Ruoqi Shen

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All published works

Action	Title	Year	Authors
+	Analysis of Langevin Monte Carlo from Poincaré to Log-Sobolev	2024	Sinho Chewi Murat A. Erdogdu Mufan Li Ruoqi Shen Matthew S. Zhang
+ PDF Chat	Private Convex Optimization in General Norms	2023	Sivakanth Gopi Yin Tat Lee Daogao Liu Ruoqi Shen Kevin Tian
+	Algorithmic Aspects of the Log-Laplace Transform and a Non-Euclidean Proximal Sampler	2023	Sivakanth Gopi Yin Tat Lee Daogao Liu Ruoqi Shen Kevin Tian
+	FiLM: Fill-in Language Models for Any-Order Generation	2023	Tianxiao Shen Hao Peng Ruoqi Shen Yao Fu Zaïd Harchaoui Yejin Choi
+	Positional Description Matters for Transformers Arithmetic	2023	Ruoqi Shen Sébastien Bubeck Ronen Eldan Yin Tat Lee Yuanzhi Li Yi Zhang
+	Data Augmentation as Feature Manipulation	2022	Ruoqi Shen Sébastien Bubeck Suriya Gunasekar
+	On Optimal Early Stopping: Over-informative versus Under-informative Parametrization	2022	Ruoqi Shen Liyao Gao Yi-An Ma
+	Sampling with Riemannian Hamiltonian Monte Carlo in a Constrained Space	2022	Yunbum Kook Yin Tat Lee Ruoqi Shen Santosh Vempala
+	Private Convex Optimization in General Norms	2022	Sivakanth Gopi Yin Tat Lee Daogao Liu Ruoqi Shen Kevin Tian
+	Condition-number-independent convergence rate of Riemannian Hamiltonian Monte Carlo with numerical integrators	2022	Yunbum Kook Yin Tat Lee Ruoqi Shen Santosh Vempala
+	How to Fine-Tune Vision Models with SGD	2022	Ananya Kumar Ruoqi Shen Sébastien Bubeck Suriya Gunasekar
+	Near-Optimal Randomized Exploration for Tabular MDP.	2021	Zhihan Xiong Ruoqi Shen Qiwen Cui Simon S. Du
+ PDF Chat	Lower Bounds on Metropolized Sampling Methods for Well-Conditioned Distributions	2021	Yin Tat Lee Ruoqi Shen Kevin Tian
+	Randomized Exploration is Near-Optimal for Tabular MDP.	2021	Zhihan Xiong Ruoqi Shen Simon S. Du
+	Lower Bounds on Metropolized Sampling Methods for Well-Conditioned Distributions	2021	Yin Tat Lee Ruoqi Shen Kevin Tian
+	Analysis of Langevin Monte Carlo from Poincaré to Log-Sobolev	2021	Sinho Chewi Murat A. Erdogdu Mufan Bill Li Ruoqi Shen Matthew Zhang
+	Near-Optimal Randomized Exploration for Tabular Markov Decision Processes	2021	Zhihan Xiong Ruoqi Shen Qiwen Cui Maryam Fazel Simon S. Du
+	Structured Logconcave Sampling with a Restricted Gaussian Oracle	2020	Yin Tat Lee Ruoqi Shen Kevin Tian
+ PDF Chat	Generalized Leverage Score Sampling for Neural Networks	2020	Jason D. Lee Ruoqi Shen Zhao Song Mengdi Wang Zheng Yu
+	When is Particle Filtering Efficient for POMDP Sequential Planning	2020	Simon S. Du Wei Hu Zhiyuan Li Ruoqi Shen Zhao Song Jia-Jun Wu
+	Logsmooth Gradient Concentration and Tighter Runtimes for Metropolized Hamiltonian Monte Carlo	2020	Yin Tat Lee Ruoqi Shen Kevin Tian
+	Composite Logconcave Sampling with a Restricted Gaussian Oracle	2020	Ruoqi Shen Kevin Tian Yin Tat Lee
+	Logsmooth Gradient Concentration and Tighter Runtimes for Metropolized Hamiltonian Monte Carlo	2020	Yin Tat Lee Ruoqi Shen Kevin Tian
+	Generalized Leverage Score Sampling for Neural Networks	2020	Jason Dean Lee Ruoqi Shen Zhao Song Mengdi Wang Yu Zheng
+	Structured Logconcave Sampling with a Restricted Gaussian Oracle	2020	Yin Tat Lee Ruoqi Shen Kevin Tian
+	When is Particle Filtering Efficient for Planning in Partially Observed Linear Dynamical Systems?	2020	Simon S. Du Wei Hu Zhiyuan Li Ruoqi Shen Zhao Song Jia-Jun Wu
