Підписатись
Guanghui (George) Lan
Guanghui (George) Lan
Professor, Georgia Institute of Technology
Підтверджена електронна адреса в isye.gatech.edu - Домашня сторінка
Назва
Посилання
Посилання
Рік
Robust stochastic approximation approach to stochastic programming
A Nemirovski, A Juditsky, G Lan, A Shapiro
SIAM Journal on optimization 19 (4), 1574-1609, 2009
28732009
Stochastic first-and zeroth-order methods for nonconvex stochastic programming
S Ghadimi, G Lan
SIAM journal on optimization 23 (4), 2341-2368, 2013
18012013
Accelerated gradient methods for nonconvex nonlinear and stochastic programming
S Ghadimi, G Lan
Mathematical Programming 156 (1), 59-99, 2016
6842016
An optimal method for stochastic composite optimization
G Lan
Mathematical Programming 133 (1), 365-397, 2012
6332012
Mini-batch stochastic approximation methods for nonconvex stochastic composite optimization
S Ghadimi, G Lan, H Zhang
Mathematical Programming 155 (1), 267-305, 2016
5532016
First-order and stochastic optimization methods for machine learning
G Lan
Springer, 2020
4702020
Optimal Stochastic Approximation Algorithms for Strongly Convex Stochastic Composite Optimization, I: a Generic Algorithmic Framework
S Ghadimi, G Lan
429*
Optimal primal-dual methods for a class of saddle point problems
Y Chen, G Lan, Y Ouyang
SIAM Journal on Optimization 24 (4), 1779-1814, 2014
2892014
An accelerated linearized alternating direction method of multipliers
Y Ouyang, Y Chen, G Lan, E Pasiliao Jr
SIAM Journal on Imaging Sciences 8 (1), 644-681, 2015
2732015
An optimal randomized incremental gradient method
G Lan, Y Zhou
Mathematical programming 171, 167-215, 2018
2672018
Communication-efficient algorithms for decentralized and stochastic optimization
G Lan, S Lee, Y Zhou
Mathematical Programming 180 (1), 237-284, 2020
2632020
Optimal Stochastic Approximation Algorithms for Strongly Convex Stochastic Composite Optimization, II: Shrinking Procedures and Optimal Algorithms
S Ghadimi, G Lan
Manuscript, Department of Industrial and Systems Engineering, University of …, 0
246*
An effective and simple heuristic for the set covering problem
G Lan, GW DePuy, GE Whitehouse
European journal of operational research 176 (3), 1387-1403, 2007
2342007
Primal-dual first-order methods with iteration-complexity for cone programming
G Lan, Z Lu, RDC Monteiro
Mathematical Programming 126 (1), 1-29, 2011
2232011
Validation analysis of mirror descent stochastic approximation method
G Lan, A Nemirovski, A Shapiro
Mathematical programming 134 (2), 425-458, 2012
1852012
Conditional gradient sliding for convex optimization
G Lan, Y Zhou
SIAM Journal on Optimization 26 (2), 1379-1409, 2016
1822016
Crpo: A new approach for safe reinforcement learning with convergence guarantee
T Xu, Y Liang, G Lan
International Conference on Machine Learning, 11480-11491, 2021
176*2021
Policy mirror descent for reinforcement learning: Linear convergence, new sampling complexity, and generalized problem classes
G Lan
Mathematical programming 198 (1), 1059-1106, 2023
1652023
Accelerated schemes for a class of variational inequalities
Y Chen, G Lan, Y Ouyang
Mathematical Programming 165, 113-149, 2017
1592017
Iteration-complexity of first-order augmented Lagrangian methods for convex programming
G Lan, RDC Monteiro
Mathematical Programming 155 (1), 511-547, 2016
1512016
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