27 citations · 31 across the 3 of their papers we have counts for
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math.OC2020★ 1 cited
Conditional Gradient Methods for Convex Optimization with General Affine and Nonlinear Constraints
Guanghui Lan, Edwin Romeijn, Zhiqiang Zhou
Conditional gradient methods have attracted much attention in both machine learning and optimization communities recently. These simple methods can guarantee the generation of spar…
math.OC2017★ 3 cited
Dynamic Stochastic Approximation for Multi-stage Stochastic Optimization
Guanghui Lan, Zhiqiang Zhou
In this paper, we consider multi-stage stochastic optimization problems with convex objectives and conic constraints at each stage. We present a new stochastic first-order method,…
math.OC2016★ 27 cited
Algorithms for stochastic optimization with functional or expectation constraints
Guanghui Lan, Zhiqiang Zhou
This paper considers the problem of minimizing an expectation function over a closed convex set, coupled with a {\color{black} functional or expectation} constraint on either decis…