82 citations · 546 across the 65 of their papers we have counts for
4 papers · 2 filters
Solving Convex Smooth Function Constrained Optimization Is Almost As Easy As Unconstrained Optimization
Zhe Zhang, Guanghui Lan
While Nesterov's Accelerated Gradient Descent (AGD) efficiently solves constrained problems when the constraint set $X \subseteq \bbr^n$ is simple and easy to project onto, it rema…
Projection-Free Functional Constrained Optimization for Risk Aversion and Sparsity Control
Yi Cheng, Guanghui Lan, Saeed Masiha +1
We study projection-free methods for functional constrained optimization with convex or smooth nonconvex objectives. Such problems arise in applications such as portfolio optimizat…
Level Constrained First Order Methods for Function Constrained Optimization
Digvijay Boob, Qi Deng, Guanghui Lan
We present a new feasible proximal gradient method for constrained optimization where both the objective and constraint functions are given by the summation of a smooth, possibly n…
Optimal Methods for Convex Risk Averse Distributed Optimization
Guanghui Lan, Zhe Zhang
This paper studies the communication complexity of convex risk-averse optimization over a network. The problem generalizes the well-studied risk-neutral finite-sum distributed opti…