Not All Tasks Are Equal: A Parameter-Efficient Task Reweighting Method for Few-Shot Learning

Cite

Text

Liu et al. "Not All Tasks Are Equal: A Parameter-Efficient Task Reweighting Method for Few-Shot Learning." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2023. doi:10.1007/978-3-031-43415-0_25

Markdown

[Liu et al. "Not All Tasks Are Equal: A Parameter-Efficient Task Reweighting Method for Few-Shot Learning." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2023.](https://mlanthology.org/ecmlpkdd/2023/liu2023ecmlpkdd-all/) doi:10.1007/978-3-031-43415-0_25

BibTeX

@inproceedings{liu2023ecmlpkdd-all,
  title     = {{Not All Tasks Are Equal: A Parameter-Efficient Task Reweighting Method for Few-Shot Learning}},
  author    = {Liu, Xin and Lyu, Yilin and Jing, Liping and Zeng, Tieyong and Yu, Jian},
  booktitle = {European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases},
  year      = {2023},
  pages     = {421-437},
  doi       = {10.1007/978-3-031-43415-0_25},
  url       = {https://mlanthology.org/ecmlpkdd/2023/liu2023ecmlpkdd-all/}
}