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cs.LG2022★ 1 cited
Zero-Shot AutoML with Pretrained Models
Ekrem Öztürk, Fabio Ferreira, Hadi S. Jomaa +3
Given a new dataset D and a low compute budget, how should we choose a pre-trained model to fine-tune to D, and set the fine-tuning hyperparameters without risking overfitting, par…
cs.LG2022★ 2 cited
Supervising the Multi-Fidelity Race of Hyperparameter Configurations
Martin Wistuba, Arlind Kadra, Josif Grabocka
Multi-fidelity (gray-box) hyperparameter optimization techniques (HPO) have recently emerged as a promising direction for tuning Deep Learning methods. However, existing methods su…