82 citations · 546 across the 65 of their papers we have counts for
5 papers · 1 filter
Complexity of Stochastic Dual Dynamic Programming
Guanghui Lan
Stochastic dual dynamic programming is a cutting plane type algorithm for multi-stage stochastic optimization originated about 30 years ago. In spite of its popularity in practice,…
Efficient Algorithms for Distributionally Robust Stochastic Optimization with Discrete Scenario Support
Zhe Zhang, Shabbir Ahmed, Guanghui Lan
Recently, there has been a growing interest in distributionally robust optimization (DRO) as a principled approach to data-driven decision making. In this paper, we consider a dist…
Stochastic First-order Methods for Convex and Nonconvex Functional Constrained Optimization
Digvijay Boob, Qi Deng, Guanghui Lan
Functional constrained optimization is becoming more and more important in machine learning and operations research. Such problems have potential applications in risk-averse machin…
GLAD: Learning Sparse Graph Recovery
Harsh Shrivastava, Xinshi Chen, Binghong Chen +4
Recovering sparse conditional independence graphs from data is a fundamental problem in machine learning with wide applications. A popular formulation of the problem is an …
A unified variance-reduced accelerated gradient method for convex optimization
Guanghui Lan, Zhize Li, Yi Zhou
We propose a novel randomized incremental gradient algorithm, namely, VAriance-Reduced Accelerated Gradient (Varag), for finite-sum optimization. Equipped with a unified step-size…