208 citations · 504 across the 30 of their papers we have counts for
4 papers · 1 filter
PASHA: Efficient HPO and NAS with Progressive Resource Allocation
Ondrej Bohdal, Lukas Balles, Martin Wistuba +3
Hyperparameter optimization (HPO) and neural architecture search (NAS) are methods of choice to obtain the best-in-class machine learning models, but in practice they can be costly…
Continual Learning with Transformers for Image Classification
Beyza Ermis, Giovanni Zappella, Martin Wistuba +2
In many real-world scenarios, data to train machine learning models become available over time. However, neural network models struggle to continually learn new concepts without fo…
Memory Efficient Continual Learning with Transformers
Beyza Ermis, Giovanni Zappella, Martin Wistuba +2
In many real-world scenarios, data to train machine learning models becomes available over time. Unfortunately, these models struggle to continually learn new concepts without forg…
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…