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Research
For technical details, please check our research publications.
- FLAML: A Fast and Lightweight AutoML Library. Chi Wang, Qingyun Wu, Markus Weimer, Erkang Zhu. MLSys 2021.
@inproceedings{wang2021flaml,
title={FLAML: A Fast and Lightweight AutoML Library},
author={Chi Wang and Qingyun Wu and Markus Weimer and Erkang Zhu},
year={2021},
booktitle={MLSys},
}
- Frugal Optimization for Cost-related Hyperparameters. Qingyun Wu, Chi Wang, Silu Huang. AAAI 2021.
- Economical Hyperparameter Optimization With Blended Search Strategy. Chi Wang, Qingyun Wu, Silu Huang, Amin Saied. ICLR 2021.
- An Empirical Study on Hyperparameter Optimization for Fine-Tuning Pre-trained Language Models. Susan Xueqing Liu, Chi Wang. ACL 2021.
- ChaCha for Online AutoML. Qingyun Wu, Chi Wang, John Langford, Paul Mineiro and Marco Rossi. ICML 2021.
- Fair AutoML. Qingyun Wu, Chi Wang. ArXiv preprint arXiv:2111.06495 (2021).
- Mining Robust Default Configurations for Resource-constrained AutoML. Moe Kayali, Chi Wang. ArXiv preprint arXiv:2202.09927 (2022).
- Targeted Hyperparameter Optimization with Lexicographic Preferences Over Multiple Objectives. Shaokun Zhang, Feiran Jia, Chi Wang, Qingyun Wu. ICLR 2023 (notable-top-5%).