Guanghui Lan

ORCID

Publication Activity (10 Years)

Years Active: 2006-2024
Publications (10 Years): 82

Top Venues

Publications

Yan Li, Guanghui Lan, Tuo Zhao
Homotopic policy mirror descent: policy convergence, algorithmic regularization, and improved sample complexity. Math. Program. 207 (1) (2024)
Guanghui Lan, Alexander Shapiro
Numerical Methods for Convex Multistage Stochastic Optimization. Found. Trends Optim. 6 (2) (2024)
Tianjiao Li, Ziwei Guan, Shaofeng Zou, Tengyu Xu, Yingbin Liang, Guanghui Lan
Faster algorithm and sharper analysis for constrained Markov decision process. Oper. Res. Lett. 54 (2024)
Guanghui Lan
Policy mirror descent for reinforcement learning: linear convergence, new sampling complexity, and generalized problem classes. Math. Program. 198 (1) (2023)
Guanghui Lan, Zhe Zhang
Optimal Methods for Convex Risk-Averse Distributed Optimization. SIAM J. Optim. 33 (3) (2023)
Guanghui Lan, Yan Li, Tuo Zhao
Block Policy Mirror Descent. SIAM J. Optim. 33 (3) (2023)
Zi Xu, Huiling Zhang, Yang Xu, Guanghui Lan
A unified single-loop alternating gradient projection algorithm for nonconvex-concave and convex-nonconcave minimax problems. Math. Program. 201 (1) (2023)
Digvijay Boob, Qi Deng, Guanghui Lan
Stochastic first-order methods for convex and nonconvex functional constrained optimization. Math. Program. 197 (1) (2023)
Tianjiao Li, Guanghui Lan, Ashwin Pananjady
Accelerated and Instance-Optimal Policy Evaluation with Linear Function Approximation. SIAM J. Math. Data Sci. 5 (1) (2023)
Guanghui Lan, Alexander Shapiro
Numerical Methods for Convex Multistage Stochastic Optimization. CoRR (2023)
Tianjiao Li, Guanghui Lan
A simple uniformly optimal method without line search for convex optimization. CoRR (2023)
Yan Li, Guanghui Lan
Policy Mirror Descent Inherently Explores Action Space. CoRR (2023)
Yan Li, Guanghui Lan
First-order Policy Optimization for Robust Policy Evaluation. CoRR (2023)
Guanghui Lan, Yuyuan Ouyang, Yi Zhou
Graph Topology Invariant Gradient and Sampling Complexity for Decentralized and Stochastic Optimization. SIAM J. Optim. 33 (3) (2023)
Sasila Ilandarideva, Anatoli B. Juditsky, Guanghui Lan, Tianjiao Li
Accelerated stochastic approximation with state-dependent noise. CoRR (2023)
Guanghui Lan
Complexity of stochastic dual dynamic programming. Math. Program. 191 (2) (2022)
Tianjiao Li, Feiyang Wu, Guanghui Lan
Stochastic first-order methods for average-reward Markov decision processes. CoRR (2022)
Yi Cheng, Guanghui Lan, H. Edwin Romeijn
Functional Constrained Optimization for Risk Aversion and Sparsity Control. CoRR (2022)
Shuoguang Yang, Xudong Li, Guanghui Lan
Data-Driven Minimax Optimization with Expectation Constraints. CoRR (2022)
Georgios Kotsalis, Guanghui Lan, Tianjiao Li
Simple and Optimal Methods for Stochastic Variational Inequalities, II: Markovian Noise and Policy Evaluation in Reinforcement Learning. SIAM J. Optim. 32 (2) (2022)
Digvijay Boob, Santanu S. Dey, Guanghui Lan
Complexity of training ReLU neural network. Discret. Optim. 44 (Part) (2022)
Yan Li, Tuo Zhao, Guanghui Lan
First-order Policy Optimization for Robust Markov Decision Process. CoRR (2022)
Guanghui Lan, Yan Li, Tuo Zhao
Block Policy Mirror Descent. CoRR (2022)
Guanghui Lan, Yuyuan Ouyang
Accelerated gradient sliding for structured convex optimization. Comput. Optim. Appl. 82 (2) (2022)
Yan Li, Dhruv Choudhary, Xiaohan Wei, Baichuan Yuan, Bhargav Bhushanam, Tuo Zhao, Guanghui Lan
Frequency-aware SGD for Efficient Embedding Learning with Provable Benefits. ICLR (2022)
