Brownian Heads for Deep ReLU Representations: Activation Mass and the Cost of Same-Sample Selection

Deep representation learning often selects hidden features and fits the final predictor on the same sample, so fixed-feature analysis performed after selection can omit selection cost. We study the conditional empirical Rademacher complexity of deep ReLU representations followed by bounded-norm pred