AI RESEARCH
PyLO: Towards Accessible Learned Optimizers in PyTorch
arXiv CS.LG
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ArXi:2506.10315v3 Announce Type: replace Learned optimizers have been an active research topic over the past decade, with increasing progress toward practical, general-purpose optimizers that can serve as drop-in replacements for widely used methods like Adam. However, recent advances such as VeLO, which was meta-trained for 4000 TPU-months, remain largely inaccessible to the broader community, in part due to their reliance on JAX and the absence of user-friendly packages for independently using the optimizers after meta-