4 papers
On Nonsmooth and Relatively Weakly Convex Minimization
Chen Jiang, Jiawen Bi, Shuzhong Zhang
Composite optimization plays a central role in modern machine learning and signal processing, as it offers a natural balance between data fidelity and structural properties. In thi…
On Second-Order Methods for Bilevel Optimization
Jiawen Bi, Jiaxiang Li, Mingyi Hong +1
Bilevel optimization is an indispensable modeling tool for modern machine learning and engineering design. However, the theory and practice for finding second order stationary poin…
On Tackling High-Dimensional Nonconvex Stochastic Optimization via Stochastic First-Order Methods with Non-smooth Proximal Terms and Variance Reduction
Yue Xie, Jiawen Bi, Hongcheng Liu
When the nonconvex problem is complicated by stochasticity, the sample complexity of stochastic first-order methods may depend linearly on the problem dimension, which is undesirab…
A Correspondence-Driven Approach for Bilevel Decision-making with Nonconvex Lower-Level Problems
Xiaotian Jiang, Jiaxiang Li, Jiawen Bi +2
We consider bilevel optimization problems with general nonconvex lower-level objectives and show that the classical hyperfunction-based formulation is unsettled, since the global m…