MetaGB: A Gradient Boosting Framework for Efficient Task Adaptive Meta Learning

Manqing Dong, Lina Yao, Xianzhi Wang 0001, Xiwei Xu, Liming Zhu 0001. MetaGB: A Gradient Boosting Framework for Efficient Task Adaptive Meta Learning. In James Bailey 0001, Pauli Miettinen, Yun Sing Koh, Dacheng Tao, Xindong Wu 0001, editors, IEEE International Conference on Data Mining, ICDM 2021, Auckland, New Zealand, December 7-10, 2021. pages 101-110, IEEE, 2021. [doi]

@inproceedings{DongY0X021,
  title = {MetaGB: A Gradient Boosting Framework for Efficient Task Adaptive Meta Learning},
  author = {Manqing Dong and Lina Yao and Xianzhi Wang 0001 and Xiwei Xu and Liming Zhu 0001},
  year = {2021},
  doi = {10.1109/ICDM51629.2021.00020},
  url = {https://doi.org/10.1109/ICDM51629.2021.00020},
  researchr = {https://researchr.org/publication/DongY0X021},
  cites = {0},
  citedby = {0},
  pages = {101-110},
  booktitle = {IEEE International Conference on Data Mining, ICDM 2021, Auckland, New Zealand, December 7-10, 2021},
  editor = {James Bailey 0001 and Pauli Miettinen and Yun Sing Koh and Dacheng Tao and Xindong Wu 0001},
  publisher = {IEEE},
  isbn = {978-1-6654-2398-4},
}