AAAI 2025technical0 citations

Towards Trustworthy, Efficient, and Scalable Machine Learning

Yezi Liu

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.

BibTeX
@article{Liu_2025, title={Towards Trustworthy, Efficient, and Scalable Machine Learning}, volume={39}, url={https://ojs.aaai.org/index.php/AAAI/article/view/35217}, DOI={10.1609/aaai.v39i28.35217}, abstractNote={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.}, number={28}, journal={Proceedings of the AAAI Conference on Artificial Intelligence}, author={Liu, Yezi}, year={2025}, month={Apr.}, pages={29279-29280} }
Towards Trustworthy, Efficient, and Scalable Machine Learning · AAAI 2025