Tiny Transfer Learning: Towards Memory-Efficient On-Device Learning

By Han Cai, Chuang Gan, Ligeng Zhu, Song Han. 2020

23 citations recorded by the source corpus.

Subfields: Representation & Self-Supervised Learning, Efficiency & Compression

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Representation & Self-Supervised Learning

1. Shauli Ravfogel
2. Yoav Goldberg
3. Omer Levy
4. Ido Dagan
5. Sunipa Dev
6. Ivan Vulic
7. Oren Melamud
8. Anna Rogers

In Efficiency & Compression

1. Elad Ben-Zaken
2. Yoav Goldberg
3. Shauli Ravfogel
4. Yi-Lin Sung
5. Mohit Bansal
6. Jaemin Cho
7. Luke S. Zettlemoyer
8. Geoffrey Irving

Citations in the corpus

• BitFit: Simple Parameter-efficient Fine-tuning for Transformer-based Masked Language-models (2021, methodology): “Finally, 267 Cai et al. (2020) demonstrate that bias-only fine- 268 tuning similar to ours is effective also for adapta- 269 tion of pre-trained computer vision models.”