+	The Randomized Midpoint Method for Log-Concave Sampling	2019	Ruoqi Shen Yin Tat Lee
+	The Randomized Midpoint Method for Log-Concave Sampling	2019	Ruoqi Shen Yin Tat Lee

Common Coauthors

Coauthor	Papers Together
Yin Tat Lee	12
Kevin Tian	6
Simon S. Du	5
Kevin Tian	4
Sivakanth Gopi	3
Daogao Liu	3
Zhihan Xiong	3
Sébastien Bubeck	3
Zhao Song	3
Yunbum Kook	2
Qiwen Cui	2
Yin Tat Lee	2
Jia-Jun Wu	2
Suriya Gunasekar	2
Sinho Chewi	2
Murat A. Erdogdu	2
Zhiyuan Li	2
Mengdi Wang	2
Yi Zhang	1
Yu Zheng	1
Wei Hu	1
Zheng Yu	1
Santosh Vempala	1
Maryam Fazel	1
Yejin Choi	1
Mufan Li	1
Santosh Vempala	1
Jason Dean Lee	1
Tianxiao Shen	1
Zhao Song	1
Zaïd Harchaoui	1
Liyao Gao	1
Ronen Eldan	1
Wei Hu	1
Ananya Kumar	1
Yin Tat Lee	1
Yi-An Ma	1
Hao Peng	1
Matthew Zhang	1
Jason D. Lee	1
Mufan Bill Li	1
Yuanzhi Li	1
Matthew S. Zhang	1
Yao Fu	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	On sampling from a log-concave density using kinetic Langevin diffusions	2018	Arnak S. Dalalyan Lionel Riou-Durand	4
+ PDF Chat	High-dimensional Bayesian inference via the unadjusted Langevin algorithm	2019	Alain Durmus Éric Moulines	4
+	Algorithmic Theory of ODEs and Sampling from Well-conditioned Logconcave Densities.	2018	Yin Tat Lee Zhao Song Santosh Vempala	4
+	Optimal Convergence Rate of Hamiltonian Monte Carlo for Strongly Logconcave Distributions	2019	Zongchen Chen Santosh Vempala	3
+	High-Order Langevin Diffusion Yields an Accelerated MCMC Algorithm	2021	Wenlong Mou Yi-An Ma Martin J. Wainwright Peter L. Bartlett Michael I. Jordan	3
+	Spatial Point Processes	2011	Mark Huber	3
+ PDF Chat	Proximal Markov chain Monte Carlo algorithms	2015	Marcelo Pereyra	3
+	Analysis of Langevin Monte Carlo via Convex Optimization	2019	Alain Durmus Szymon Majewski Błażej Miasojedow	3
+	Underdamped Langevin MCMC: A non-asymptotic analysis	2017	Xiang Cheng Niladri S. Chatterji Peter L. Bartlett Michael I. Jordan	3
+	Fast mixing of Metropolized Hamiltonian Monte Carlo: Benefits of multi-step gradients	2020	Yuansi Chen Raaz Dwivedi Martin J. Wainwright Bin Yu	3
+	Hit-and-Run from a Corner	2006	László Lovász Santosh Vempala	3
+	Fast Algorithms for Logconcave Functions: Sampling, Rounding, Integration and Optimization	2006	László Lovász Santosh Vempala	2
+	Analysis and Geometry of Markov Diffusion Operators	2013	Dominique Bakry Ivan Gentil Michel Ledoux	2
+	REGAL: A Regularization based Algorithm for Reinforcement Learning in Weakly Communicating MDPs	2012	Peter L. Bartlett Ambuj Tewari	2
+	$Q$-learning with Logarithmic Regret	2020	Kunhe Yang Lin F. Yang Simon S. Du	2
+	Model-Free Reinforcement Learning: from Clipped Pseudo-Regret to Sample Complexity	2020	Zihan Zhang Yuan Zhou Xiangyang Ji	2
+	Is Reinforcement Learning More Difficult Than Bandits? A Near-optimal Algorithm Escaping the Curse of Horizon	2020	Zihan Zhang Xiangyang Ji Simon S. Du	2
+	Langevin Monte Carlo and JKO splitting.	2018	Espen Bernton	2
+ PDF Chat	Sampling from a Log-Concave Distribution with Projected Langevin Monte Carlo	2018	Sébastien Bubeck Ronen Eldan Joseph Lehec	2
+	Worst-Case Regret Bounds for Exploration via Randomized Value Functions	2019	Daniel Russo	2
+	Mirrored Langevin Dynamics	2018	Ya-Ping Hsieh Ali Kavis Paul Rolland Volkan Cevher	2
+	The Randomized Midpoint Method for Log-Concave Sampling	2019	Ruoqi Shen Yin Tat Lee	2
