ML Anthology

Towards Trustworthy, Efficient, and Scalable Machine Learning

Yezi Liu
AAAI 2025 pp. 29279-29280
doi:10.1609/AAAI.V39I28.35217 /aaai/2025/liu2025aaai-trustworthy/

Abstract

Throughout the development of machine learning, researchers have increasingly focused on the challenges of trustworthiness, efficiency, and scalability. Our research specifically addresses these critical aspects.

AAAI Semantic Scholar

Cite

Text

Liu. "Towards Trustworthy, Efficient, and Scalable Machine Learning." AAAI Conference on Artificial Intelligence, 2025. doi:10.1609/AAAI.V39I28.35217

Markdown

[Liu. "Towards Trustworthy, Efficient, and Scalable Machine Learning." AAAI Conference on Artificial Intelligence, 2025.](https://mlanthology.org/aaai/2025/liu2025aaai-trustworthy/) doi:10.1609/AAAI.V39I28.35217

BibTeX

@inproceedings{liu2025aaai-trustworthy,
  title     = {{Towards Trustworthy, Efficient, and Scalable Machine Learning}},
  author    = {Liu, Yezi},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2025},
  pages     = {29279-29280},
  doi       = {10.1609/AAAI.V39I28.35217},
  url       = {https://mlanthology.org/aaai/2025/liu2025aaai-trustworthy/}
}