Author name: Jan Kobiolka, Christian Frey, Gresa Shala, Arlind Kadra, Erind Bedalli, Josif Grabocka

arXiv:2602.15473v2 Announce Type: replace
Abstract: Gradient-based optimizers are highly sensitive to design choices in their adaptive learning rate mechanisms. To address this limitation, we introduce POP, a meta-learned Reinforcement Learning (RL) p…