+	Almost Optimal Model-Free Reinforcement Learning via Reference-Advantage Decomposition	2020	Zihan Zhang Yuan Zhou Xiangyang Ji	2
+	Is Long Horizon Reinforcement Learning More Difficult Than Short Horizon Reinforcement Learning?	2020	Ruosong Wang Simon S. Du Lin F. Yang Sham M. Kakade	2
+	Q-learning with UCB Exploration is Sample Efficient for Infinite-Horizon MDP	2019	Kefan Dong Yuanhao Wang Xiaoyu Chen Liwei Wang	2
+	On Optimism in Model-Based Reinforcement Learning.	2020	Aldo Pacchiano Philip Ball Jack Parker-Holder Krzysztof Choromański Stephen Roberts	2
+	Why is Posterior Sampling Better than Optimism for Reinforcement Learning?	2016	Ian Osband Benjamin Van Roy	2
+	An Efficient Sampling Algorithm for Non-smooth Composite Potentials	2019	Wenlong Mou Nicolas Flammarion Martin J. Wainwright Peter L. Bartlett	2
+	Log-concave sampling: Metropolis-Hastings algorithms are fast	2018	Raaz Dwivedi Yuansi Chen Martin J. Wainwright Bin Yu	2
+	MOTS: Minimax Optimal Thompson Sampling	2020	Tianyuan Jin Pan Xu J. Y. Shi Xiaokui Xiao Quanquan Gu	2
+	Random walks in a convex body and an improved volume algorithm	1993	László Lovász Miklós Simonovits	2
+	Simulated annealing in convex bodies and an <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si1.gif" overflow="scroll"><mml:msup><mml:mrow><mml:mi>O</mml:mi></mml:mrow><mml:mrow><mml:mo>*</mml:mo></mml:mrow></mml:msup><mml:mo stretchy="false">(</mml:mo><mml:msup><mml:mrow><mml:mi>n</mml:mi></mml:mrow><mml:mrow><mml:mn>4</mml:mn></mml:mrow></mml:msup><mml:mo stretchy="false">)</mml:mo></mml:math> volume algorithm	2005	László Lovász Santosh Vempala	2
+ PDF Chat	Blocking Conductance and Mixing in Random Walks	2006	Ravi Kannan László Lovász Ravi Montenegro	2
+ PDF Chat	PAC Bounds for Discounted MDPs	2012	Tor Lattimore Marcus Hütter	2
+	Regression Shrinkage and Selection Via the Lasso	1996	Robert Tibshirani	2
+	A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems	2009	Amir Beck Marc Teboulle	2
+	Solving convex programs by random walks	2004	Dimitris Bertsimas Santosh Vempala	2
+	Rapid Mixing of Hamiltonian Monte Carlo on Strongly Log-Concave Distributions	2017	Oren Mangoubi Aaron Smith	2
+ PDF Chat	Prior-free and prior-dependent regret bounds for Thompson Sampling	2014	Sébastien Bubeck Che-Yu Liu	2
+	Exploration by Random Network Distillation.	2018	Yuri Burda Harrison Edwards Amos Storkey Oleg Klimov	2
+	Proximal Langevin Algorithm: Rapid Convergence Under Isoperimetry	2019	Andre Wibisono	2
+ PDF Chat	A random polynomial-time algorithm for approximating the volume of convex bodies	1991	Martin Dyer Alan Frieze Ravi Kannan	2
+ PDF Chat	Bayesian Reasoning and Machine Learning	2012	David Barber	2
+	User-friendly guarantees for the Langevin Monte Carlo with inaccurate gradient	2019	Arnak S. Dalalyan Avetik Karagulyan	2
+	Coercive Inequalities for Gibbs Measures	1999	Lorenzo Bertini Bogusław Zegarliński	1
+ PDF Chat	Approximation of zonoids by zonotopes	1989	Jean Bourgain Joram Lindenstrauss Vitali Milman	1
+	On the role of interaction in sequential Monte Carlo algorithms	2015	Nick Whiteley Anthony Lee Kari Heine	1
+ PDF Chat	Weighted Csiszár-Kullback-Pinsker inequalities and applications to transportation inequalities	2005	François Bolley Cédric Villani	1
+	Geometric Random Walks: a Survey	2007	Santosh Vempala	1
+ PDF Chat	Sparse regression learning by aggregation and Langevin Monte-Carlo	2012	Arnak S. Dalalyan A. B. Tsybakov	1