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2020 – today
- 2024
[c14]Ananya Kumar, Ruoqi Shen, Sébastien Bubeck, Suriya Gunasekar:
How to Fine-Tune Vision Models with SGD. ICLR 2024- 2023
- [c13]Sivakanth Gopi, Yin Tat Lee, Daogao Liu, Ruoqi Shen, Kevin Tian:
Algorithmic Aspects of the Log-Laplace Transform and a Non-Euclidean Proximal Sampler. COLT 2023: 2399-2439 - [c12]Yunbum Kook, Yin Tat Lee, Ruoqi Shen, Santosh S. Vempala:
Condition-number-independent Convergence Rate of Riemannian Hamiltonian Monte Carlo with Numerical Integrators. COLT 2023: 4504-4569 - [c11]Sivakanth Gopi, Yin Tat Lee, Daogao Liu, Ruoqi Shen, Kevin Tian:
Private Convex Optimization in General Norms. SODA 2023: 5068-5089 - [i17]Sivakanth Gopi, Yin Tat Lee, Daogao Liu, Ruoqi Shen, Kevin Tian:
Algorithmic Aspects of the Log-Laplace Transform and a Non-Euclidean Proximal Sampler. CoRR abs/2302.06085 (2023) - [i16]Tianxiao Shen, Hao Peng, Ruoqi Shen, Yao Fu, Zaïd Harchaoui, Yejin Choi:
FiLM: Fill-in Language Models for Any-Order Generation. CoRR abs/2310.09930 (2023) - [i15]Ruoqi Shen, Sébastien Bubeck, Ronen Eldan, Yin Tat Lee, Yuanzhi Li, Yi Zhang:
Positional Description Matters for Transformers Arithmetic. CoRR abs/2311.14737 (2023) - 2022
- [c10]Sinho Chewi, Murat A. Erdogdu, Mufan (Bill) Li, Ruoqi Shen, Shunshi Zhang:
Analysis of Langevin Monte Carlo from Poincare to Log-Sobolev. COLT 2022: 1-2 - [c9]Ruoqi Shen, Sébastien Bubeck, Suriya Gunasekar:
Data Augmentation as Feature Manipulation. ICML 2022: 19773-19808 - [c8]Yunbum Kook, Yin Tat Lee, Ruoqi Shen, Santosh S. Vempala:
Sampling with Riemannian Hamiltonian Monte Carlo in a Constrained Space. NeurIPS 2022 - [c7]Zhihan Xiong, Ruoqi Shen, Qiwen Cui, Maryam Fazel, Simon S. Du:
Near-Optimal Randomized Exploration for Tabular Markov Decision Processes. NeurIPS 2022 - [i14]Yunbum Kook, Yin Tat Lee, Ruoqi Shen, Santosh S. Vempala:
Sampling with Riemannian Hamiltonian Monte Carlo in a Constrained Space. CoRR abs/2202.01908 (2022) - [i13]Ruoqi Shen, Liyao Gao, Yi-An Ma:
On Optimal Early Stopping: Over-informative versus Under-informative Parametrization. CoRR abs/2202.09885 (2022) - [i12]Ruoqi Shen, Sébastien Bubeck, Suriya Gunasekar:
Data Augmentation as Feature Manipulation: a story of desert cows and grass cows. CoRR abs/2203.01572 (2022) - [i11]Sivakanth Gopi, Yin Tat Lee, Daogao Liu, Ruoqi Shen, Kevin Tian:
Private Convex Optimization in General Norms. CoRR abs/2207.08347 (2022) - [i10]Yunbum Kook, Yin Tat Lee, Ruoqi Shen, Santosh S. Vempala:
Condition-number-independent Convergence Rate of Riemannian Hamiltonian Monte Carlo with Numerical Integrators. CoRR abs/2210.07219 (2022) - [i9]Ananya Kumar, Ruoqi Shen, Sébastien Bubeck, Suriya Gunasekar:
How to Fine-Tune Vision Models with SGD. CoRR abs/2211.09359 (2022) - 2021
- [c6]Yin Tat Lee, Ruoqi Shen, Kevin Tian:
Structured Logconcave Sampling with a Restricted Gaussian Oracle. COLT 2021: 2993-3050 - [c5]Yin Tat Lee, Ruoqi Shen, Kevin Tian:
Lower Bounds on Metropolized Sampling Methods for Well-Conditioned Distributions. NeurIPS 2021: 18812-18824 - [c4]Simon S. Du, Wei Hu, Zhiyuan Li
, Ruoqi Shen, Zhao Song, Jiajun Wu:
When is particle filtering efficient for planning in partially observed linear dynamical systems? UAI 2021: 728-737 - [i8]Zhihan Xiong, Ruoqi Shen, Simon S. Du:
Randomized Exploration is Near-Optimal for Tabular MDP. CoRR abs/2102.09703 (2021) - [i7]Yin Tat Lee, Ruoqi Shen, Kevin Tian:
Lower Bounds on Metropolized Sampling Methods for Well-Conditioned Distributions. CoRR abs/2106.05480 (2021) - 2020
- [c3]Yin Tat Lee, Ruoqi Shen, Kevin Tian:
Logsmooth Gradient Concentration and Tighter Runtimes for Metropolized Hamiltonian Monte Carlo. COLT 2020: 2565-2597 - [c2]Jason D. Lee, Ruoqi Shen, Zhao Song, Mengdi Wang, Zheng Yu:
Generalized Leverage Score Sampling for Neural Networks. NeurIPS 2020 - [i6]Yin Tat Lee, Ruoqi Shen, Kevin Tian:
Logsmooth Gradient Concentration and Tighter Runtimes for Metropolized Hamiltonian Monte Carlo. CoRR abs/2002.04121 (2020) - [i5]Simon S. Du, Wei Hu, Zhiyuan Li, Ruoqi Shen, Zhao Song, Jiajun Wu:
When is Particle Filtering Efficient for POMDP Sequential Planning? CoRR abs/2006.05975 (2020) - [i4]Ruoqi Shen, Kevin Tian, Yin Tat Lee:
Composite Logconcave Sampling with a Restricted Gaussian Oracle. CoRR abs/2006.05976 (2020) - [i3]Jason D. Lee, Ruoqi Shen, Zhao Song, Mengdi Wang, Zheng Yu:
Generalized Leverage Score Sampling for Neural Networks. CoRR abs/2009.09829 (2020) - [i2]Yin Tat Lee, Ruoqi Shen, Kevin Tian:
Structured Logconcave Sampling with a Restricted Gaussian Oracle. CoRR abs/2010.03106 (2020)
2010 – 2019
- 2019
- [c1]Ruoqi Shen, Yin Tat Lee:
The Randomized Midpoint Method for Log-Concave Sampling. NeurIPS 2019: 2098-2109 - [i1]Ruoqi Shen, Yin Tat Lee:
The Randomized Midpoint Method for Log-Concave Sampling. CoRR abs/1909.05503 (2019)
Coauthor Index
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