137 citations · 656 across the 54 of their papers we have counts for
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math.OC2020★ 33 cited
Global Convergence and Variance-Reduced Optimization for a Class of Nonconvex-Nonconcave Minimax Problems
Junchi Yang, Negar Kiyavash, Niao He
Nonconvex minimax problems appear frequently in emerging machine learning applications, such as generative adversarial networks and adversarial learning. Simple algorithms such as…
math.OC2020★ 6 cited
Bregman Augmented Lagrangian and Its Acceleration
Shen Yan, Niao He
We study the Bregman Augmented Lagrangian method (BALM) for solving convex problems with linear constraints. For classical Augmented Lagrangian method, the convergence rate and its…
math.OC2020★ 14 cited
Biased Stochastic First-Order Methods for Conditional Stochastic Optimization and Applications in Meta Learning
Yifan Hu, Siqi Zhang, Xin Chen +1
Conditional stochastic optimization covers a variety of applications ranging from invariant learning and causal inference to meta-learning. However, constructing unbiased gradient…