11 citations · 18 across the 4 of their papers we have counts for
4 papers
Stochastic Inexact Augmented Lagrangian Method for Nonconvex Expectation Constrained Optimization
Zichong Li, Pin-Yu Chen, Sijia Liu +2
Many real-world problems not only have complicated nonconvex functional constraints but also use a large number of data points. This motivates the design of efficient stochastic me…
Zeroth-order Optimization for Composite Problems with Functional Constraints
Zichong Li, Pin-Yu Chen, Sijia Liu +2
In many real-world problems, first-order (FO) derivative evaluations are too expensive or even inaccessible. For solving these problems, zeroth-order (ZO) methods that only need fu…
Rate-improved Inexact Augmented Lagrangian Method for Constrained Nonconvex Optimization
Zichong Li, Pin-Yu Chen, Sijia Liu +2
First-order methods have been studied for nonlinear constrained optimization within the framework of the augmented Lagrangian method (ALM) or penalty method. We propose an improved…
Augmented Lagrangian based first-order methods for convex-constrained programs with weakly-convex objective
Zichong Li, Yangyang Xu
First-order methods (FOMs) have been widely used for solving large-scale problems. A majority of existing works focus on problems without constraint or with simple constraints. Sev…