Learning Hyperparameters via a Data-Emphasized Variational Objective
arXiv:2502.01861v3 Announce Type: replace-cross
Abstract: When training large models on limited data, avoiding overfitting is paramount. Common grid search or smarter search methods rely on expensive separate runs for each candidate hyperparameter, wh…