Deciding When to Switch: E-Processes for Adaptive Minimax Training for Generative Adversarial Nets
DGX agentarXiv:2608.10096v1 Announce Type: cross Abstract: Modern data science increasingly gives rise to hypothesis-testing problems that are not naturally formulated in terms of parameters within prespecifie