete.