5 papers
Nonconvex Composite Functional Constraints via First-Order Augmented Lagrangian Methods under Local Regularity
Linglingzhi Zhu, Jiajin Li
We study nonasymptotic convergence of primal-dual methods for a class of nonconvex constrained optimization problems with a convex-composite structure. In this class, both the obje…
Dual Quaternion SE(3) Synchronization with Recovery Guarantees
Jianing Zhao, Linglingzhi Zhu, Anthony Man-Cho So
Synchronization over the special Euclidean group SE(3) aims to recover absolute poses from noisy pairwise relative transformations and is a core primitive in robotics and 3D vision…
Efficient Single-Loop Stochastic Algorithms for Nonconvex-Concave Minimax Optimization
Xia Jiang, Linglingzhi Zhu, Taoli Zheng +1
Nonconvex-concave (NC-C) finite-sum minimax problems have wide applications in signal processing and machine learning tasks. Conventional stochastic gradient algorithms, which rely…
Nonsmooth Nonconvex-Nonconcave Minimax Optimization: Primal-Dual Balancing and Iteration Complexity Analysis
Jiajin Li, Linglingzhi Zhu, Anthony Man-Cho So
Nonconvex-nonconcave minimax optimization has gained widespread interest over the last decade. However, most existing works focus on variants of gradient descent-ascent (GDA) algor…
Shuffling Gradient Descent-Ascent with Variance Reduction for Nonconvex-Strongly Concave Smooth Minimax Problems
Xia Jiang, Linglingzhi Zhu, Anthony Man-Cho So +2
In recent years, there has been considerable interest in designing stochastic first-order algorithms to tackle finite-sum smooth minimax problems. To obtain the gradient estimates,…