A Neural Collapse and simplex ETF

Then the same solution in the Lemma 1 is obtained. We will prove that if Assumptions 1 and 2 hold, the stochastic gradients cannot be uniformly bounded. However, FedGELA might reach better local optimal by adapting the feature structure. Here we complete the proof. "existing angle" as the angle of classifier vectors belonging to classes that exist in a local client In Fed-ISIC2019, there exists a true PCDD situation that needs to be solved.