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A New Simple Stochastic Gradient Descent Type Algorithm With Lower Computational Complexity for Bilevel Optimization
Haimei Huo, Risheng Liu, Zhixun Su
Bilevel optimization has been widely used in many machine learning applications such as hyperparameter optimization and meta learning. Recently, many simple stochastic gradient des…
Augmenting Iterative Trajectory for Bilevel Optimization: Methodology, Analysis and Extensions
Risheng Liu, Yaohua Liu, Shangzhi Zeng +1
In recent years, there has been a surge of machine learning applications developed with hierarchical structure, which can be approached from Bi-Level Optimization (BLO) perspective…
Averaged Method of Multipliers for Bi-Level Optimization without Lower-Level Strong Convexity
Risheng Liu, Yaohua Liu, Wei Yao +2
Gradient methods have become mainstream techniques for Bi-Level Optimization (BLO) in learning fields. The validity of existing works heavily rely on either a restrictive Lower-Lev…
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…
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…
Linearized Alternating Direction Method with Adaptive Penalty for Low-Rank Representation
Zhouchen Lin, Risheng Liu, Zhixun Su
Low-rank representation (LRR) is an effective method for subspace clustering and has found wide applications in computer vision and machine learning. The existing LRR solver is bas…