Johannes von Oswald, Dominic Zhao, Seijin Kobayashi, Simon Schug, Massimo Caccia, Nicolas Zucchet, João Sacramento. Learning where to learn: Gradient sparsity in meta and continual learning. In Marc'Aurelio Ranzato, Alina Beygelzimer, Yann N. Dauphin, Percy Liang, Jennifer Wortman Vaughan, editors, Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual. pages 5250-5263, 2021. [doi]
@inproceedings{OswaldZKSCZS21,
title = {Learning where to learn: Gradient sparsity in meta and continual learning},
author = {Johannes von Oswald and Dominic Zhao and Seijin Kobayashi and Simon Schug and Massimo Caccia and Nicolas Zucchet and João Sacramento},
year = {2021},
url = {https://proceedings.neurips.cc/paper/2021/hash/2a10665525774fa2501c2c8c4985ce61-Abstract.html},
researchr = {https://researchr.org/publication/OswaldZKSCZS21},
cites = {0},
citedby = {0},
pages = {5250-5263},
booktitle = {Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual},
editor = {Marc'Aurelio Ranzato and Alina Beygelzimer and Yann N. Dauphin and Percy Liang and Jennifer Wortman Vaughan},
}