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Empirical Inference Conference Paper 2025

Avoiding spurious sharpness minimization broadens applicability of SAM

arXiv
Thumb ticker sm 20211026 sidak pal singh wolfram scheible short
Empirical Inference
Sidak Pal Singh
Collaborator

Author(s): Singh, S. P. and Mobahi, H. and Agarwala, A. and Dauphin, Y.
Links:
Book Title: Proceedings of the 42nd International Conference on Machine Learning (ICML)
Volume: 267
Pages: 55702--55719
Year: 2025
Month: July
Series: Proceedings of Machine Learning Research
Editors: Singh, Aarti and Fazel, Maryam and Hsu, Daniel and Lacoste-Julien, Simon and Berkenkamp, Felix and Maharaj, Tegan and Wagstaff, Kiri and Zhu, Jerry
Publisher: PMLR
BibTeX Type: Conference Paper (conference)
Event Name: International Conference on Machine Learning
Event Place: Vancouver Convention Center
State: Published
URL: https://proceedings.mlr.press/v267/singh25b.html

BibTeX 

@conference{SinMobAgaDau25,
  title = {Avoiding spurious sharpness minimization broadens applicability of SAM},
  booktitle = {Proceedings of the 42nd International Conference on Machine Learning (ICML)},
  volume = {267},
  pages = {55702--55719},
  series = {Proceedings of Machine Learning Research},
  editors = {Singh, Aarti and Fazel, Maryam and Hsu, Daniel and Lacoste-Julien, Simon and Berkenkamp, Felix and Maharaj, Tegan and Wagstaff, Kiri and Zhu, Jerry},
  publisher = {PMLR},
  month = jul,
  year = {2025},
  author = {Singh, S. P. and Mobahi, H. and Agarwala, A. and Dauphin, Y.},
  url = {https://proceedings.mlr.press/v267/singh25b.html},
  month_numeric = {7}
}