Guanghui (George) Lan
Title
Cited by
Cited by
Year
Robust stochastic approximation approach to stochastic programming
A Nemirovski, A Juditsky, G Lan, A Shapiro
SIAM Journal on optimization 19 (4), 1574-1609, 2009
15242009
Stochastic first-and zeroth-order methods for nonconvex stochastic programming
S Ghadimi, G Lan
SIAM Journal on Optimization 23 (4), 2341-2368, 2013
5132013
An optimal method for stochastic composite optimization
G Lan
Mathematical Programming 133 (1-2), 365-397, 2012
3562012
Accelerated gradient methods for nonconvex nonlinear and stochastic programming
S Ghadimi, G Lan
Mathematical Programming 156 (1-2), 59-99, 2016
3162016
Optimal Stochastic Approximation Algorithms for Strongly Convex Stochastic Composite Optimization, I: a Generic Algorithmic Framework
S Ghadimi, G Lan
221*
Mini-batch stochastic approximation methods for nonconvex stochastic composite optimization
S Ghadimi, G Lan, H Zhang
Mathematical Programming 155 (1-2), 267-305, 2016
1842016
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
1782007
Primal-dual first-order methods with iteration-complexity for cone programming
G Lan, Z Lu, RDC Monteiro
Mathematical Programming 126 (1), 1-29, 2011
1722011
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
1482015
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
1482014
An optimal randomized incremental gradient method
G Lan, Y Zhou
Mathematical programming 171 (1-2), 167-215, 2018
1402018
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
135*
Validation analysis of mirror descent stochastic approximation method
G Lan, A Nemirovski, A Shapiro
Mathematical programming 134 (2), 425-458, 2012
1142012
Communication-efficient algorithms for decentralized and stochastic optimization
G Lan, S Lee, Y Zhou
Mathematical Programming, 1-48, 2018
932018
Stochastic block mirror descent methods for nonsmooth and stochastic optimization
CD Dang, G Lan
SIAM Journal on Optimization 25 (2), 856-881, 2015
802015
Conditional gradient sliding for convex optimization
G Lan, Y Zhou
SIAM Journal on Optimization 26 (2), 1379-1409, 2016
782016
Iteration-complexity of first-order augmented Lagrangian methods for convex programming
G Lan, RDC Monteiro
Mathematical Programming 155 (1-2), 511-547, 2016
73*2016
The complexity of large-scale convex programming under a linear optimization oracle
G Lan
arXiv preprint arXiv:1309.5550, 2013
732013
Bundle-level type methods uniformly optimal for smooth and nonsmooth convex optimization
G Lan
Mathematical Programming 149 (1-2), 1-45, 2015
66*2015
On the effectiveness of incorporating randomness and memory into a multi-start metaheuristic with application to the set covering problem
G Lan, GW DePuy
Computers & Industrial Engineering 51 (3), 362-374, 2006
502006
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Articles 1–20