Guanghui Lan
Policy Optimization over General State and Action Spaces. CoRR (2022)
Guanghui Lan, Zhe Zhang
Optimal Methods for Risk Averse Distributed Optimization. CoRR (2022)
Georgios Kotsalis, Guanghui Lan, Tianjiao Li
Simple and Optimal Methods for Stochastic Variational Inequalities, I: Operator Extrapolation. SIAM J. Optim. 32 (3) (2022)
Guanghui Lan
Correction to: Complexity of stochastic dual dynamic programming. Math. Program. 194 (1) (2022)
Yan Li, Tuo Zhao, Guanghui Lan
Homotopic Policy Mirror Descent: Policy Convergence, Implicit Regularization, and Improved Sample Complexity. CoRR (2022)
Georgios Kotsalis, Guanghui Lan, Arkadi S. Nemirovsky
Convex Optimization for Finite-Horizon Robust Covariance Control of Linear Stochastic Systems. SIAM J. Control. Optim. 59 (1) (2021)
Tengyu Xu, Yingbin Liang, Guanghui Lan
CRPO: A New Approach for Safe Reinforcement Learning with Convergence Guarantee. ICML (2021)
Zhe Zhang, Shabbir Ahmed, Guanghui Lan
Efficient Algorithms for Distributionally Robust Stochastic Optimization with Discrete Scenario Support. SIAM J. Optim. 31 (3) (2021)
Guanghui Lan, Zhiqiang Zhou
Dynamic stochastic approximation for multi-stage stochastic optimization. Math. Program. 187 (1) (2021)
Tianjiao Li, Guanghui Lan, Ashwin Pananjady
Accelerated and instance-optimal policy evaluation with linear function approximation. CoRR (2021)
Guanghui Lan, Yi Zhou
Asynchronous Decentralized Accelerated Stochastic Gradient Descent. IEEE J. Sel. Areas Inf. Theory 2 (2) (2021)
Yan Li, Dhruv Choudhary, Xiaohan Wei, Baichuan Yuan, Bhargav Bhushanam, Tuo Zhao, Guanghui Lan
Frequency-aware SGD for Efficient Embedding Learning with Provable Benefits. CoRR (2021)
Guanghui Lan, Edwin Romeijn, Zhiqiang Zhou
Conditional Gradient Methods for Convex Optimization with General Affine and Nonlinear Constraints. SIAM J. Optim. 31 (3) (2021)
Tianjiao Li, Ziwei Guan, Shaofeng Zou, Tengyu Xu, Yingbin Liang, Guanghui Lan
Faster Algorithm and Sharper Analysis for Constrained Markov Decision Process. CoRR (2021)
Guanghui Lan
Policy Mirror Descent for Reinforcement Learning: Linear Convergence, New Sampling Complexity, and Generalized Problem Classes. CoRR (2021)
Zhe Zhang, Guanghui Lan
Optimal Algorithms for Convex Nested Stochastic Composite Optimization. CoRR (2020)
Digvijay Boob, Qi Deng, Guanghui Lan, Yilin Wang
A Feasible Level Proximal Point Method for Nonconvex Sparse Constrained Optimization. NeurIPS (2020)
Guanghui Lan, Zhiqiang Zhou
Algorithms for stochastic optimization with function or expectation constraints. Comput. Optim. Appl. 76 (2) (2020)
Guanghui Lan, Edwin Romeijn, Zhiqiang Zhou
Conditional Gradient Methods for Convex Optimization with Function Constraints. CoRR (2020)
Georgios Kotsalis, Guanghui Lan, Tianjiao Li
Simple and optimal methods for stochastic variational inequalities, I: operator extrapolation. CoRR (2020)
Tengyu Xu, Yingbin Liang, Guanghui Lan
A Primal Approach to Constrained Policy Optimization: Global Optimality and Finite-Time Analysis. CoRR (2020)
Georgios Kotsalis, Guanghui Lan, Tianjiao Li
Simple and optimal methods for stochastic variational inequalities, II: Markovian noise and policy evaluation in reinforcement learning. CoRR (2020)
Guanghui Lan, Soomin Lee, Yi Zhou
Communication-efficient algorithms for decentralized and stochastic optimization. Math. Program. 180 (1) (2020)
Harsh Shrivastava, Xinshi Chen, Binghong Chen, Guanghui Lan, Srinivas Aluru, Han Liu, Le Song
