Massively Parallel Hyperparameter Tuning. - Liam Li; Kevin G. Jamieson; Afshin Rostamizadeh; Ekaterina Gonina; Moritz Hardt; Benjamin Recht; Ameet Talwalkar (CoRR, 2018)

Random Search and Reproducibility for Neural Architecture Search. - Liam Li; Ameet Talwalkar (UAI, 2019)

Exploiting Reuse in Pipeline-Aware Hyperparameter Tuning. - Liam Li; Evan Randall Sparks; Kevin G. Jamieson; Ameet Talwalkar (CoRR, 2019)

A System for Massively Parallel Hyperparameter Tuning. - Liam Li; Kevin G. Jamieson; Afshin Rostamizadeh; Ekaterina Gonina; Jonathan Ben-tzur; Moritz Hardt; Benjamin Recht; Ameet Talwalkar (MLSys, 2020)

On Data Efficiency of Meta-learning. - Maruan Al-Shedivat; Liam Li; Eric P. Xing; Ameet Talwalkar (AISTATS, 2021)

Geometry-Aware Gradient Algorithms for Neural Architecture Search. - Liam Li; Mikhail Khodak; Nina Balcan; Ameet Talwalkar (ICLR, 2021)

Federated Hyperparameter Tuning: Challenges, Baselines, and Connections to Weight-Sharing. - Mikhail Khodak; Renbo Tu; Tian Li 005; Liam Li; Maria-Florina Balcan; Virginia Smith; Ameet Talwalkar (NeurIPS, 2021)

Rethinking Neural Operations for Diverse Tasks. - Nicholas Roberts; Mikhail Khodak; Tri Dao; Liam Li; Christopher Ré; Ameet Talwalkar (NeurIPS, 2021)

Towards Efficient Automated Machine Learning. - Liam Li (2021)

Cross-Modal Fine-Tuning: Align then Refine. - Junhong Shen; Liam Li; Lucio M. Dery; Corey Staten; Mikhail Khodak; Graham Neubig; Ameet Talwalkar (ICML, 2023)