Internal Robust Representations for Domain Generalization

AAAI 2023 pp. 15451

doi:10.1609/AAAI.V37I13.26818 /aaai/2023/rostami2023aaai-internal/

Abstract

Model generalization under distributional changes remains a significant challenge for machine learning. We present consolidating the internal representation of the training data in a model as a strategy of improving model generalization.

PDF AAAI Semantic Scholar

Cite

Text

Rostami. "Internal Robust Representations for Domain Generalization." AAAI Conference on Artificial Intelligence, 2023. doi:10.1609/AAAI.V37I13.26818

Markdown

[Rostami. "Internal Robust Representations for Domain Generalization." AAAI Conference on Artificial Intelligence, 2023.](https://mlanthology.org/aaai/2023/rostami2023aaai-internal/) doi:10.1609/AAAI.V37I13.26818

BibTeX

@inproceedings{rostami2023aaai-internal,
  title     = {{Internal Robust Representations for Domain Generalization}},
  author    = {Rostami, Mohammad},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2023},
  pages     = {15451},
  doi       = {10.1609/AAAI.V37I13.26818},
  url       = {https://mlanthology.org/aaai/2023/rostami2023aaai-internal/}
}