GLAD: Learning Sparse Graph Recovery. ICLR (2020)
Zi Xu, Huiling Zhang, Yang Xu, Guanghui Lan
A Unified Single-loop Alternating Gradient Projection Algorithm for Nonconvex-Concave and Convex-Nonconcave Minimax Problems. CoRR (2020)
Digvijay Boob, Qi Deng, Guanghui Lan, Yilin Wang
A Feasible Level Proximal Point Method for Nonconvex Sparse Constrained Optimization. CoRR (2020)
Saeed Ghadimi, Guanghui Lan, Hongchao Zhang
Generalized Uniformly Optimal Methods for Nonlinear Programming. J. Sci. Comput. 79 (3) (2019)
Guanghui Lan, Yu Yang
Accelerated Stochastic Algorithms for Nonconvex Finite-Sum and Multiblock Optimization. SIAM J. Optim. 29 (4) (2019)
Zhe Wang, Yi Zhou, Yingbin Liang, Guanghui Lan
A note on inexact gradient and Hessian conditions for cubic regularized Newton's method. Oper. Res. Lett. 47 (2) (2019)
Yunmei Chen, Guanghui Lan, Yuyuan Ouyang, Wei Zhang
Fast bundle-level methods for unconstrained and ball-constrained convex optimization. Comput. Optim. Appl. 73 (1) (2019)
Guanghui Lan, Zhize Li, Yi Zhou
A unified variance-reduced accelerated gradient method for convex optimization. CoRR (2019)
Guanghui Lan, Zhize Li, Yi Zhou
A unified variance-reduced accelerated gradient method for convex optimization. NeurIPS (2019)
Zhe Wang, Yi Zhou, Yingbin Liang, Guanghui Lan
Stochastic Variance-Reduced Cubic Regularization for Nonconvex Optimization. AISTATS (2019)
Digvijay Boob, Qi Deng, Guanghui Lan
Proximal Point Methods for Optimization with Nonconvex Functional Constraints. CoRR (2019)
Zhe Wang, Yi Zhou, Yingbin Liang, Guanghui Lan
Cubic Regularization with Momentum for Nonconvex Optimization. UAI (2019)
Guanghui Lan
Complexity of Stochastic Dual Dynamic Programming. CoRR (2019)
Harsh Shrivastava, Xinshi Chen, Binghong Chen, Guanghui Lan, Srinivas Aluru, Le Song
GLAD: Learning Sparse Graph Recovery. CoRR (2019)
Zhe Wang, Yi Zhou, Yingbin Liang, Guanghui Lan
Sample Complexity of Stochastic Variance-Reduced Cubic Regularization for Nonconvex Optimization. CoRR (2018)
Zhe Wang, Yi Zhou, Yingbin Liang, Guanghui Lan
A Note on Inexact Condition for Cubic Regularized Newton's Method. CoRR (2018)
Zhe Wang, Yi Zhou, Yingbin Liang, Guanghui Lan
Cubic Regularization with Momentum for Nonconvex Optimization. CoRR (2018)
Digvijay Boob, Santanu S. Dey, Guanghui Lan
Complexity of Training ReLU Neural Network. CoRR (2018)
Guanghui Lan, Yi Zhou
Random Gradient Extrapolation for Distributed and Stochastic Optimization. SIAM J. Optim. 28 (4) (2018)
Guanghui Lan, Yi Zhou
Asynchronous decentralized accelerated stochastic gradient descent. CoRR (2018)
Guanghui Lan, Yi Zhou
An optimal randomized incremental gradient method. Math. Program. 171 (1-2) (2018)
Qi Deng, Yi Cheng, Guanghui Lan
Optimal Adaptive and Accelerated Stochastic Gradient Descent. CoRR (2018)
Guanghui Lan, Sebastian Pokutta, Yi Zhou, Daniel Zink
Conditional Accelerated Lazy Stochastic Gradient Descent. CoRR (2017)
Guanghui Lan, Zhiqiang Zhou
Dynamic Stochastic Approximation for Multi-stage Stochastic Optimization. CoRR (2017)
Yunmei Chen, Guanghui Lan, Yuyuan Ouyang
Accelerated schemes for a class of variational inequalities. Math. Program. 165 (1) (2017)
Guanghui Lan, Soomin Lee, Yi Zhou
Communication-Efficient Algorithms for Decentralized and Stochastic Optimization. CoRR (2017)
Guanghui Lan, Sebastian Pokutta, Yi Zhou, Daniel Zink
Conditional Accelerated Lazy Stochastic Gradient Descent. ICML (2017)
Guanghui Lan, Yi Zhou
Random gradient extrapolation for distributed and stochastic optimization. CoRR (2017)
