3 citations · 3 across the 3 of their papers we have counts for
4 papers
A Single-Loop, Constant-Batch First-Order Penalty Method for Stochastic Bilevel Optimization
Xingyu Chen, Ming Yang, Quanqi Hu +1
Recent advances in penalty-based methods for stochastic bilevel optimization (SBO) have eliminated the need for second-order derivative oracles. However, for stochastic nonconvex-s…
Single-loop Algorithms for Stochastic Non-convex Optimization with Weakly-Convex Constraints
Ming Yang, Gang Li, Quanqi Hu +2
Constrained optimization with multiple functional inequality constraints has significant applications in machine learning. This paper examines a crucial subset of such problems whe…
Stability and Generalization of Stochastic Compositional Gradient Descent Algorithms
Ming Yang, Xiyuan Wei, Tianbao Yang +1
Many machine learning tasks can be formulated as a stochastic compositional optimization (SCO) problem such as reinforcement learning, AUC maximization, and meta-learning, where th…
Momentum Accelerates the Convergence of Stochastic AUPRC Maximization
Guanghui Wang, Ming Yang, Lijun Zhang +1
In this paper, we study stochastic optimization of areas under precision-recall curves (AUPRC), which is widely used for combating imbalanced classification tasks. Although a few m…