123 citations · 244 across the 36 of their papers we have counts for
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Compressed Decentralized Proximal Stochastic Gradient Method for Nonconvex Composite Problems with Heterogeneous Data
Yonggui Yan, Jie Chen, Pin-Yu Chen +3
We first propose a decentralized proximal stochastic gradient tracking method (DProxSGT) for nonconvex stochastic composite problems, with data heterogeneously distributed on multi…
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…
Non-convex Min-Max Optimization: Applications, Challenges, and Recent Theoretical Advances
Meisam Razaviyayn, Tianjian Huang, Songtao Lu +3
The min-max optimization problem, also known as the saddle point problem, is a classical optimization problem which is also studied in the context of zero-sum games. Given a class…