Adversarial Logit Separation

In this paper, we propose a sequential iterative method to optimize the cosine distance of output logits to maximize model diversity with a cosine annealing schedule to stabalize convergence. We call this strategy logit separation. This ensemble joint training technique needs to be added to a base method that acts on individual models.