Digvijay Boob, Guanghui Lan
Theoretical properties of the global optimizer of two layer neural network. CoRR (2017)
Saeed Ghadimi, Guanghui Lan
Accelerated gradient methods for nonconvex nonlinear and stochastic programming. Math. Program. 156 (1-2) (2016)
Guanghui Lan
Gradient sliding for composite optimization. Math. Program. 159 (1-2) (2016)
Guanghui Lan, Yi Zhou
Conditional Gradient Sliding for Convex Optimization. SIAM J. Optim. 26 (2) (2016)
Saeed Ghadimi, Guanghui Lan, Hongchao Zhang
Mini-batch stochastic approximation methods for nonconvex stochastic composite optimization. Math. Program. 155 (1-2) (2016)
Guanghui Lan, Renato D. C. Monteiro
Iteration-complexity of first-order augmented Lagrangian methods for convex programming. Math. Program. 155 (1-2) (2016)
Cong D. Dang, Guanghui Lan
Stochastic Block Mirror Descent Methods for Nonsmooth and Stochastic Optimization. SIAM J. Optim. 25 (2) (2015)
Guanghui Lan
Bundle-level type methods uniformly optimal for smooth and nonsmooth convex optimization. Math. Program. 149 (1-2) (2015)
Cong D. Dang, Guanghui Lan
On the convergence properties of non-Euclidean extragradient methods for variational inequalities with generalized monotone operators. Comput. Optim. Appl. 60 (2) (2015)
Yuyuan Ouyang, Yunmei Chen, Guanghui Lan, Eduardo Pasiliao Jr.
An Accelerated Linearized Alternating Direction Method of Multipliers. SIAM J. Imaging Sci. 8 (1) (2015)
Guanghui Lan, Yi Zhou
An optimal randomized incremental gradient method. CoRR (2015)
Hao Zhang, Justin C. Park, Yunmei Chen, Guanghui Lan, Bo Lu
A novel method for 4D cone-beam computer-tomography reconstruction. Medical Imaging: Image Processing (2015)
Yunmei Chen, Guanghui Lan, Yuyuan Ouyang
Optimal Primal-Dual Methods for a Class of Saddle Point Problems. SIAM J. Optim. 24 (4) (2014)
Cong D. Dang, Kaiyu Dai, Guanghui Lan
A linearly convergent first-order algorithm for total variation minimisation in image processing. Int. J. Bioinform. Res. Appl. 10 (1) (2014)
Guanghui Lan
Gradient Sliding for Composite Optimization. CoRR (2014)
Saeed Ghadimi, Guanghui Lan
Stochastic First- and Zeroth-Order Methods for Nonconvex Stochastic Programming. SIAM J. Optim. 23 (4) (2013)
Guanghui Lan, Renato D. C. Monteiro
Iteration-complexity of first-order penalty methods for convex programming. Math. Program. 138 (1-2) (2013)
Saeed Ghadimi, Guanghui Lan
Stochastic First- and Zeroth-order Methods for Nonconvex Stochastic Programming. CoRR (2013)
Saeed Ghadimi, Guanghui Lan
Optimal Stochastic Approximation Algorithms for Strongly Convex Stochastic Composite Optimization, II: Shrinking Procedures and Optimal Algorithms. SIAM J. Optim. 23 (4) (2013)
Guanghui Lan, Arkadi Nemirovski, Alexander Shapiro
Validation analysis of mirror descent stochastic approximation method. Math. Program. 134 (2) (2012)
Saeed Ghadimi, Guanghui Lan
Optimal Stochastic Approximation Algorithms for Strongly Convex Stochastic Composite Optimization I: A Generic Algorithmic Framework. SIAM J. Optim. 22 (4) (2012)
Guanghui Lan
An optimal method for stochastic composite optimization. Math. Program. 133 (1-2) (2012)
Guanghui Lan, Zhaosong Lu, Renato D. C. Monteiro
(1/e) iteration-complexity for cone programming. Math. Program. 126 (1) (2011)
Guanghui Lan, Renato D. C. Monteiro, Takashi Tsuchiya
A Polynomial Predictor-Corrector Trust-Region Algorithm for Linear Programming. SIAM J. Optim. 19 (4) (2009)

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Publication Activity (10 Years)

Top Topics

Top Venues

Guanghui Lan