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4 papers
On the Communication Complexity of Decentralized Stochastic Bilevel Optimization
Yihan Zhang, My T. Thai, Jie Wu +1
Stochastic bilevel optimization finds widespread applications in machine learning, including meta-learning, hyperparameter optimization, and neural architecture search. To extend s…
Gradient-Free Method for Heavily Constrained Nonconvex Optimization
Wanli Shi, Hongchang Gao, Bin Gu
Zeroth-order (ZO) method has been shown to be a powerful method for solving the optimization problem where explicit expression of the gradients is difficult or infeasible to obtain…
Decentralized Stochastic Gradient Descent Ascent for Finite-Sum Minimax Problems
Hongchang Gao
Minimax optimization problems have attracted significant attention in recent years due to their widespread application in numerous machine learning models. To solve the minimax pro…
Federated Compositional Deep AUC Maximization
Xinwen Zhang, Yihan Zhang, Tianbao Yang +2
Federated learning has attracted increasing attention due to the promise of balancing privacy and large-scale learning; numerous approaches have been proposed. However, most existi…