241 citations · 815 across the 44 of their papers we have counts for
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Inexact Proximal-Point Penalty Methods for Constrained Non-Convex Optimization
Qihang Lin, Runchao Ma, Yangyang Xu
In this paper, an inexact proximal-point penalty method is studied for constrained optimization problems, where the objective function is non-convex, and the constraint functions c…
A Data Efficient and Feasible Level Set Method for Stochastic Convex Optimization with Expectation Constraints
Qihang Lin, Selvaprabu Nadarajah, Negar Soheili +1
Stochastic convex optimization problems with expectation constraints (SOECs) are encountered in statistics and machine learning, business, and engineering. In data-rich environment…
Quadratically Regularized Subgradient Methods for Weakly Convex Optimization with Weakly Convex Constraints
Runchao Ma, Qihang Lin, Tianbao Yang
Optimization models with non-convex constraints arise in many tasks in machine learning, e.g., learning with fairness constraints or Neyman-Pearson classification with non-convex l…
Distributionally Robust Optimization with Confidence Bands for Probability Density Functions
Xi Chen, Qihang Lin, Guanglin Xu
Distributionally robust optimization (DRO) has been introduced for solving stochastic programs where the distribution of the random parameters is unknown and must be estimated by s…