| 2024 | ICLR | How to Fine-Tune Vision Models with SGD. | Ananya Kumar, Ruoqi Shen, Sbastien Bubeck, Suriya Gunasekar |
| 2023 | COLT | Algorithmic Aspects of the Log-Laplace Transform and a Non-Euclidean Proximal Sampler. | Sivakanth Gopi, Yin Tat Lee, Daogao Liu, Ruoqi Shen, Kevin Tian |
| 2023 | COLT | Condition-number-independent Convergence Rate of Riemannian Hamiltonian Monte Carlo with Numerical Integrators. | Yunbum Kook, Yin Tat Lee, Ruoqi Shen, Santosh S. Vempala |
| 2023 | SODA | Private Convex Optimization in General Norms. | Sivakanth Gopi, Yin Tat Lee, Daogao Liu, Ruoqi Shen, Kevin Tian |
| 2022 | COLT | Analysis of Langevin Monte Carlo from Poincare to Log-Sobolev. | Sinho Chewi, Murat A. Erdogdu, Mufan (Bill) Li, Ruoqi Shen, Shunshi Zhang |
| 2022 | ICML | Data Augmentation as Feature Manipulation. | Ruoqi Shen, Sbastien Bubeck, Suriya Gunasekar |
| 2021 | COLT | Structured Logconcave Sampling with a Restricted Gaussian Oracle. | Yin Tat Lee, Ruoqi Shen, Kevin Tian |
| 2021 | UAI | When is particle filtering efficient for planning in partially observed linear dynamical systems? | Simon S. Du, Wei Hu, Zhiyuan Li, Ruoqi Shen, Zhao Song, Jiajun Wu |
| 2020 | COLT | Logsmooth Gradient Concentration and Tighter Runtimes for Metropolized Hamiltonian Monte Carlo. | Yin Tat Lee, Ruoqi Shen, Kevin Tian |