144 citations · 148 across the 3 of their papers we have counts for
3 papers
Task Selection for AutoML System Evaluation
Jonathan Lorraine, Nihesh Anderson, Chansoo Lee +2
Our goal is to assess if AutoML system changes - i.e., to the search space or hyperparameter optimization - will improve the final model's performance on production tasks. However,…
Parameter-Efficient Transfer Learning for NLP
Neil Houlsby, Andrei Giurgiu, Stanislaw Jastrzebski +5
Fine-tuning large pre-trained models is an effective transfer mechanism in NLP. However, in the presence of many downstream tasks, fine-tuning is parameter inefficient: an entire n…
Neural Architecture Search Over a Graph Search Space
Stanisław Jastrzębski, Quentin de Laroussilhe, Mingxing Tan +3
Neural Architecture Search (NAS) enabled the discovery of state-of-the-art architectures in many domains. However, the success of NAS depends on the definition of the search space.…