Generalizing to any diverse distribution: uniformity, gentle finetuning and rebalancing

Andreas Loukas, Karolis Martinkus, Ed Wagstaff +1

As training datasets grow larger, we aspire to develop models that generalize well to any diverse test distribution, even if the latter deviates significantly from the training dat…