82 citations · 546 across the 65 of their papers we have counts for
9 papers · 2 filters
On the Convergence Properties of Non-Euclidean Extragradient Methods for Variational Inequalities with Generalized Monotone Operators
Cong D. Dang, Guanghui Lan
In this paper, we study a class of generalized monotone variational inequality (GMVI) problems whose operators are not necessarily monotone (e.g., pseudo-monotone). We present non-…
Accelerated Gradient Methods for Nonconvex Nonlinear and Stochastic Programming
Saeed Ghadimi, Guanghui Lan
In this paper, we generalize the well-known Nesterov's accelerated gradient (AG) method, originally designed for convex smooth optimization, to solve nonconvex and possibly stochas…
Stochastic First- and Zeroth-order Methods for Nonconvex Stochastic Programming
Saeed Ghadimi, Guanghui Lan
In this paper, we introduce a new stochastic approximation (SA) type algorithm, namely the randomized stochastic gradient (RSG) method, for solving an important class of nonlinear…
Optimal Primal-Dual Methods for a Class of Saddle Point Problems
Yunmei Chen, Guanghui Lan, Yuyuan Ouyang
We present a novel accelerated primal-dual (APD) method for solving a class of deterministic and stochastic saddle point problems (SPP). The basic idea of this algorithm is to inco…
Bundle-Level Type Methods Uniformly Optimal for Smooth and Nonsmooth Convex Optimization
Guanghui Lan
The main goal of this paper is to develop uniformly optimal first-order methods for convex programming (CP). By uniform optimality we mean that the first-order methods themselves d…
Linearly Convergent First-Order Algorithms for Semi-definite Programming
Cong D. Dang, Guanghui Lan
In this paper, we consider two formulations for Linear Matrix Inequalities (LMIs) under Slater type constraint qualification assumption, namely, SDP smooth and non-smooth formulati…