Early-stopped neural networks are consistent

Ziwei Ji, Justin D. Li, Matus Telgarsky. Early-stopped neural networks are consistent. 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 1805-1817, 2021. [doi]

@inproceedings{JiLT21,
  title = {Early-stopped neural networks are consistent},
  author = {Ziwei Ji and Justin D. Li and Matus Telgarsky},
  year = {2021},
  url = {https://proceedings.neurips.cc/paper/2021/hash/0e1ebad68af7f0ae4830b7ac92bc3c6f-Abstract.html},
  researchr = {https://researchr.org/publication/JiLT21},
  cites = {0},
  citedby = {0},
  pages = {1805-1817},
  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},
}