13 citations · 30 across the 4 of their papers we have counts for
6 papers
Towards Extremely Fast Bilevel Optimization with Self-governed Convergence Guarantees
Risheng Liu, Xuan Liu, Wei Yao +2
Gradient methods have become mainstream techniques for Bi-Level Optimization (BLO) in learning and vision fields. The validity of existing works heavily relies on solving a series…
Towards Gradient-based Bilevel Optimization with Non-convex Followers and Beyond
Risheng Liu, Yaohua Liu, Shangzhi Zeng +1
In recent years, Bi-Level Optimization (BLO) techniques have received extensive attentions from both learning and vision communities. A variety of BLO models in complex and practic…
A Value-Function-based Interior-point Method for Non-convex Bi-level Optimization
Risheng Liu, Xuan Liu, Xiaoming Yuan +2
Bi-level optimization model is able to capture a wide range of complex learning tasks with practical interest. Due to the witnessed efficiency in solving bi-level programs, gradien…
Investigating Bi-Level Optimization for Learning and Vision from a Unified Perspective: A Survey and Beyond
Risheng Liu, Jiaxin Gao, Jin Zhang +2
Bi-Level Optimization (BLO) is originated from the area of economic game theory and then introduced into the optimization community. BLO is able to handle problems with a hierarchi…
A Generic First-Order Algorithmic Framework for Bi-Level Programming Beyond Lower-Level Singleton
Risheng Liu, Pan Mu, Xiaoming Yuan +2
In recent years, a variety of gradient-based first-order methods have been developed to solve bi-level optimization problems for learning applications. However, theoretical guarant…
Perturbation techniques for convergence analysis of proximal gradient method and other first-order algorithms via variational analysis
Xiangfeng Wang, Jane Ye, Xiaoming Yuan +2
We develop new perturbation techniques for conducting convergence analysis of various first-order algorithms for a class of nonsmooth optimization problems. We consider the iterati…